Innovation in Urban and Regional Planning: Proceedings of INPUT 2023 - Volume 1 (Lecture Notes in Civil Engineering, 467) 3031541170, 9783031541179

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Lecture Notes in Civil Engineering

Alessandro Marucci Francesco Zullo Lorena Fiorini Lucia Saganeiti   Editors

Innovation in Urban and Regional Planning Proceedings of INPUT 2023 - Volume 1

Lecture Notes in Civil Engineering

467

Series Editors Marco di Prisco, Politecnico di Milano, Milano, Italy Sheng-Hong Chen, School of Water Resources and Hydropower Engineering, Wuhan University, Wuhan, China Ioannis Vayas, Institute of Steel Structures, National Technical University of Athens, Athens, Greece Sanjay Kumar Shukla, School of Engineering, Edith Cowan University, Joondalup, WA, Australia Anuj Sharma, Iowa State University, Ames, IA, USA Nagesh Kumar, Department of Civil Engineering, Indian Institute of Science Bangalore, Bengaluru, Karnataka, India Chien Ming Wang, School of Civil Engineering, The University of Queensland, Brisbane, QLD, Australia Zhen-Dong Cui, China University of Mining and Technology, Xuzhou, China

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Alessandro Marucci · Francesco Zullo · Lorena Fiorini · Lucia Saganeiti Editors

Innovation in Urban and Regional Planning Proceedings of INPUT 2023 - Volume 1

Editors Alessandro Marucci DICEAA University of L’Aquila L’Aquila, Italy

Francesco Zullo DICEAA University of L’Aquila L’Aquila, Italy

Lorena Fiorini DICEAA University of L’Aquila L’Aquila, Italy

Lucia Saganeiti DICEAA University of L’Aquila L’Aquila, Italy

ISSN 2366-2557 ISSN 2366-2565 (electronic) Lecture Notes in Civil Engineering ISBN 978-3-031-54117-9 ISBN 978-3-031-54118-6 (eBook) https://doi.org/10.1007/978-3-031-54118-6 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Paper in this product is recyclable.

Dedication

These volumes are the result of the collection of papers from the 12th International Conference on Innovation in Urban and Regional Planning (INPUT 2023): “Working for sustainable soil management and the role of land planning” and they are a tribute to the memory of Professor Bernardino Romano, who passed away prematurely on 1st September 2023, just before the conference took place. INPUT 2023 was possible due to his foresight and recognition in the academic world. Prof. Bernardino Romano has been a full professor of Urban Planning at the University of L’Aquila. He had considerable influence on the development of his subject over a period of more than 30 years and provided much support to a generation of researchers and colleagues. Since the beginning of his academic career, Prof. Romano has dedicated himself to the study of the relationship between the natural and built environment. He has been passionate about the issue of protected areas and ecological networks, expanding the existing meaning of concepts such as biopermeability and environmental continuity. In the eighties, he has been one of the first promoters of the institution of the main parks in Central Italy. His commitment in this direction was both academic and personal, through an intense activity at top level with the World Wide Fund for Nature (WWF) and the Italian Alpine Club (CAI). During these years, he has developed studies on land planning tools aimed at the establishment of both protected areas in Abruzzo region and the system of European Apennine Parks (APE). He has been a strong supporter of biodiversity conservation, and he made the knowledge of ecosystem dynamics a key point of his courses at university. Prof. Romano has been a national reference for land take dynamics inspiring research and studies by many research groups. He always has been strongly convinced that land and urban planning plays a key role in sustainability of transformations. In fact, the dynamics of land transformation have always been a focus of his research and he has worked for years for drawing a precise and analytic description of the Italian settlement evolution. In the last period, he was active in the national discussion about drafting a law for stopping land consumption. He has approached urban planning, ecology, and landscape both inside and outside the academic context, enriching the research with humanity. He has always been fascinated by the computational aspects of urban planning and by the possibility to explore new scientific approaches based on data analysis and indicator engineering. He has been a courageous explorer into this field, always looking for innovating the panorama of techniques and tools for spatial diagnosis. Thanks to his creative vision, integrity, rigorous research, scientific excellence, and exceptionally broad intellectual horizons, he has left his imprint on the lives of students, PhD students, young researchers as well as many colleagues and collaborators from various institutions. He has also taught the value of autonomy of thought and collaboration.

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Dedication

He did so with passion, dedication, and desire to spread his great knowledge of Land Sciences. He has left us with a significant legacy that we are going to preserve and share. November 2023

CENTROPLANECO

Preface

The 12th International Conference on Innovation in Urban and Regional Planning (INPUT 2023) has been organized by CENTROPLANECO group of DICEAA— Department of Civil, Construction-Architectural and Environmental Engineering of the University of L’Aquila. It took place in L’Aquila (Italy) on 6–8 September 2023 and has been titled “Working for sustainable soil management and the role of land planning”. Global challenges related to the sustainability of land transformations require the measurement of land transformations through specific indicators. Spatial planning and land management systems then play a crucial role in addressing issues of policy reform and investment, ecological transition, and sustainability in its three dimensions: environmental, economic, and social aspect. Integrating sustainability into our policies, strategies, and practices is fundamental to making a relevant impact with respect to current issues related to climate change, ecosystem services’ provision and the energy supply. INPUT 2023 has given the opportunity to discuss such central issues and try to find and assess innovative and advanced methodologies to provide decision support systems through land science and indicator engineering. Those proceedings represent the state of the art of modelling and computational approaches to innovations in urban and regional planning, with a transdisciplinary and borderless character to address the complexity of contemporary socio-ecological systems and following a practice-oriented and problem-solving approach. In particular, this book presents the collection of 62 papers submitted at the INPUT 2023 Conference. The accepted papers, after a blind-review process, are here organized according to the thematic sessions of the conference: – Geospatial earth data to support the restoration of soil ecosystems and implications for spatial planning (geo4sp). – Geodesign for informed collaborative spatial planning and design. – The urban digital twin: a new dimension for the land planning. – Spreading porosity: the contribution of planning tools in increasing soil permeability. – Research and standards for sustainable spatial planning (R&S4SP). – Coastal planning: diagnostic tools to address physical, social, and environmental concerns. – Territorial strategies in place-based and community-led energy transitions. – Innovative simulations for urban planning: decoding configuration, morphology, and space. – The energy transition of the built environment. – Innovations in the 15 minute-city approaches: conceptual, data-driven, and practical developments towards a sustainable urban planning. INPUT is a scientific community of Italian university and academic researchers who meet every two years and discuss issues from different fields related to urban and regional planning topics.

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The latest editions have been hosted in Viterbo (2018), Turin (2016), Cagliari (2014), Potenza (2012), Catania (2021), and L’Aquila (2023). During INPUT 2023 (L’Aquila), the conference recorded the following numbers: • 20 parallel sessions have been organized from experts in different fields of research related to urban and land planning. • 171 submitted abstracts. • 124 accepted papers. • 130 among online and in presence participants.

Keynote Speakers of the INPUT 2023 Conference Three keynote speakers enrich the programme during three plenary sessions. Speeches have been held by: Sara Meerow, School of Geographical Sciences and Urban Planning, Arizona State University She is an associate professor in the School of Geographical Sciences and Urban Planning at Arizona State University where she leads the Planning for Urban Resilience Lab. She is an interdisciplinary scholar working at the intersection of urban geography and planning to tackle the challenge of making cities more resilient in the face of climate change and other social and environmental hazards, while at the same time more sustainable and just. Her current projects focus on conceptualizations of urban resilience, planning for urban resilience in a changing climate, and green infrastructure planning in a range of cities in the USA and internationally. She has published over 30 articles in academic journals, in addition to book chapters, reports, and popular press articles on these topics. She has a PhD in Natural Resources and Environment from the University of Michigan and an MS in International Development Studies from the University of Amsterdam. Title of keynote speech: Urban climate change resilience planning in theory and practice Jacques Teller, Local Environment Management and Analysis, University of Liège, Belgium He is a professor of urban planning at the University of Liège, where he is leading the Local Environment Management and Analysis (LEMA) research group. He is a member of the Scientific Council of the Lab Research Environment (Vinci, ParisTech) and of the Efficacity Research Institute in France. His research typically combines urban governance issues with the modelling of urbanization and densification dynamics. It addresses the impacts of urbanization on energy consumption, heritage management, housing provision, and transport demand. He is presently working on the interactions between urbanization and exposure to floods, combining quantitative modelling and qualitative approaches. Title of keynote speech: Urban growth models for regulating urban densification in response to zero net land take policies Claudia (van der Laag) Yamu, Department of Built Environment, Oslo Metropolitan University, Oslo, Norway

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She is an architect and urban planner. She is a professor of urban analytics at Oslo Metropolitan University. She is an expert on transport land use planning including people’s behaviour in cities applying a wide range of analytical techniques including method and tool development at the forefront of virtual modelling. As a former project consultant, she excels in combining the theoretical innovations with practice-oriented solutions and has been involved in numerous international projects in industry and research. Claudia was awarded the prestigious Michael Breheny Prize in 2015 for her work on multiscale, multifractal urban planning models. She is an editorial board member for Springer’s the Urban Book Series. She holds a PhD in Architecture from TU Wien connecting architecture, urban planning, and computer science and a PhD in Geography and Regional Planning in complexity-based modelling from Université de Franche-Comté. She dedicates her work to the development of sustainable cities and regions. Title of keynote speech: Accessibility and multiscalarity: fractal urban planning models

Best Paper Award Among the contributions, four papers have been selected for the Best Paper awards: 1. Giovanni Cialone Best Paper Award addressed to studies on inner areas, protected areas, and sustainable development. The award is dedicated to the memory of Giovanni Cialone: architect, passed away in 2020. He has been a CNR researcher (National Research Council) and served in the 1990s as an environmental councillor for the municipality of L’Aquila. He was highly committed to issues related to environmental protection and education, sustainability, and cultural enhancement of inner areas. He held the position of vice-president of the Gran Sasso–Monti della Laga National Park and was a member of the “Italia Nostra” association and a delegate of Slow Food. He enriched the debate about knowledge and defence of the territory defence, with a strong presence in the media and interventions in the political sphere, consistently displaying a well-regarded balance in his positions and numerous contributions of critique. The award goes to the paper titled: “The shapes of the adaptive ground design: formulation of a new taxonomy between spatial quality and ecological performance” authored by: Simone Porfiri, University of Camerino (Italy). 2. Giorgio Pipponzi Best Paper Award addressed to studies on advanced GIS techniques. The award is dedicated to the memory of Giorgio Pipponzi: After his studies in geology and a PhD in geodynamics, he carried out highly professional positions in the Abruzzo Region, with the Basin Authority and the Civil Protection Service. He collaborated in the drafting of the Guidelines for the Seismic Microzoning Plans, in the development and management of computer databases as well as in the Level 3 Microzoning Pilot Project in the municipality of Sulmona. Since 2013 in the USRC, he has carried out his activity as Technical Geologist Directive Instructor, dealing with the geological problems inherent in the Reconstruction Plans and Private Reconstruction projects as well as being responsible for the GIS systems of the USRC. In 2019, he was appointed Head of the Procedure for the technical-economic investigation of the private reconstruction projects after the 2009 earthquake.

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The award goes to the paper titled: “The applicability of the urban digital twin in the detailed choices of the urban plan” authored by: Federica Cicalese, University of Salerno (Italy). 3. LAND Best Paper Award addressed to studies on urbanization phenomena, densification, and land consumption. The award intends to enhance the merit of young researchers who will present scientifically relevant papers on topics related to urbanization phenomena, densifications, and contrasting land consumption. Work should focus on the role of urban and regional planning in urban growth management with the goal to meet specific needs while increasing the resilience of urban settlements. This award refers to the special issue “Towards Sustainable Urban Development: New Approaches and Tools for Regeneration Strategies”. The award goes to the papers: • “Space Syntax vs Agent-Based Modelling in the maze of urban complexity: a critical comparison between top-down and bottom-up approaches and applications” authored by: Federico Mara, University of Pisa (Italy). • “Urban energy resilience and strategic urban planning in Emilia-Romagna: evidence from three cities” authored by: Giovanni Tedeschi, University of Parma (Italy). • “Digital Twin for urban development” authored by: Angela Martone and Monica Buonocore, University of Sannio (Italy). November 2023

Alessandro Marucci Francesco Zullo Lorena Fiorini Lucia Saganeiti

Organization

The 12th International Conference on Innovation in Urban and Regional Planning (INPUT 2023) was organized by the CENTROPLANECO group of the DICEAADepartment of Civil, Building, Architectural, and Environmental Engineering of the University of L’Aquila. The composition of the organizing groups is shown in detail below.

Local Scientific Committee Romano Bernardino

Marucci Alessandro

Zullo Francesco

Fiorini Lorena

Saganeiti Lucia

De Berardinis Pierluigi

Rotilio Marianna

Di Risio Marcello

Pasquali Davide

Celli Daniele

Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy

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Organization

Organizing Committee Fiorini Lorena (Coordinator)

Saganeiti Lucia (Coordinator)

Di Dato Chiara

Pilogallo Angela

Falasca Federico

Sette Camilla

Montaldi Cristina

Cattani Chiara

Di Pietro Gianni

Ulisse Carmen

CENTROPLANECO Lab-Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy CENTROPLANECO Lab-Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy CENTROPLANECO Lab-Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy CENTROPLANECO Lab-Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy CENTROPLANECO Lab-Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy CENTROPLANECO Lab-Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy CENTROPLANECO Lab-Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy CENTROPLANECO Lab-Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy CENTROPLANECO Lab-Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy CENTROPLANECO Lab-Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy

Organization

Felli Annamaria

Marziali Emilio

Tomei Vanessa

CENTROPLANECO Lab-Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy CENTROPLANECO Lab-Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy CENTROPLANECO Lab-Department of Civil, Construction-Architectural and Environmental Engineering–DICEAA, University of L’Aquila, Italy

Scientific Committee Balletto Ginevra Barbarossa Luca Blecic Ivan Borri Dino Bottero Marta Brunetta Grazia Busi Roberto Camarda Domenico Campagna Michele Carpentieri Gerardo Cecchini Arnaldo Cerreta Maria Cialdea Donatella Colavitti AnnaMaria Concilio Grazia Congiu Tanja Cortinovis Chiara Cutini Valerio De Luca Claudia De Montis Andrea Del Ponte Ilaria Di Gangi Massimo Fasolino Isidoro Fiorini Lorena Fistola Romano Garau Chiara Gargiulo Carmela

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University of Cagliari University of Catania University of Cagliari Polytechnic University of Bari Polytechnic University of Turin Polytechnic University of Turin University of Brescia Polytechnic University of Bari University of Cagliari University of Naples “Federico II” University of Sassari University of Naples “Federico II” University of Molise University of Cagliari Polytechnic University of Milan University of Sassari University of Trento University of Pisa University of Bologna University of Sassari University of Genoa University of Messina University of Salerno University of l’Aquila University of Naples “Federico II” University of Cagliari University of Naples “Federico II”

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Organization

Geneletti Davide Gerundo Roberto Grimaldi Michele La Greca Paolo La Rosa Daniele Lai Sabrina Las Casas Giuseppe Leone Antonio Lombardi Patrizia Lombardini Giampiero Maciocco Giovanni Maragno Denis Marucci Alessandro Moccia Francesco Murgante Beniamino Musco Francesco Nocera Silvio Occelli Sylvie Papa Rocco Pelorosso Raffaele Pezzagno Michele Pinto Fulvia Plaisant Alessandro Pontrandolfi Piergiuseppe Pratelli Antonio Privitera Riccardo Romano Bernardino Ronchi Silvia Russo Michelangelo Saganeiti Lucia Scorza Francesco Tiboni Michela Tira Maurizio Tondelli Simona Torre Carmelo Maria Voghera Angioletta Zoppi Corrado Zullo Francesco

University of Trento University of Salerno University of Salerno University of Catania University of Catania University of Cagliari University of Basilicata University of Salento Polytechnic University of Turin University of Genoa University of Sassari IUAV university of Venice University of l’Aquila University of Naples “Federico II” University of Basilicata IUAV University of Venice IUAV University of Venice IRES Piemonte University of Naples “Federico II” Tuscia University University of Brescia Polytechnic University of Milan University of Sassari University of Basilicata University of Pisa University of Catania University of l’Aquila Polytechnic University of Milan University of Naples “Federico II” University of l’Aquila University of Basilicata University of Brescia University of Brescia University of Bologna Polytechnic University of Bari Polytechnic University of Turin University of Cagliari University of l’Aquila

Organization

Conference Session Organizers Resilient, Circular, and Sustainable Cities Balletto Ginevra Ladu Mara Trinh tu Anh Borruso Giuseppe Fancello Gianfranco Balázs Kulcsár

University of Cagliari University of Cagliari University of Economics Ho Chi Minh University of Trieste University of Cagliari University of Debrecen

Geospatial Earth Data to Support the Restoration of Soil Ecosystems and Implications for Spatial Planning Tarantino Eufemia Esposito Dario Capolupo Alessandra

Polytechnic University of Bari Polytechnic University of Bari Polytechnic University of Bari

Geodesign for Informed Collaborative Spatial Planning and Design Campagna Michele Mourao Moura Ana Clara Scorza Francesco

University of Cagliari Universidade Federal de Minas Gerais University of Basilicata

Integrating Ecosystem Services into Spatial Planning Processes: Sustainable Solutions for Healthier and Safer Urban and Rural Environments Privitera Riccardo Lai Sabrina Zoppi Corrado

University of Catania University of Cagliari University of Cagliari

The Urban Digital Twin: A New Dimension for the Land Planning Fistola Romano Fasolino Isidoro

University of Naples Federico II University of Salerno

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Organization

Supporting the Transition Towards Ecologically-Oriented Urban Planning: What’s the Role of Early-Career Researchers? Innovative Findings, Experiences, and Ways Forward De Luca Claudia Ronchi Silvia Cortinovis Chiara

University of Bologna Polytechnic University of Milan University of Trento

Towards Denser and Greener Cities? Methods and Indicators to Monitor Trends And Impacts in Support of Urban Planning and Policies Cortinovis Chiara Ronchi Silvia Geneletti Davide

University of Trento Polytechnic University of Milan University of Trento

Innovative Approaches and Methodologies for Driving Sustainable and Inclusive Urban Regeneration Saganeiti Lucia Fiorini Lorena Pilogallo Angela

University of L’Aquila University of L’Aquila University of L’Aquila

The Innovation of Urban Planning Tools for Energy-Resilient Cities Guida Carmen Gargiulo Carmela Cutini Valerio Zazzi Michele Zucaro Floriana Carpentieri Gerardo

University of Naples Federico II University of Naples Federico II University of Pisa University of Parma University of Naples Federico II University of Naples Federico II

Spreading Porosity: the Contribution of Planning Tools in Increasing Soil Permeability Garda Emanuele Caselli Barbara

University of Bergamo University of Parma

Research and Standards for Sustainable Spatial Planning Esposito Dario Gueze Raffaella Francesca Bretzel Francesca

Polytechnic University of Bari Cord Agende 21 locali italiane, Padova National Research Council, Pisa

Organization

Tundo Antonella Capezzuto Pasquale

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National Agency for New Technology UNI International Standardization Organization

Coastal Planning: Diagnostic Tools to Address Physical, Social, and Environmental Concerns Di Risio Marcello Pasquali Davide Celli Daniele Castellino Myrta Scipione Francesca Fischione Piera

University of L’Aquila University of L’Aquila University of L’Aquila Sapienza University of Rome Sapienza University of Rome University of Rome “Tor Vergata”

Territorial Strategies in Place-Based and Community-Led Energy Transitions Grassini Laura Bonifazi Alessandro

Polytechnic University of Bari Polytechnic University of Bari

Innovative Simulations for Urban Planning: Decoding Configuration, Morphology, and Space Cutini Valerio Altafini Diego

University of Pisa University of Pisa

The Energy Transition of the Built Environment Rotilio Marianna Marchionni Chiara

University of L’Aquila University of L’Aquila

Smart Happy Region. Relationship Between Planning and Subjective Well-Being Garau Chiara Murgante Beniamino Gervasi Osvaldo Rossetti Silvia Campisi Tiziana Desogus Giulia Annunziata Alfonso

University of Cagliari University of Basilicata University of Perugia University of Parma University of ENNA “Kore” University of Cagliari University of Cagliari

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Organization

Innovations in the 15 Minute-City Approaches: Conceptual, Data-Driven, and Practical Developments Towards a Sustainable Urban Planning Murgante Beniamino Garau Chiara Cutini Valerio Nesi Paolo Zamperlin Paola Altafini Diego Delponte Ilaria

University of Basilicata University of Cagliari University of Pisa University of Florence University of Pisa University of Pisa University of Genoa

Climate Sensitive Planning: Re-defining Urban Environments for Sustainable Cities La Rosa Daniele Stanganelli Marialuce Gerundo Carlo

University of Catania University of Naples University of Naples

Urban and Peri-Urban Areas: Building Knowledge and Mapping to Better Plan the Sustainable Green City Fiorini Lorena Pierantoni Ilenia Di Dato Chiara Giacomelli Matteo Marucci Alessandro Sargolini Massimo

University of L’Aquila University of Camerino University of L’Aquila University of Camerino University of L’Aquila University of Camerino

Densification and Urban Regeneration for Climate Adaptation in Sustainable Settlements Romano Bernardino Marucci Alessandro Zullo Francesco Fiorini Lorena Saganeiti Lucia

University of L’Aquila University of L’Aquila University of L’Aquila University of L’Aquila University of L’Aquila

Organization

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Sponsoring and Patronage Organization The conference was sponsored by: – Springer publishing group – LAND (open access journal by MDPI) – Special Office for the Reconstruction of the Municipalities of the Crater–USRC (Ufficio Speciale per la Ricostruzione dei Comuni del Cratere) – Slow Food L’Aquila – Abruzzo Region – Province of L’Aquila – Municipality of L’Aquila – National Association of Building Constructors-ANCE and Young ANCE (Associazione Nazionale Costruttori Edili) – Association of engineers of the province of L’Aquila – Association of the architects of the province of L’Aquila – Institute for Environmental Protection and Research-ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale) – Italian standardization body-UNI (Ente Italiano di Normazione)

Contents

Geospatial Earth Data to Support the Restoration of Soil Ecosystems and Implications for Spatial Planning (GEO4SP) A Customized JAVA OpenStreetMap Preset to Extract Solar Panel Installations for Humanitarian Purposes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Claudio Ladisa, Alessandra Capolupo, and Eufemia Tarantino

3

Copernicus Geodatabase for Investigating Land Cover Changes at the European Scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Carlo Barletta, Alessandra Capolupo, and Eufemia Tarantino

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Earth Observation Data for Sustainable Management of Water Resources to Inform Spatial Planning Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alessandra Capolupo, Carlo Barletta, Dario Esposito, and Eufemia Tarantino

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Future Urban Setting and Effects on the Hydrographic System. The Case Study of Bologna, Italy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Emilio Marziali, Gianni Di Pietro, and Cristina Montaldi

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Using SAR Observation Data to Support the Spatial Planning in Areas Affected by Landslide Phenomena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alberico Sonnessa

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Geodesign for Informed Collaborative Spatial Planning and Design Geodesign as a Supplementary Tool to Strategic Environmental Assessment . . . Luanita Snyman-van der Walt Geovisualization and Geodesign in a Framework for the Evaluation of Landscape Units as a Basis for the Sustainable Planning of the Quadrilátero Ferrífero, Brazil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ana Clara Mourão Moura, Christian Rezende Freitas, Alfio Conti, Ítalo Sousa De Sena, Nicole Andrade Rocha, Danilo M. Magalhães, and Gustavo A. T. Martinez Participatory Mapping to Improve Urban Resilience Starting from the Experiences in the Scientific Literature and Virtuous Cases . . . . . . . . . . Ilenia Spadaro, Fabrizio Bruno, Maria Cristina Lobascio, and Francesca Pirlone

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Geodesign in the Shared Decision to Create Full Protection Conservation Units, as a Mitigating and Compensatory Action for the Transformations of Iron Mining in the Landscape . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Flávia Las-Cazas de Brito and Ana Clara Mourão Moura

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Geoprocessing, Geodesign and Urban Parameters: Geoinformation and Co-Creation of Ideas in Urban Planning Teaching . . . . . . . . . . . . . . . . . . . . . . 102 Ashiley Adelaide Rosa and Ana Clara Mourão Moura Geodesign: (a Personal) Retrospective, and Perspectives . . . . . . . . . . . . . . . . . . . . 114 Michele Campagna Geodesign in the Teaching Process of Global Agreements: Sustainable Development Goals and Smart Cities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 Fabiana Carmo De Vargas Vieira, Tiago Mello, and Ana Clara Mourão Moura Geodesign for Open Spaces Management in Mining-Dependent Urban Settlements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 Luiz Glück Lima, Camila Marques Zyngier, Christian Freitas, and Ana Clara Mourão Moura Strategies for Democratizing Development. Application of Geodesign in a Low-Context Culture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 Simone Corrado, Luigi Santopietro, Alfonso Annunziata, Rosanna Piro, Rachele Vanessa Gatto, Rossella Scorzelli, Shiva Rahmani, Francesco Scorza, and Beniamino Murgante The Urban Digital Twin: A New Dimension for the Land Planning Applying 4.0 Technologies to Public Spaces. Exploring New Functions and Interactions in Savona University Campus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 Daniele Soraggi and Federico Campanini Urban Built Environment Visual Features Modeling for 3D GeoSimulation Using USD Standard Specifications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Igor Agbossou Digital Twin for Urban Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 Angela Martone and Monica Buonocore Digital Twins of Cities vs. Digital Twins for Cities . . . . . . . . . . . . . . . . . . . . . . . . . 192 Maria Rosaria Stufano Melone, Stefano Borgo, and Domenico Camarda

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Beyond the Smart City. The Urban Digital Twin for the Augmented City: The Vox Hortus Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 Romano Fistola and Ida Zingariello The Applicability of the Urban Digital Twin in the Detailed Choices of the Urban Plan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 Federica Cicalese, Michele Grimaldi, and Isidoro Fasolino Urban and Spatial Planning Through the Support Tool of the Regional Digital Twin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221 Sara Sacco, Federico Eugeni, and Donato Di Ludovico Towards Sustainable Urban Development: Matera’s Urban Digital Twin and Challenges in Data Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230 Simone Corrado and Francesco Scorza City Burning: New Approaches to Measure the UHI and Its Effect on Urban Energy Balance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 Federica Gaglione, Carmela Gargiulo, and Floriana Zucaro Spreading Porosity: The Contribution of Planning Tools in Increasing Soil Permeability A Multidimensional Assessment Model of Settlement Efficiency at the Urban Scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251 Federica Cicalese and Isidoro Fasolino The Shapes of Adaptive Ground Design: A New Taxonomy Between Spatial Quality and Ecological Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263 Simone Porfiri Urban Planning and Water Resources: Integrated Regeneration Strategies for Contemporary Territories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275 Laura Ricci and Sofía Gabriela Fernández Balmaceda Towards the Integration of Soil Desealing in the Urban Areas’ Transformation Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286 Barbara Caselli, Marianna Ceci, Ilaria De Noia, Emanuele Garda, and Michele Zazzi

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Research and Standards for Sustainable Spatial Planning (R&S4SP) Holistic Approach for Sustainable Cities and Communities: Best Practices in Living Labs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301 Antonella Tundo, Pasquale Capezzuto, Laura Blaso, Paolo Marinucci, and Guglielmina Mutani Need of New Standards for New Definition of Cities . . . . . . . . . . . . . . . . . . . . . . . . 313 Pierluigi Potenza The Issue of Standards Development for Sustainable Cities and Communities: ISO 37101 Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325 Angela Ruggiero, Bruno Barroca, Margot Pellegrino, and Vincent Becue Establishing a Knowledge Value Chain for Sustainable Spatial Planning and Urban Governance: Meeting the SDGs Through Technical Standards . . . . . . 337 Dario Esposito, Raffaella Francesca Gueze, Francesca Bretzel, Antonella Tundo, and Pasquale Capezzuto Towards a Definition of “Tourism Ecosystem” for Sustainable Development of Inland Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350 Rachele Vanessa Gatto, Simone Corrado, Beniamino Murgante, and Francesco Scorza The Planning Tool Mosaic as a Tool for Sustainable Land Management. Keys Point for a National Regulatory Framework . . . . . . . . . . . . . . . . . . . . . . . . . . 359 Cristina Montaldi, Chiara Cattani, and Francesco Zullo Mapping Civic Uses in Abruzzo Region: Opportunities for Sustainable Resource Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373 Chiara Cattani and Francesco Zullo Spatial Decision Making for Improvement of the Resilience of the Historic Areas: SHELTER DSS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 384 Asel Villanueva-Merino, Amaia López-de-Aguileta-Benito, Jose Luis Izkara, and Aitziber Egusquiza Achieving SDGs through Public Participation in Spatial Planning and Urban Governance: International Standards for Effective Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 396 Dario Esposito, Giulia Motta Zanin, Pasquale Balena, and Valeria Monno

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Embedding Resilience to Climate Change and Natural Hazards in Smart Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 408 Sonia Giovinazzi, Maria Luisa Villani, Roberta Pezzetti, Nicoletta Gozo, Laura Blaso, Antonio Costanzo, and Quintilio Piattoni Coastal Planning: Diagnostic Tools to Address Physical, Social and Environmental Concerns Port Cities. Models of Governance, Port and Local Planning and Sub-areas of City-Port Interaction. The Case of Livorno and Valencia . . . . . . . . . . . . . . . . . . 423 Carmela Mariano and Maria Racioppi Analysis of the Influence of Coastal Urban Regeneration Strategies on Water Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 435 Annamaria Felli, Francesco Zullo, and Marcello Di Risio Extreme Sea Level Variation in Future Climate Change Scenarios: The Case of Abruzzo Region Coastal Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 446 Davide Pasquali, Daniele Celli, Carmine Di Nucci, Piera Fischione, and Marcello Di Risio Physics and Coastal Planning Strategies: Two Sides of the Same Coin . . . . . . . . . 457 Marcello Di Risio and Luca Iagnemma Long-Term Evolution of the Shoreline of the South Lazio Region (Italy) Littoral Cell by Combining Historical Aerial Photography and Satellite Imagery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 466 Francesca Scipione, José Antonio Palenzuela Baena, Marcello Di Risio, Maria Antonietta Marsella, Myrta Castellino, and Paolo De Girolamo Distribution of Polycyclic Aromatic Hydrocarbons and Organochlorine Pesticides in Two Coastal Sediment Cores in the Mong Cai Area, Vietnam . . . . . 478 Bui Thi Thanh Loan, Nguyen Thi Hue, Hoang Nam, Vu Van Tu, Pham Thi Kha, Pham Tien Dung, Nguyen Thi Mai Luu, Paolo Roccaro, Daniele La Rosa, and Dang Hoai Nhon Coastal Urbanization and Ecosystem Services Depletion: An Italian Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 490 Giampiero Lombardini, Angela Pilogallo, and Giorgia Tucci

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Territorial Strategies in Place-Based and Community-Led Energy Transitions Modeling Structural Equations to Balance the Positive Energy Area in Cities . . . 503 Nastaran Esmaeilpour Zanjani, Ghazaleh Goodarzi, Caterina Pietra, and Roberto De Lotto Urban Polycentric Structures: Scenarios of Energy Communities of Small and Medium-Sized Cities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512 Pasquale Balena, Michele Vomero, and Antonio Leone Place-Based Strategies for Energy Transitions in Apulia: Pilot Experiences, Limitations and Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 523 Alessandro Bonifazi and Laura Grassini Innovative Simulations for Urban Planning: Decoding Configuration, Morphology and Space Percolation Model to Capture Urban Coalescence («Natural Cities»). The Case of Italy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 539 Giampiero Lombardini Preprocessing Open Data for Optimizing Estimation Times in Urban Network Analysis: Extracting, Filtering, Geoprocessing, and Simplifying the Road-Center Lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 551 Müslüm Hacar, Federico Mara, Diego Altafini, and Valerio Cutini Urban Safety and Resilience: Agent-Based Modelling Simulations for Pre-disaster Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 563 Federico Eugeni, Sara Sacco, and Donato Di Ludovico Territorial Analysis of Regional Disparities in Brazil: Impacts on Sustainable Urban Mobility and Accessibility . . . . . . . . . . . . . . . . . . . . . . . . . . . 573 Franciele Marques Space Syntax vs Agent-Based Modelling in the Maze of Urban Complexity: A Critical Comparison Between Top-Down and Bottom-Up Approaches and Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 585 Federico Mara and Valerio Cutini

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The Energy Transition of the Built Environment The Energy Efficiency of Building Components. The Case of Historical Masonry Through a Multidisciplinary Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 599 Marianna Rotilio, Chiara Marchionni, Pierluigi De Berardinis, and Federica Cucchiella Urban Energy Analysis and Building Performance Evaluation: The Case of Segrate Municipality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 609 Elisabetta Venco, Luca Alessio, Tancredi Marco De Francesco, and Nastaran Esmaeilpour Zanjani Establishing a Renewable Energy Community in a Residential District: Advantages and Implementation Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 621 Cristina Montaldi and Luca Giannobile Innovative and Sustainable Solutions for the Organization of Energy and Service Networks in Historical Centres . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 632 Marianna Rotilio, Chiara Marchionni, and Alessia Massari Innovations in the 15 Minute-City Approaches: Conceptual, Data-Driven, and Practical Developments Towards a Sustainable Urban Planning Tackling Un-sustainable Mobility. Smart City Tools to Limit Car Access to the City Center Through MaaS Solutions, the Genoese Experience . . . . . . . . . 645 Ilaria Delponte and Valentina Costa Travel-Time in a Grid: Modelling Movement Dynamics in the “Minute City” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 657 Camilla Pezzica, Diego Altafini, Federico Mara, and Chiara Chioni Building a 15-Minute City: A Methodological Approach for Assessing the Socio-economic and Environmental Effects of Locating Amenities in Low-Density Settlement Contexts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 669 Gennaro Pace, Lucia Saganeiti, Valentina Santarsiero, and Beniamino Murgante Spatial and Configurational Analysis for the Implementation of the 15-Minute City Model. The Case Study of Perugia, Italy . . . . . . . . . . . . . . . 681 Lucia Patimisco, Alfonso Annunziata, and Beniamino Murgante Assessing the Relationship Between Spatial Configuration and Proximity to Basic Services. The Case Studies of Matera and Terni, Italy . . . . . . . . . . . . . . . 693 Raffaela Valluzzi, Alfonso Annunziata, and Beniamino Murgante

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Possibility, Opportunity, Capability. A Critical Reinterpretation for Accessibility Planning in the 15-Min City . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 705 Alessia Guaiani Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 717

List of Contributors

Igor Agbossou Laboratoire ThéMA, UMR 6049, IUT NFC, Université de FrancheComté, Belfort, France Luca Alessio Municipality of Segrate (MI), Segrate, Italy Diego Altafini University of Pisa, Pisa, PI, Tuscany, Italy Alfonso Annunziata Laboratory of Urban and Regional System Engineering (LISUT), School of Engineering, University of Basilicata, Potenza, Italy Maria Antonietta Marsella Department of Civil, Building and Environmental Engineering (DICEA), Sapienza University of Rome, Rome, RM, Italy Pasquale Balena Polytechnic University of Bari, Bari, Italy Sofía Gabriela Fernández Balmaceda Department of Planning, Design and Technology of Architecture, Sapienza University of Rome, Rome, Italy Carlo Barletta Department of Civil, Environmental, Land, Building Engineering and Chemistry (DICATECh), Polytechnic University of Bari, Bari, Italy Bruno Barroca Lab’Urba - Université Gustave Eiffel, Champs-sur-Marne, France Vincent Becue Faculté d’Architecture et d’Urbanisme, UMONS, Mons, Belgium Laura Blaso ENEA Smart Cities and Communities Laboratory, Smart Energy Division, Department of Energy Technologies and Renewable Sources, Italian National Agency for New Technologies, Energy and Sustainable Economic Development, ENEA, Rome, Italy Alessandro Bonifazi Polytechnic University of Bari, Bari, Italy Stefano Borgo Laboratory for Applied Ontology, CNR-ISTC, Trento, Italy Francesca Bretzel CNR Istituto di Ricerca sugli Ecosistemi Terrestri, Pisa, Italy Fabrizio Bruno Department of Civil, Chemistry and Environmental Engineering, University of Genoa, Genoa, GE, Italy Monica Buonocore Università degli Studi del Sannio, Benevento, Italy Domenico Camarda Polytechnic University of Bari, Bari, Italy Michele Campagna University of Cagliari, Cagliari, Italy Federico Campanini Italian Excellence Centre for Logistics, Infrastructures and Transport, University of Genoa, 16126 Genoa, Italy Pasquale Capezzuto UNI TC 058 - Sustainable, Cities, Communities and Infrastructures, Milan, Italy

xxx

List of Contributors

Alessandra Capolupo Department of Civil, Environmental, Land, Construction and Chemistry (DICATECh), Polytechnic University of Bari, Bari, Italy Barbara Caselli Department of Engineering and Architecture, University of Parma, Parma, Italy Myrta Castellino Department of Civil, Building and Environmental Engineering (DICEA), Sapienza University of Rome, Rome, RM, Italy Chiara Cattani Department of Civil Construction-Architectural and Environmental Engineering, University of L’Aquila, L’Aquila, Italy Marianna Ceci Department of Engineering and Architecture, University of Parma, Parma, Italy Daniele Celli Environmental and Maritime Hydraulic Laboratory (LIam), Department of Civil, Construction-Architectural and Environmental Engineering (DICEAA), University of L’Aquila, L’Aquila, Italy Chiara Chioni Department of Civil, Environmental and Mechanical Engineering, University of Trento, Via Mesiano 77, 38123 Trento, Italy Federica Cicalese Department of Civil Engineer, University of Salerno, Fisciano, SA, Italy Alfio Conti School of Architecture, Geoprocessing Laboratory, Federal University of Minas Gerais (UFMG), Rua Paraíba 697, Belo Horizonte, Brazil Simone Corrado Laboratory of Urban and Regional System Engineering (LISUT), School of Engineering, University of Basilicata, Potenza, Italy Valentina Costa Italian Excellence Centre for Logistics, Transport and Infrastructures, University of Genoa, Genoa, Italy Antonio Costanzo National Earthquake Observatory, Istituto Nazionale di Geofisica e Vulcanologia, INGV, Rome, Italy Federica Cucchiella Department of Industrial and Information Engineering and Economics, University of L’Aquila, L’Aquila, Italy Valerio Cutini University of Pisa, Pisa, PI, Tuscany, Italy Pierluigi De Berardinis Department of Civil, Construction-Architectural and Environmental Engineering, University of L’Aquila, L’Aquila, Italy Flávia Las-Cazas de Brito Geosciences Institute, Federal University of Minas Gerais Minas Gerais (UFMG), Belo Horizonte, Brazil Tancredi Marco De Francesco Municipality of Segrate (MI), Segrate, Italy Paolo De Girolamo Department of Civil, Building and Environmental Engineering (DICEA), Sapienza University of Rome, Rome, RM, Italy

List of Contributors

xxxi

Roberto De Lotto Department of Civil Engineering and Architecture – DICAr, University of Pavia, Pavia, Italy Ilaria De Noia Department of Engineering and Architecture, University of Parma, Parma, Italy Ítalo Sousa De Sena University College Dublin, Dublin, Ireland Fabiana Carmo De Vargas Vieira Federal University of Minas Gerais, Belo Horizonte, Brazil Ilaria Delponte Civil, Chemical and Environmental Engineering Department, University of Genoa, Genoa, Italy Donato Di Ludovico DICEAA - Department of Civil, Construction-Architectural and Environmental Engineering, University of L’Aquila, L’Aquila, Italy Carmine Di Nucci Environmental and Maritime Hydraulic Laboratory (LIam), Department of Civil, Construction-Architectural and Environmental Engineering (DICEAA), University of L’Aquila, L’Aquila, Italy Gianni Di Pietro University of L’Aquila – Department of Civil, ConstructionArchitectural and Environmental Engineering, Monteluco Di Roio, L’Aquila, Italy Marcello Di Risio University of L’Aquila, 67100 L’Aquila, AQ, Italy Pham Tien Dung Institute of Environment, Vietnam Maritime University, Hai Phong City, Vietnam Aitziber Egusquiza Tecnalia, Basque Research and Technology Alliance (BRTA), Parque Científico y Tecnológico de Bizkaia, Derio, Spain Nastaran Esmaeilpour Zanjani Department of Civil Engineering and Architecture – DICAr, University of Pavia, Pavia, Italy; LATTS, Ecole Des Ponts, Univ Gustave Eiffel, CNRS, Marne-La-Vallée, France Dario Esposito Department of Civil, Environmental, Land, Building Engineering and Chemistry (DICATECh), Polytechnic University of Bari, Bari, Italy Federico Eugeni DICEAA - Department of Civil, Construction-Architectural and Environmental Engineering, University of L’Aquila, L’Aquila, Italy Isidoro Fasolino Department of Civil Engineer, University of Salerno, Fisciano, SA, Italy Annamaria Felli Department of Civil Engineer, University of Salerno, Fisciano, SA, Italy Piera Fischione Department of Civil and Computer Science Engineering, University of Rome Tor Vergata, Rome, Italy Romano Fistola University of Naples Federico II, Naples, Italy Christian Freitas GE21Geotecnologias, Horizonte, Brazil

xxxii

List of Contributors

Christian Rezende Freitas GE21 Geotechnologies, Belo Horizonte, Brazil Federica Gaglione Department of Engineering, University of Sannio, Benevento, Italy Emanuele Garda Department of Engineering and Applied Sciences, University of Bergamo, Dalmine, Italy Carmela Gargiulo Department of Civil, Building and Environmental Engineering, University of Naples Federico II, Naples, Italy Rachele Vanessa Gatto Laboratory of Urban and Regional System Engineering (LISUT), School of Engineering, University of Basilicata, Potenza, Italy Luca Giannobile Department of Civil, Construction-Architectural and Environmental Engineering, University of L’Aquila, L’Aquila, Italy Sonia Giovinazzi Italian National Agency for New Technologies, Energy and Sustainable Economic Development, ENEA, Rome, Italy Ghazaleh Goodarzi Department of Urbanism, Faculty of Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran Laura Grassini Polytechnic University of Bari, Bari, Italy Nicoletta Gozo Italian National Agency for New Technologies, Energy and Sustainable Economic Development, ENEA, Rome, Italy Michele Grimaldi Department of Civil Engineer, University of Salerno, Fisciano, SA, Italy Alessia Guaiani School of Architecture and Design, University of Camerino, Ascoli Piceno, AP, Italy Raffaella Francesca Gueze Coordinamento Agende 21 Locali Italiane, Padova, Italy Müslüm Hacar Yildiz Technical University, 34210 Esenler, Istanbul, Türkiye; University of Pisa, Pisa, PI, Tuscany, Italy Nguyen Thi Hue Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Cau Giay District, Ha Noi, Vietnam; Institute of Environmental Technology, Vietnam Academy of Science and Technology, Cau Giay District, Hanoi, Vietnam Luca Iagnemma Municipality of L’Aquila, Ecological Transition and Civil Protection Office, Abruzzo Region Maritime Structures and Water Quality Office, L’Aquila, Italy Jose Luis Izkara University of Deusto, Bilbao, Bizkaia, Spain Pham Thi Kha Institute of Marine Environment and Resources, Vietnam Academy of Science and Technology, Hai Phong City, Vietnam Daniele La Rosa Department of Civil Engineering and Architecture, The University of Catania, Catania, Italy

List of Contributors

xxxiii

Claudio Ladisa Department of Civil, Environmental, Land, Construction and Chemistry (DICATECh), Polytechnic University of Bari, Bari, Italy Antonio Leone Innovation Engineering Department, University of Salento, Lecce, Italy Luiz Glück Lima Princeton University, Princeton, NJ, USA Bui Thi Thanh Loan Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Cau Giay District, Ha Noi, Vietnam; Institute of Environment, Vietnam Maritime University, Hai Phong City, Vietnam Maria Cristina Lobascio Department of Civil, Chemistry and Environmental Engineering, University of Genoa, Genoa, GE, Italy Giampiero Lombardini Department of Architecture and Design, University of Genova (I), Genoa, Italy Amaia López-de-Aguileta-Benito Tecnalia, Basque Research and Technology Alliance (BRTA), Parque Científico y Tecnológico de Bizkaia, Derio, Spain Nguyen Thi Mai Luu Institute of Marine Environment and Resources, Vietnam Academy of Science and Technology, Hai Phong City, Vietnam Danilo M. Magalhães Paulista State University (UNESP), Avenida 24 A 1515, Rio Claro, Brazil Federico Mara University of Pisa, Pisa, PI, Tuscany, Italy Chiara Marchionni Department of Civil, Construction-Architectural and Environmental Engineering, University of L’Aquila, L’Aquila, Italy Carmela Mariano Department of Planning, Design and Technology of Architecture, Sapienza University of Rome, Rome, Italy Paolo Marinucci Department of Electrotechnical and Electronics, IISS “E. Majorana”, Termoli, CB, Italy Franciele Marques University of Debrecen, Debrecen, 4032 Hungary Gustavo A. T. Martinez School of Architecture, Geoprocessing Laboratory, Federal University of Minas Gerais (UFMG), Rua Paraíba 697, Belo Horizonte, Brazil Angela Martone Università degli Studi del Sannio, Benevento, Italy Emilio Marziali University of L’Aquila – Department of Civil, ConstructionArchitectural and Environmental Engineering, Monteluco Di Roio, L’Aquila, Italy Alessia Massari Department of Civil, Building and Environmental Engineering, University of L’Aquila, L’Aquila, Italy Tiago Mello ICLEI – Local Governments for Sustainability, São Paulo, Brazil Valeria Monno Polytechnic University of Bari, Bari, Italy Cristina Montaldi Department of Civil Construction-Architectural and Environmental Engineering, University of L’Aquila, L’Aquila, Italy

xxxiv

List of Contributors

Ana Clara Mourão Moura Laboratório de Geoprocessamento, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil Beniamino Murgante Laboratory of Urban and Regional System Engineering (LISUT), School of Engineering, University of Basilicata, Potenza, Italy Guglielmina Mutani Department of Energy, R3C, Politecnico di Torino, Turin, Italy Hoang Nam Institute of Environmental Technology, Vietnam Academy of Science and Technology, Cau Giay District, Hanoi, Vietnam Dang Hoai Nhon Institute of Marine Environment and Resources, Vietnam Academy of Science and Technology, Hai Phong City, Vietnam Gennaro Pace School of Engineering, University of Basilicata, Potenza, Italy José Antonio Palenzuela Baena Survey Lab S.r.l, Spinoff of Sapienza University of Rome, Rome, RM, Italy Davide Pasquali Environmental and Maritime Hydraulic Laboratory (LIam), Department of Civil, Construction-Architectural and Environmental Engineering (DICEAA), University of L’Aquila, L’Aquila, Italy Lucia Patimisco SI – School of Engineering, University of Basilicata, Potenza, Italy Margot Pellegrino Lab’Urba - Université Gustave Eiffel, Champs-sur-Marne, France Roberta Pezzetti International Research Centre for Smart Organizations Management and Smart Land Valorization, SMARTER, Insubria University, Busto Arsizio, Italy Camilla Pezzica Welsh School of Architecture, Cardiff University, Cardiff, UK Quintilio Piattoni Office of Public Works, Maintenance, Environment and Seismic Reconstruction, Municipality of Camerino, Italy Caterina Pietra Department of Civil Engineering and Architecture – DICAr, University of Pavia, Pavia, Italy Angela Pilogallo Department of Civil, Building-Architecture and Environmental Engineering, University of L’Aquila, Via G. Gronchi 18, 67100 L’Aquila, Italy Francesca Pirlone Department of Civil, Chemistry and Environmental Engineering, University of Genoa, Genoa, GE, Italy Rosanna Piro Laboratory of Urban and Regional System Engineering (LISUT), School of Engineering, University of Basilicata, Potenza, Italy Simone Porfiri School of Architecture and Design, University of Camerino, Ascoli Piceno, Italy Pierluigi Potenza Independent Advisor on Urban Resilience, Rome, Italy Maria Racioppi Department of Planning, Design and Technology of Architecture, Sapienza University of Rome, Rome, Italy

List of Contributors

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Shiva Rahmani Laboratory of Urban and Regional System Engineering (LISUT), School of Engineering, University of Basilicata, Potenza, Italy Laura Ricci Department of Planning, Design and Technology of Architecture, Sapienza University of Rome, Rome, Italy Paolo Roccaro Department of Civil Engineering and Architecture, The University of Catania, Catania, Italy Nicole Andrade Rocha Granbery Methodist College, Rua Sampaio 300, Juiz de Fora, Brazil Ashiley Adelaide Rosa Programa de Pós-Graduação Em Geografia, Universidade Federal de Minas Gerais (UFMG), Instituto de Geociências da UFMG, Belo Horizonte, Brazil Marianna Rotilio Department of Civil, Construction-Architectural and Environmental Engineering, University of L’Aquila, L’Aquila, Italy Angela Ruggiero Lab’Urba - Université Gustave Eiffel, Champs-sur-Marne, France; Faculté d’Architecture et d’Urbanisme, UMONS, Mons, Belgium Sara Sacco DICEAA - Department of Civil, Construction-Architectural and Environmental Engineering, University of L’Aquila, L’Aquila, Italy Lucia Saganeiti Department of Civil, Construction-Architectural and Environmental Engineering – DICEAA, University of L’Aquila, L’Aquila, Italy Valentina Santarsiero Planetek Italia, Bari, Italy Luigi Santopietro Laboratory of Urban and Regional System Engineering (LISUT), School of Engineering, University of Basilicata, Potenza, Italy Francesca Scipione Department of Civil, Building and Environmental Engineering (DICEA), Sapienza University of Rome, Rome, RM, Italy Francesco Scorza Laboratory of Urban and Regional System Engineering (LISUT), School of Engineering, University of Basilicata, Potenza, Italy Rossella Scorzelli Laboratory of Urban and Regional System Engineering (LISUT), School of Engineering, University of Basilicata, Potenza, Italy Luanita Snyman-van der Walt Council for Scientific and Industrial Research, Stellenbosch, South Africa Alberico Sonnessa Department of Civil, Environmental, Land, Construction and Chemistry (DICATECh), Polytechnic University of Bari, Bari, Italy Daniele Soraggi Italian Excellence Centre for Logistics, Infrastructures and Transport, University of Genoa, 16126 Genoa, Italy Maria Rosaria Stufano Melone Polytechnic University of Bari, Bari, Italy

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Eufemia Tarantino Department of Civil, Environmental, Land, Construction and Chemistry (DICATECh), Polytechnic University of Bari, Bari, Italy Giorgia Tucci University of Genoa, dAD, Stradone Sant’Agostino 37, 16123 Genova, Italy Antonella Tundo ENEA, Smart Cities and Communities Laboratory, Smart Energy Division, Department of Energy Technologies and Renewable Sources, Bari, Italy Raffaela Valluzzi SI – School of Engineering, University of Basilicata, Potenza, Italy Vu Van Tu Institute of Science and Technology for Energy and Environment, Vietnam Academy of Science and Technology, Cau Giay District, Hanoi, Vietnam Elisabetta Venco Department of Civil Engineering and Architecture – DICAr, University of Pavia, Pavia, Italy Maria Luisa Villani Italian National Agency for New Technologies, Energy and Sustainable Economic Development, ENEA, Rome, Italy Asel Villanueva-Merino Tecnalia, Basque Research and Technology Alliance (BRTA), Parque Científico y Tecnológico de Bizkaia, Derio, Spain Michele Vomero DAFNE Department, University of Tuscia, Viterbo, Italy Giulia Motta Zanin Polytechnic University of Bari, Bari, Italy Michele Zazzi Department of Engineering and Architecture, University of Parma, Parma, Italy Ida Zingariello University of Sannio, Benevento, Italy Floriana Zucaro Department of Civil, Building and Environmental Engineering, University of Naples Federico II, Naples, Italy Francesco Zullo Department of Civil Construction-Architectural and Environmental Engineering, University of L’Aquila, L’Aquila, AQ, Italy Camila Marques Zyngier Instituto de Educação Continuada, Pontifícia Universidade Católica de Minas Gerais, Belo Horizonte, Brazil

Geospatial Earth Data to Support the Restoration of Soil Ecosystems and Implications for Spatial Planning (GEO4SP)

A Customized JAVA OpenStreetMap Preset to Extract Solar Panel Installations for Humanitarian Purposes Claudio Ladisa(B)

, Alessandra Capolupo , and Eufemia Tarantino

Department of Civil, Environmental, Land, Construction and Chemistry (DICATECh), Polytechnic University of Bari, Via Orabona N. 4, 70125 Bari, Italy [email protected]

Abstract. The use of clean and renewable energies, such as solar power, is essential for improving local economies, reducing reliance on scarce fossil fuels, and mitigating climate change. However, although solar power harvested using PhotoVoltaic (PV) cells has grown significantly in recent years, the actual amount of energy produced is unknown and challenging to define because of the lack of geographic data on the number of PV panels installed on rooftops. Due to the low spatial resolution of open-source satellite images, free surveying PV small-scale installations is currently not feasible. YouthMappers, an academic network dedicated to the creation and use of open mapping for development and humanitarian purposes, offers a possible solution. Indeed, it is an effective method to gather free detailed information on a large scale thanks to the support of high-resolution satellite images such as MapBox, Bing, or DigitalBox in an open-source environment, like Java OpenStreetMap (JOSM). As a result, in this study, an ad hoc tool written in JOSM was created to map PV panels on rooftops manually. This preset collects all of the information needed to describe PV panel features, such as type, size, and orientation, and calculate the amount of energy produced. Furthermore, its interface is simple and easy to use for both Information Technology (IT) and non-IT users. All data collected is stored in a geodatabase accessible to local governments, communities, industries, and scientists, allowing for a global overview of installed PV panel systems, the potential amount of energy produced, and the tracking of their evolution over time. Keywords: Renewable Energy · Solar Energy · Collaborative Mapping · YouthMappers · JOSM · Sustainability

1 Introduction The reduction of greenhouse gas emissions associated with fossil fuel exploitation is crucial for both boosting local economies and combating global warming [1]. As a result, the use of clean and renewable energy sources, such as solar power generated by PV panels, has increased significantly in recent years [2]. According to current estimates, PV systems generate between 500 and 600 GW of electricity per year, albeit its spawning is © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 3–11, 2024. https://doi.org/10.1007/978-3-031-54118-6_1

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not uniform over the world: Italy, for example, makes a major contribution by producing around 1,500 to 2,000 kWh per kWp [3]. This is mainly due to that energy production depends on various factors such as location, season, cloud cover, and the type of solar panels used [4]. Moreover, quantifying the real amount of energy generated is challenging due to a lack of geographic data on the number of PV panels installed [5]. This issue may be partially settled by developing automated PV installations detection algorithms based on satellite data, since such approaches allow for the extraction of panel classes over wide areas in a short period of time [6–9]. However, a global scale analysis might be performed just using free open-source satellite images to save collecting time and cost. Nevertheless, those data cover the whole Earth’s surface, albeit at a resolution insufficient to detect small PV installations [10–12]. Collaborative mapping, which is based on a team effort to use digital technologies to generate accurate and detailed maps [13], provides a viable solution that can be used in a variety of contexts, including urban planning, emergency management, environmental protection, and tourism promotion [14–16]. Among the many different organizations, Youthmapper, an international network committed to enhancing OpenStreetMap (OSM) information to address social and environmental challenges, deserves special note [17]. OSM, in fact, accepts several satellite image sources, including Bing Maps, DigitalGlobe, MapBoxer, and Maxar [18], which may be changed or updated using online tools like Java OpenStreetMap (JOSM) [19]. JOSM is one of the most popular since it has an assortment of complex features that make it suited for both expert and beginner users [20]. For instance, it allows for the development of complicated roads and buildings and the modification of several elements simultaneously [21]. Additionally, JOSM enables users to create customized presets that comprise all of the elements required for mapping a given theme. In previous works, for example, a setup for mapping deforestation in the Amazon was created, and factors such as grasslands, roads, and cultivated areas were incorporated so that a deforestation risk model could be established later [13]. The primary goal of this research was to create a new JOSM preset for mapping small PV panel installations on various types of structures. This tool was designed to facilitate detailed information collection and dissemination concerning PV panels’ location and energy production capacities.

2 JOSM JOSM is a Java 8-based editor for creating, editing, visualizing, uploading, and downloading OSM maps [22]. Because it is an offline editor, any changes made are only visible until they are submitted to the server [23]. This enables users to experiment with and practice altering operations like adding, removing, or labeling items without changing the real map data [19, 24]. In the editing process, the first step involves nodes or ways in addition to the OSM data. Such elements, however, are useless unless they are labeled to indicate what they represent. Tags, which are made up of key-value pairs, give information on the meaning of each node, path, and connection [24]. Keys, such as “Highway” or “Land Use”, identify the larger category, while values indicate individual aspects, such as “Main Road” or “Residential Road,” or land uses such as “Residential” or “Retail” [23]. Tags can be inserted manually or automatically using presets.

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2.1 JOSM Presets Presets in JOSM are default options that allow users to create primitive geometries and easily label them with common OSM tags [25]. They provide a user-friendly interface for modifying multiple items at once, as well as suggestions for new keys and values that may be added to these objects [24]. In this way, users can avoid manually entering keys and values, saving time and effort [22]. JOSM offers three types of presets: i) pre-installed default presets, ii) presets created by the OSM community that can be enabled via the Tagging Presets register in Preferences, and iii) custom presets created by users themselves using Extensible Markup Language (XML) code by OSM guidelines [25].

3 Methodology In this study, an XML code was developed by following the hierarchical sequence illustrated in Fig. 1 to construct a preset suited for mapping PV panels on rooftops. The initial segment of the code involves the component, which plays a crucial role in establishing a connection with OSM and utilizing its tags in the preset. Following that, the component was incorporated within the element. This section featured the “Solar Set” preset designation and a variety of were embedded inside it. More specifically, the group contained four designations, namely “Urban Buildings”, “Farm Buildings”, “Industrial Buildings”, and “Country House”. The aforementioned groups were carefully chosen to cover all possible buildings that may support solar panel installation.

Fig. 1. Solar Set hierarchical scheme

Each object has its own “Name”, “type”, “icon”, “key”, and “value”. The parameter “type” specifies the geometric element category to which the preset can be applied. The categories “closedway” and “relation” were chosen for all four items in this scenario,

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implying that the object can represent either a closed area, such as a solar panel, or a collection of geographic objects, such as nodes, segments, and polygons, that together express portions of a single concept. [26]. The “icon” function is used to insert Scalable Vector Graphics (SVG) images for each items’ visual appearance. The “key” in the preset introduces a predefined tag for OSM elements. In OSM, the term “key” refers to the initial component of a tag that identifies the category or type of the described feature. On the other hand, the “value” represents the specific attribute or characteristic associated with that feature. It is crucial to maintain a consistent set of keys and values in OSM as it enables consistent structuring and querying of data [26]. In this case, the key “generator:source”, which is the OSM tag designated for energy generation, was chosen. The value solar denotes that energy generation is renewable, specifically solar [26]. This tag makes it easier for users to build new items on the map by automatically adding the “generator:source” tag with the matching value of solar to the newly formed element. Furthermore, each preconfigured element contains a variety of text labels and input boxes that mappers may fill out with the necessary data. The data has been divided into three categories: i) general information, ii) panels information, and iii) building information. 3.1 General Information Category Users may submit information about panel location, province, and municipality in the code’s general information section (Fig. 2). The “delete_if_empty” command removes an element or attribute only if it is empty. This command is frequently used during XML data manipulation to eliminate empty elements or attributes and improve the XML document structure.

Fig. 2. General Information section

3.2 Panels Information Section This part of the code was designed to allow users to provide technical information regarding PV panels. Figure 3 shows two text boxes where the user may enter the installed power of the panel in kW and the year of installation. The form was then enhanced with two combo boxes, the first of which allowed the user to select panel orientation from three options: “North-South Axis,” “East-West Axis,” and “Other,” and the second of which allows the user to select panel material, with monocrystalline and polycrystalline panels available.

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Fig. 3. Panels Information section

3.3 Building Information Item In this final section of the code, text and combo elements were incorporated to input information on the buildings where the PV panels are installed (Fig. 4). Aside from a text area for entering the number of floors, three distinct combination components were offered: the first enables users to define if a raised floor is present, the second one indicates if panels are installed on slope or slab, and, lastly, the third one allows inserting the information concerning building’s ownership.

Fig. 4. Building Information section

3.4 Code entry within JOSM When the code was finished, it was added to the “Preset Labels”, portion of the Presets menu, and to “Preset Preferences” section.

4 Results and Discussion Once the “Solar Set” preset has been successfully installed in JOSM, the user can commence the mapping process. After downloading the OSM data for the desired area, the user can choose suitable aerial photography sources for mapping solar panels, such as

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Bing or Maxar Premium Imagery. Subsequently, the drawing tools within the software can be utilized to create a geometric representation of the solar panel, as depicted in Fig. 5. The user can then apply the “Solar Set” preset to tag the geometry and specify the type of building where the solar panel is installed by selecting the appropriate option from the pre-setting menu in JOSM.

Fig. 5. Geometry creation in JOSM

By selecting the proper building type, a form will appear (as shown in Fig. 6) where the user can provide accurate information about the building and solar panel to be added to OpenStreetMap. It is crucial to ensure the accuracy and reliability of the data submitted during this step of the mapping process. If customer information is missing or unknown, it is advisable to leave the corresponding field blank rather than submitting inaccurate data. To gather additional information, such as the public or private status of the solar panels and their angle, the Mapillary plug-in in JOSM can be utilized. Mapillary is a Web 2.0 service that allows users to contribute street-level images from various locations worldwide.

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Fig. 6. Preset form in JOSM

5 Conclusions Even though the usage of solar energy has grown significantly in recent years, accurately measuring the amount of energy generated by PV systems is challenging since it is affected by several factors such as location, season, and cloud cover. Although free open-source satellite data has contributed to the improvement of automated sensing techniques for mapping PV systems, surveying small-scale installations remains tough due to their limited spatial resolution. Creating a customized preset for mapping rooftop solar panel installations in JOSM has shown to be a great technique to improve the mapping process’s efficiency and accuracy. This allows users to utilize high-resolution images and enter other sorts of panel information, which is a departure from past work. The data collected through this method can be stored in a geodatabase accessible to local governments, communities, industries, and scientists. This allows for the compilation of a worldwide overview of PV panel installations as well as the tracking of their progress over time, resulting in a better knowledge of the potential of renewable energy sources in different areas and the promotion of future sustainable energy practices. The preset might be improved in the future by integrating new building types or machine learning techniques to automate some elements of the mapping process. In

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conclusion, the development of a tailored preset for mapping rooftop solar panel installations contributes significantly to the promotion of renewable energy sources and the reduction of the environmental effect of human activities. It may be improved further by developing unique solutions.

References 1. Kabir, E., Kumar, P., Kumar, S., Adelodun, A., Kim, K.: Solar energy: potential and future prospects. Renew. Sustain. Energy Rev. 82, 894–900 (2018) 2. Rabaia, M., Abdelkareem, M., Sayed, E., Elsaid, K., Chae, K.-J., Wilberforce, T., Olabi, A.G.: Environmental impacts of solar energy systems: a review. Sci. Total Env. 754, 141989 (2021) 3. Monforti, F., Huld, T., Bódis, K., Vitali, L., D’Isidoro, M., Lacal-Arántegui, R.: Assessing complementarity of wind and solar resources for energy production in Italy. A Monte Carlo approach. Renew. Energy 63, 576–586 (2014) 4. Gašparovi´c, I., Gašparovi´c, M.: Determining optimal solar power plant locations based on remote sensing and GIS methods: a case study from Croatia. Remote Sens. 11(12), 1481 (2019) 5. Pindozzi, S., Faugno, S., Cervelli, E., Capolupo, A., Sannino, M., Boccia, L.: Consequence of land use changes into energy crops in Campania region. J. Agric. Eng. 44(2s) (2013) 6. Peters, I., Liu, H., Reindl, T., Buonassisi, T.: Global prediction of photovoltaic field performance differences using open-source satellite data. Joule 2(2), 307–322 (2017) 7. Tarantino, E., Figorito, B.: Steerable filtering in interactive tracing of archaeological linear features using digital true colour aerial images. Int. J. Digital Earth 7(11), 870–880 (2014) 8. Ladisa C, Capolupo A, Ripa M, Tarantino E (2022) Combining OBIA approach and Machine Learning algorithm to extract photovoltaic panels from Sentinel 2 images automatically. Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIV (Vol. 12262, pp. 67–76). SPIE 9. Ladisa, C., Capolupo, A., Ripa, M., Tarantino, E.: Evaluation of ecognition developer and orfeo toolbox performances for segmenting agrophotovoltaic systems from sentinel-2 images. In: Gervasi, O., Murgante, B., Misra, S., Rocha, A.M.A.C., Garau, C. (eds.) Computational Science and Its Applications – ICCSA 2022 Workshops: Malaga, Spain, July 4–7, 2022, Proceedings, Part III, pp. 466–482. Springer International Publishing, Cham (2022). https:// doi.org/10.1007/978-3-031-10545-6_32 10. Viana, C., Girão, I., Rocha, J.: Long-Term Satellite Image Time-Series for Land Use/Land Cover Change Detection Using Refined Open Source Data in a Rural Region. Remote Sens. 11(9), 1104 (2019) 11. Stowell, D., Kelly, J., Tanner, D., et al.: A harmonised, high-coverage, open dataset of solar photovoltaic installations in the UK. Sci. Data 7, 394 (2020) 12. Figorito, B., Tarantino, E.: Semi-automatic detection of linear archaeological traces fromorthorectified aerial images. Int. J. Appl. Earth Obs. Geoinf. 26(1), 458–463 (2014) 13. Gaspari, F.: Innovation in teaching: the Polimappers collaborative and humanitarian mapping course at Politecnico di Milano. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences – ISPRS Archives, International Society for Photogrammetry and Remote Sensing (2021) 14. Hite, R., Solís, P., Wargo, L., Larsen, T.: Exploring affective dimensions of authentic geographic education using a qualitative document analysis of students’ youthmappers blogs. Educ. Sci. 8(4), 173 (2018) 15. Solís, P., Zeballos, M. (eds.): Open Mapping towards Sustainable Development Goals: Voices of YouthMappers on Community Engaged Scholarship. Springer International Publishing, Cham (2023)

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16. García-Nieto, A., Quintas-Soriano, C., García-Llorente, M., Palomo, I., Montes, C., MartínLópez, B.: Collaborative mapping of ecosystem services: the role of stakeholders’ profiles. Ecosyst. Serv. 13, 141–152 (2015) 17. Solís, P., Anderson, J., Rajagopalan, S.: Open geospatial tools for humanitarian data creation, analysis, and learning through the global lens of YouthMappers. J. Geogr. Syst. 23(4), 599–625 (2021) 18. Schott, M., Grinberger, A., Lautenbach, S., Zipf, A.: The impact of community happenings in openstreetmap—establishing a framework for online community member activity analyses. ISPRS Int. J. Geo-Inform. 10(3), 164 (2021) 19. Vargas-Munoz, J., Srivastava, S., Tuia, D., Falcao, A.: OpenStreetMap: challenges and opportunities in machine learning and remote sensing. IEEE Geosci. Remote Sens. Mag. 9(1), 184–199 (2021) 20. Ahamed, A., Vakilzadian, H.: Impact of direction parameter in performance of modified AODV in VANET. J. Sens. Actuator Netw. 9(3), 40 (2020) 21. Scioscia, F., Binetti, M., Ruta, M., Ieva, S., Di Sciascio, E.: A framework and a tool for semantic annotation of POIs in OpenStreetMap. Procedia Soc. Behav. Sci. 111, 1092–1101 (2014) 22. Ramm, F., Topf, J.: OpenStreetMap: Die freie Weltkarte nutzen und mitgestalten. Lehmanns Media (2010) 23. Wang, Z., Niu, L.: A data model for using openstreetmap to integrate indoor and outdoor route planning. Sensors (Switzerland) 18(7) (2018) 24. Girres, J., Touya, G.: Quality assessment of the french OpenStreetMap dataset. Trans. GIS 14(4), 435–459 (2010). https://doi.org/10.1111/j.1467-9671.2010.01203.x 25. LearnOSM Homepage https://learnosm.org/en/josm/start-josm/. Last accessed 18 May 2023 26. WikiOpenStreetMap Homepage. https://wiki.openstreetmap.org/wiki/IT:Pagina%20Princip ale?uselang=it. Last accessed 18 May 2023

Copernicus Geodatabase for Investigating Land Cover Changes at the European Scale Carlo Barletta , Alessandra Capolupo(B)

, and Eufemia Tarantino

Department of Civil, Environmental, Land, Building Engineering and Chemistry (DICATECh), Polytechnic University of Bari, Via Orabona 4, 70125 Bari, Italy [email protected]

Abstract. Copernicus, the European initiative for monitoring the Earth, provides an extensive range of data types that allow consumers, public authorities, and scientists to get free, open, and comprehensive knowledge of the world. Therefore, it is recognized as one of the largest geodatabases storing a great deal of data provided by satellites and in-situ sensors, which are then processed to generate reliable and up-to-date information on a large number of pressing environmental and security concerns. As a result, it could be a valid option for examining the state of landscape and its evolution over time. More knowledge about land changes might assist in developing an effective strategy to tackle the soil sealing phenomena, which is largely caused by climate change and anthropogenic pressure and is being experienced by all European countries. Thus, this study examines how Copernicus earth observation data and geographical services might help with changes in terrain cover at the European level. The land cover change maps were evaluated after looking at all the data, when it was possible to perform this task, while in other cases, Google Earth Engine, a cloud platform designed by Google to manage large geographic data, was used to produce the maps. The benefits and drawbacks of the Copernicus platform have been examined. It proves to be a functional platform for achieving research goals, but it is insufficient for a global study because of the absence of data in many European cities and the low resolution of many of them. Keywords: Earth Observation data · Cloud Platform · Copernicus Program · Geographical services

1 Introduction Copernicus is recognized as one of the most important and ambitious Earth Observation (EO) programs collecting large amounts of remotely sensed and in-situ data to provide valuable information on the Earth system. The initiative, led by the European Union (EU) in partnership with other agencies and institutions including the European Space Agency (ESA) and the European Environment Agency (EEA), provides freely and openly available products to its users, helping researchers and institutions to address many global environmental and territorial issues. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 12–23, 2024. https://doi.org/10.1007/978-3-031-54118-6_2

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Copernicus Earth monitoring is made possible through a set of dedicated satellites (called “Sentinels”) and other contributing satellite missions, as well as in-situ observations from ground-based, airborne and seaborne measuring equipment. The collected data are transformed into value-added information by six thematic services [1–5]. The “soil sealing” phenomenon, which converts land into impermeable surfaces as a result of urban expansion and is also considered a kind of land degradation, is now a serious environmental concern impacting many European nations. Indeed, sealed soils have diminished ecological functions and can negatively impact on climate and water cycle. Europe is one of the most intensively used territories in the world, with up to 80% of its land used for production systems (including agriculture and forestry), settlements and infrastructure. Detecting changes in land use/land cover (LU/LC) at various scales of study using appropriate approaches is thus critical in order to understand the evolution of the soil sealing process over time and establish effective planning measures to address it. However, to properly investigate LU/LC changes over a specific site, accurate geodatabases covering different time periods are required [6–17]. The objective of this study is to examine how Copernicus EO data and services are helpful for evaluating LU/LC changes at the European scale, which is necessary for sustainable land use management. For this purpose, after reviewing all accessible datasets, different Copernicus satellite data and the Copernicus Land Monitoring Service (CLMS) [12] which is dedicated to terrain analysis and monitoring, were studied. Where Copernicus-derived LU/LC data could not be collected, the potentialities of the Google Earth Engine (GEE) cloud platform [18–20] for LU/LC change investigation at the European level were explored.

2 Materials and Methods 2.1 Copernicus Satellite Data for LU/LC Change Monitoring The EU Copernicus program provides a huge amount of free and open data collected by a constellation of satellites, known as “Sentinels”, that can be used for detecting and monitoring the LU/LC over time. The Sentinel-1 Synthetic Aperture Radar (SAR) mission, in particular, provides the best data for this purpose (with a geometric resolution of 10 m and a temporal resolution of 6 days), from which it is possible to detect and monitor, among other things, forest types, biomass, forest fire scars, crop conditions, soil properties and seasonal changes in land use. On the other hand, optical multispectral data from the Sentinel-2 satellite (with a geometric resolution up to 10 m) enable mapping of LU/LC and its changes with a high revisit frequency (5 days), which is crucial in many fields of study including, for instance, spatial planning, natural resource management and monitoring, and agro-environmental monitoring. Other data sources for LU/LC change study include the Sentinel-3 mission, which provides worldwide maps of key bio-geophysical variables (e.g., Leaf Area Index) can be retrieved at 300 m resolution every 2–3 days. Copernicus users may access Sentinel data via the new Copernicus Data Space Ecosystem (https://dataspace.copernicus.eu/), which is growing from the Copernicus Open Access Hub and the five Data and Information Access Services (DIAS). This

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service, launched in January 2023, will allow Copernicus users to easily and freely search, visualize and download data for a certain day or time period. Furthermore, the service provides its customers with the ability to access and handle data in the cloud via a variety of APIs and advanced data processing tools [21–24]. 2.2 Copernicus Land Monitoring Service The CLMS (https://land.copernicus.eu/) is the Copernicus service dedicated to providing geographical information on LU/LC and its changes. Based on diverse EO data, the EEA and the Joint Research Centre (JRC) execute this service, which contributes to the construction and continual updating of the products. Since there is no restriction on the use of CLMS data and information, all citizens, researchers, organizations and public authorities have free and open access to the products. The CLMS consists of three main components: i) the global component; ii) the pan-European component; and iii) the local component [12, 25]. The global component of the CLMS is managed by the JRC and provides a series of bio-geophysical products concerning the status and dynamics of the land surface at mid-to-low resolution (from 100 m to 1 km), useful for the systematic monitoring of the vegetation, water resources, energy budgets and cryosphere at global scale. The products are provided in near real time through a user-friendly portal (https://land.cop ernicus.eu/global/), and are complemented with historical time series, with a focus on change detection [26, 27]. On the other hand, the CLMS pan-European component is managed by the EEA and delivers information products on LU/LC and its changes, through the CORINE Land Cover dataset (where “CORINE” stands for “COoRdination of INformation on the Environment” [33]), as well as high resolution layers on specific land cover characteristics (imperviousness, forests, grasslands, water and wetness, and small woody features) and bio-geophysical parameters (vegetation phenology and productivity, and snow and ice) at European scale (https://land.copernicus.eu/pan-european) [25]. The CLMS local component (https://land.copernicus.eu/local), instead, managed by the EEA, provides detailed information (based on very high-resolution imagery and other useful datasets) on specific areas of environmental concern in Europe (namely “hotspots”), complementary to those provided by the pan-European component. The hotspots on which focuses the CLMS local component are: i) the major European urban areas; ii) the riparian zones; iii) the sites of the EU “Natura 2000” network; and iv) the coastal zones [25]. 2.3 Google Earth Engine Platform GEE is a cloud-based platform released by Google, that is well suited for many environmental and territorial applications. It consists of a multi-petabyte, freely accessible data catalog of various EO datasets, coupled with a high-performance computing service. The data can be processed using the GEE Code Editor, an Interactive Development Environment (IDE) associated with the JavaScript Application Programming Interface (API) or, alternatively, using the Google Colab environment, specific for the Python API.

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GEE users can therefore perform operations by developing specific and customizable codes in order to meet their needs [19, 28, 29]. One way of extracting LU/LC change information in the GEE environment is by processing multi-temporal optical remote sensing images. To perform a LU/LC classification, different techniques exist in literature [11, 17, 29–31]. A consolidated method, for example, consists in computing appropriate indices that integrate different spectral bands (“index-based approach”), as reported in [29], where the Normalized Difference Bareness Index (NDBaI1) and the SwirTirRed (STRed) indices were applied to extract bare soil, built-up, sparse vegetation, dense vegetation and water LU/LC categories from Landsat satellite data related to the Berlin urban area. Alternatively, another way to investigate terrain changes over time is to compare various multi-temporal LU/LC maps already available in the GEE data catalog.

3 Results and Discussion The aim of this study is to investigate how the free Copernicus data and services and the GEE platform could contribute to the detection of the LU/LC and its changes at the European scale. For this purpose, several available data and products were examined and compared. Because of the very good geometric, temporal, spectral, and radiometric resolutions of the sensors on board these satellite platforms, the SAR and multispectral satellite images acquired by the Sentinel-1 and Sentinel-2 missions, respectively, are a valuable source of information on LU/LC and change detection. In fact, this enables the generation of accurate multi-temporal and medium-resolution LU/LC maps after selecting from among the many LU/LC classification algorithms available in the literature. [17, 29– 31]. Furthermore, the Sentinel-3 data can add other useful information (e.g., on the state of vegetation) at a coarser geometric resolution (300 m) [23]. The main Sentinels features data analyzed in this study are summarized in Table 1. Table 1. Sentinels data main features adapt for LU/LC monitoring. SAR: Synthetic Aperture Radar; OLCI: Ocean and Land Color Instrument; SLSTR: Sea and Land Surface Temperature Radiometer. * Dismissed [32]; ** Until 2021/12/23 [32]. Mission

Satellites

Sensor type

Geometric resolution

Temporal resolution

First launch

Sentinel-1

Sentinel-1A, Sentinel-1B*

SAR

10 m

6 days**

2014

Sentinel-2

Sentinel-2A, Sentinel-2B

Optical

Up to 10 m (depending on the band)

5 days

2015

Sentinel-3

Sentinel-3A, Sentinel-3B

Optical (OLCI), Optical/Thermal (SLSTR)

300 m (OLCI), 500 m–1 km (SLSTR)

2–3 days

2016

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As previously reported, the CLMS is the Copernicus service dedicated to terrain analysis and monitoring. This service provides free and open products at global, panEuropean and local scales. At the global level, the CLMS produced the Global Land Cover maps at 100 m resolution for the years from 2015 to 2019 (https://land.copernicus.eu/global/produc ts/lc). These layers are present in a raster format in the GEE data catalog, as discussed later. At the pan-European level, instead, the CORINE Land Cover product constitutes a unique series to monitor changes in landscapes since 1990 (Tables 2 and 3). This effort, which was established to survey and monitor LU/LC features with an emphasis on the status of the environment and natural resources, is the only source in Europe that provides a full, uniform, and standardized picture at the national level. The dataset consists of an inventory of 44 LU/LC classes provided for the years 1990, 2000, 2006, 2012 and 2018, as well as LU/LC change layers (1990–2000, 2000–2006, 2006–2012 and 2012–2018). The nomenclature of the LU/LC classes is hierarchical and can be grouped into five main categories: i) artificial surfaces; ii) agriculture; iii) forests and seminatural areas; iv) wetlands; and v) water [25, 34]. Data are delivered in both vector and raster formats. The CLMS products adapted for LU/LC change analysis at the local scale are four: Urban Atlas, Riparian Zones, Natura 2000 and Coastal Zones. Urban Atlas focuses on the mapping and LU/LC change analysis of the main European Functional Urban Areas (FUAs) and their surroundings (Tables 2 and 3). The FUAs are extracted from very high-resolution and other available imagery, combined with insitu data. Urban Atlas is considered a valid tool for monitoring spatial patterns and policies in urban areas across Europe, thus facilitating evidence-based policy-making. The dataset currently covers the years 2006 (319 FUAs in 27 countries), 2012 (785 FUAs in 39 countries) and 2018 (788 FUAs in 39 countries). The nomenclature includes 17 urban LU/LC classes with a Minimum Mapping Unit (MMU) of 0.25 ha and 10 rural LU/LC classes (MMU of 1 ha), for both the 2012 and 2018 products. Conversely, the 2006 product has 17 urban classes (MMU 0.25 ha) and only 2 rural classes (MMU 1 ha). The database also includes Urban Atlas change layers (2006–2012 with 302 FUAs, and 2012–2018 with 785 FUAs), having a MMU of 0.1 ha and 0.25 ha for urban and rural classes, respectively. The Urban Atlas classification is derived from CORINE Land Cover and consists of five thematic groups: i) artificial surfaces; ii) agricultural areas; iii) natural and seminatural areas; iv) wetlands; and v) water. The data are delivered in a vector format [25, 35–38]. Riparian Zones (RZ) “Land cover/Land use”, instead, addresses LU/LC and its changes in river areas across Europe (Tables 2 and 3). This dataset, useful for supporting biodiversity mapping and monitoring along river ecosystems, covers an area of about 805000 km2 in a variable buffer zone of selected rivers (levels 2–9 of Strahler classification derived from “EU-Hydro” database) for the years 2012 and 2018. A LU/LC change layers (“RZ Land Cover/Land Use change 2012–2018”) is also included. The LU/LC classes are extracted from very high-resolution satellite images and other available data with a MMU of 0.5 ha and a MMW of 10 m. The classification, aligned with the Mapping and Assessment of Ecosystems and their Services (MAES) ecosystem types and the CORINE Land Cover nomenclature, provides 55 classes grouped into eight main

Copernicus Geodatabase for Investigating Land Cover Changes

17

categories: i) urban; ii) cropland; iii) woodland and forest; iv) grassland; v) heathland and scrub; vi) open spaces with little or no vegetation; vii) wetland; and viii) water. The data are delivered in a vector format [39–41]. Natura 2000 is another local CLMS product that provides LU/LC mapping of grassland-rich sites in the EU “Natura 2000” network (Tables 2 and 3). The objective of this product is to evaluate whether these locations are adequately protected. In fact, the information on LU/LC variations in these locations is helpful for biodiversity monitoring and assessment. For the years 2006, 2012, and 2018, this service covered an area of roughly 631000 km2 across Europe, with a 2 km buffer zone surrounding each location. In addition, two LU/LC change products are available for the periods 2006– 2012 and 2012–2018. The LU/LC classes are recognized and retrieved from extremely high-resolution, detailed data (MMU of 0.5 ha). The classification, which follows a nomenclature based on the MAES ecosystem typologies and is harmonized with the CORINE Land Cover, provides 55 thematic categories divided into eight main groups: i) urban; ii) cropland; iii) woodland and forest; iv) grassland; v) heathland and scrub; vi) open spaces with little or no vegetation; vii) wetland; and viii) water. The data are delivered in vector format [42–45]. Coastal Zones is a Copernicus local service adapt to monitor coastal landscape trends and dynamics (Tables 2 and 3). This product covers all European coastal areas (approximately 730000 km2 ). The database consists in two status layers (for reference years 2012 and 2018) and a LU/LC change layer (period 2012–2018) characterized by a high spatial resolution (MMU of 0.5 ha). The maps cover a buffer zone of coastline (landward distance of 10 km) derived from “EU-Hydro” dataset. The LU/LC classification provides 71 thematic classes based on MAES ecosystem types and CORINE Land Cover categories, distinct into eight main classes: i) urban; ii) cropland; iii) woodland and forest; iv) grassland; v) heathland and scrub; vi) open spaces with little or no vegetation; vii) wetland; and viii) water. The data are delivered in a vector format [46–48]. The main features of the CLMS products analyzed in this study are summarized in Tables 2 and 3. As previously reported, the potentialities of the GEE platform to provide multitemporal LU/LC datasets covering the European territory were explored. As mentioned below, the GEE public data catalog presently provides certain raster datasets adapted for LU/LC alterations analysis at the European scale. In addition to the CORINE Land Cover maps (with a spatial resolution of 100 m), the GEE catalog contains the Copernicus Global Land Cover layers (CGLS-LC100 Collection 3) with a spatial resolution of 100 m for the years 2015 to 2019. These maps include 23 LU/LC classes. The collection also includes the ESA WorldCover at 10 m resolution for 2020 and 2021, as well as the Dynamic World V1 (10 m resolution) from 2015 to the present. The classification (11 LU/LC categories) in the former is based on Sentinel-1 and Sentinel-2 satellite pictures. The latter, on the other hand, provides Sentinel-2-generated LU/LC class predictions (9 classes) [49]. The main features of the Copernicus data-derived GEE datasets for LU/LC mapping and monitoring are summarized in Table 4. The research and comparison of the CLMS’s numerous products reveals that, with the exception of the Global Land Cover dataset, the CORINE Land Cover is the only

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Table 2. Main features of the CLMS products for LU/LC mapping. CGLS: Copernicus Global Land Service; LC: Land Cover; PROBA-V: Project for On-Board Autonomy – Vegetation; CLC: Corine Land Cover; UA: Urban Atlas; RZ: Riparian Zones; N2K: Natura 2000; CZ: Coastal Zones; MMU: Minimum Mapping Unit; MMW: Minimum Mapping Width; SPOT: Satellite Pour l’Observation de la Terre; IRS: Indian Remote Sensing; LISS: Linear Imaging Self-scanning Sensor; KOMPSAT: Korean Multi-Purpose Satellite; VHR: Very High Resolution. Product

Scale

Temporal coverage

MMU/MMW or Satellite data geometric resolution

Number of countries

CGLS LC-100

global

2015–2019

100 m

PROBA-V

worldwide

CLC

pan-European

1990, 2000, 2006, 2012, 2018

25 ha/100 m

Landsat 5/7/8, Sentinel-2, SPOT – 4/5, IRS LISS III, RapidEye and others

27 (1990), 39 (2000, 2006, 2012, 2018)

UA

local

2006, 2012, 2018

0.25–1 ha/10 m

SPOT-5/6, Formosat-2, Pléiades, KOMPSAT and others

27 (2006), 39 (2012, 2018)

RZ

local

2012, 2018

0.5 ha/10 m

SPOT-5/6/7, Pléiades, KOMPSAT and others

39

N2K

local

2006, 2012, 2018

0.5 ha/10 m

Mix of VHR datasets

29

CZ

local

2012, 2018

0.5 ha/10 m

SPOT-5/6/7, Pléiades, KOMPSAT and others

29

product that provides national LU/LC coverage of European nations. This last dataset is also the oldest (the earliest data are from 1990) and enables for LU/LC change analyses at a coarse resolution (25 ha MMU for status maps and 5 ha for change layers, with an MMW of 100 m). Local scale CLMS products (e.g., Urban Atlas, Riparian Zones, Natura 2000, and Coastal Zones) give a higher degree of information. However, these statistics are limited to specific portions of European territory (known as “hotspots”). For the period 2006–2018, Urban Atlas, which covers the major European city areas, provides the best level of detail among the various CLMS datasets examined in this work (from 0.25 to 1 ha MMU for status maps and from 0.1 to 0.25 MMU for change layers, depending on the LU/LC class, with an MMW of 10 m). The other three local CLMS products (Riparian Zones, Natura 2000, and Coastal Zones) have a resolution of 0.5 ha

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19

Table 3. Main features of the CLMS products for LU/LC change mapping. CLC: Corine Land Cover; UA: Urban Atlas; RZ: Riparian Zones; N2K: Natura 2000; CZ: Coastal Zones; MMU: Minimum Mapping Unit; MMW: Minimum Mapping Width; SPOT: Satellite Pour l’Observation de la Terre; IRS: Indian Remote Sensing; LISS: Linear Imaging Self-scanning Sensor; KOMPSAT: Korean Multi-Purpose Satellite; VHR: Very High Resolution. Product

Scale

Temporal coverage

MMU/MMW

Satellite data

Number of countries

CLC change

pan-European

1990–2000, 2000–2006, 2006–2012, 2012–2018

5 ha/100 m

Landsat 5/7/8, Sentinel-2, SPOT-4/5, IRS LISS III, RapidEye and others

29 (1990–2000), 39 (2000–2006, 2006–2012, 2012–2018)

UA change

local

2006–2012, 2012–2018

0.1–0.25 ha/10 m

SPOT-5/6, Formosat-2, Pléiades, KOMPSAT and others

27 (2006–2012), 39 (2012–2018)

RZ change

local

2012–2018

0.5 ha/10 m

SPOT-5/6/7, Pléiades, KOMPSAT and others

39

N2K change

local

2006–2012, 2012–2018

0.5 ha/10 m

Mix of VHR datasets

29

CZ change

local

2012–2018

0.5 ha/10 m

SPOT-5/6/7, Pléiades, KOMPSAT and others

29

Table 4. Main features of the Copernicus data-derived GEE datasets for LU/LC mapping and monitoring. LU/LC: Land Use/Land Cover: CLC: CORINE Land Cover; CGLS: Copernicus Global Land Service; LC: Land Cover; ESA: European Space Agency; V1: Version 1. Product

Temporal coverage

Geometric resolution

Number of LU/LC classes

CLC

1990, 2000, 2006, 2012, 2018

100 m

44

CGLS LC-100

2015–2019

100 m

23

ESA World Cover

2020–2021

10 m

11

Dynamic World V1

2015-present

10 m

9

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MMU and 10 m MMW. In addition, this research also investigated whether the GEE cloud platform may aid in acquiring information on LU/LC when data from CLMS products is unavailable. One benefit is that Sentinel-1, Sentinel-2 and the Sentinel-3 OLCI images are available in the GEE data catalog, allowing LU/LC classifications to be performed with less operational and computing time due to GEE cloud-technology, as opposed to desktop software [17, 29, 49]. Aside from the CORINE Land Cover raster maps (at 100 m resolution), the GEE catalog also includes the Copernicus Global Land Cover, the ESA WorldCover and the Dynamic World V1 layers, which allow users to analyze temporal variations in LU/LC for the periods 2015–2019 (100 m resolution), 2015-present (10 m resolution), and 2020–2021 (10 m resolution).

4 Conclusion This research aims at investigating whether Copernicus data and services could contribute to LU/LC monitoring in European countries, which are increasingly experiencing soil sealing. As land is a finite resource, proper and effective management of its use, based on monitoring of LU/LC changes using different techniques, is crucial to protect soil from degradation and loss of ecological functions [7, 8, 12, 17, 29, 50–54]. The analysis revealed that the CLMS data is functional for achieving the research aims, but insufficient for a comprehensive examination due to a lack of high-resolution data in many European locations and the restricted temporal coverage of most of the data. Satellite images from the Sentinel mission, to be processed for LU/LC classification, as well as LU/LC datasets from the GEE public catalog, might assist to fill this void.

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Earth Observation Data for Sustainable Management of Water Resources to Inform Spatial Planning Strategies Alessandra Capolupo(B) , Carlo Barletta , Dario Esposito, and Eufemia Tarantino Department of Civil, Environmental, Land, Building Engineering and Chemistry (DICATECh), Polytechnic University of Bari, Via Orabona 4, 70125 Bari, Italy [email protected]

Abstract. Water is a vital resource for sustaining human life, well-being, and the Earth’s biodiversity and ecosystems. However, its availability and usability are decreasing due to strong anthropogenic pressure and intense climatic stress, leading to a variety of environmental issues, including desertification. Consequently, areas exposed to these factors, such as those in Southern Italy, are highly vulnerable to desertification. To address soil deterioration, it is crucial to identify and implement appropriate land management strategies aimed at promoting sustainability and improving ecosystem services. Remote sensing techniques provide a low-cost and non-destructive tool for extracting baseline information on water bodies, land use/cover classes, and Earth morphology features. When combined with meteorological data, these techniques can help identify the most effective, efficient, and sustainable water management strategies to tackle desertification. This is made possible by the vast amount of publicly available medium-resolution satellite data, such as Landsat and Sentinel missions, as well as open-source cloud infrastructures for managing big geographic data, like Google Earth Engine (GEE). The primary goal of this study is to provide a reference framework for a comprehensive workflow that moves from available data, through their proper elaboration with models, to knowledge management aimed at informing public policies. The case study presented provides a snapshot of the current state of natural water resource availability in the Apulian environment by identifying and evaluating the key hydrological balance components provided by the BIGBANG model. The input data for the model were images from Landsat missions and climate data handled in GEE. The results from the BIGBANG model were then used to define a scenario analysis to determine the best water resource planning and management policies. Keywords: Geospatial Big Data · Landsat images · Resilience · Risk reduction · Drought

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 24–35, 2024. https://doi.org/10.1007/978-3-031-54118-6_3

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1 Introduction Water supply sustainability is one of the world’s most pressing issues since it is the most critical resource for the health of human civilizations and economies [1]. Indeed, without such a source, living organisms can only survive for a few days, less than any other food font save fresh air. To meet the requirements of towns, agriculture, and industry, societies extract huge amounts of water from rivers, lakes, wetlands, and subterranean aquifers [2, 3]. This situation, exacerbated by climate change, is causing water shortages, affecting several social and environmental concerns, including the altering of historic seasonal human migration patterns and desertification [4–6]. Indeed, the Intergovernmental Panel on Climate Change (IPCC) forecasts a 2–4 degree Celsius increase in global earth surface temperature over the next 100 years [7], with a direct influence on the hydrologic cycle via increased evaporation and an indirect impact on ground-water [8, 9]. Saltwater intrusion and a decrease in water quality are additional repercussions introduced by the situation mentioned above [10, 11]. In this scenario, spatial planning strategies are crucial in ensuring sustainable water management practices, as they guide the allocation of water resources and the development of infrastructure and land use policies. To detect the optimal planning approaches, pinpointing the long-term dynamics of the major elements driving water cycle activity at all scales, from global to local, is crucial. Such information, in particular, should be sed to provide valuable insights into the spatial and temporal dynamics of water-related parameters, enabling a comprehensive understanding of water availability and quality and the connections between land and water bodies [12]. Traditional ground-based measurements and hydrological models have long been used to assess these components; however, they often suffer from limitations in spatial coverage and temporal resolution [13]. Earth Observation (EO) data, derived from satellite imagery and other remote sensing technologies, has attracted considerable attention in recent years due to its potential to provide a wealth of data on precipitation patterns [14, 15], soil moisture dynamics [16, 17], and changes in surface water bodies [18], allowing worthy perceptions into the behaviour and variability of the water cycle. EO significantly improves in-situ measurements by providing the information required to conduct such analyses extensively and continuously. As a result, it has significant advantages over traditional techniques. For starters, EO gives a panoramic picture of broad areas, allowing for evaluating water resources at regional and even global dimensions [19, 20]. This larger view makes it easier to identify water stress hotspots, floodprone areas, and places with insufficient access to clean water, which aids in developing focused spatial planning initiatives. Second, it gives information on numerous waterrelated characteristics simultaneously, allowing for integrated water resource management [21, 22]. Satellite observations, for example, may identify changes in surface water bodies, monitor water quality metrics like turbidity and chlorophyll-a concentrations, and estimate evapotranspiration rates from vegetated regions. These extensive statistics enable decision-makers to evaluate various water components’ status and trends and prioritise solutions accordingly. Third, EO provides excellent geographical and temporal resolutions, enabling for rapid and accurate water resource monitoring [23, 24]. Smallscale changes in water bodies and land-water interactions may be detected by satellite sensors with great spatial resolution, and frequent return intervals in order to assure the

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availability of up-to-date information. These skills are beneficial for guiding adaptive management techniques by monitoring seasonal fluctuations, drought conditions, and quick changes in the water supply. Despite EO’s enormous promise, significant hurdles remain in its proper integration into spatial planning techniques for water resource management. These difficulties stem from various factors, including technical constraints, data availability and quality, and the complexities of integrating disparate datasets and models. Addressing these arguments is critical in order to maximise its advantages and improve the capacity to make educated decisions about water resource management and climate adaptation. The combination of the recently released cloud-based platform Google Earth Engine (GEE) [25, 26] and the “Nationwide GIS-based regular gridded hydrological water budget” procedure introduced by the Italian National Institute for Environmental Protection and Research (ISPRA) [27, 28], known as Bilancio Idrologico GIS BAsed a scala Nazionale su Griglia regolare (BIGBANG), has emerged as a powerful tool for going beyond the limits mentioned above [22]. Indeed, GEE provides for faster acquisition and processing times, as well as customising scripts to meet the demands of users [29, 30]. Simultaneously, the BIGBANG model enables the integration of multiple data into a unique model capable of evaluating the water budget components on a monthly time frame. Thus, the main goal of this research is to provide a reference framework for a complete process that advances from available EO data to knowledge management intending to inform public policy. By identifying and assessing the important hydrological balance components offered through the BIGBANG model, the three selected case studies (Candelaro, Lesina-Varano, and Marina di Ginosa basins) provide a picture of the current status of natural water resource availability in the Apulian environment. These findings will serve as the foundation for a subsequent scenario-based study to identify the best planning solutions. To meet such a purpose a proper code was programmed in the GEE environment.

2 Materials and Methods The approaches employed to fulfil the study objectives are described in this section, with the operational process depicted in Fig. 1. Following the end of the data-collecting phase and the geodatabase creation, the climate-related parameters were spatialised using the Inverse Distance Weighting (IDW) interpolation method, and the monthly potential evapotranspiration was computed. As a result, the BIGBANG model was used to compute the water budget components as well as the natural availability of both surface water and ground-water resources, as stated below. An original JavaScript code was created and implemented in the GEE environment to carry out all of the operational process phases. 2.1 Case studies Candelaro (Fig. 2a), Lesina-Varano (Fig. 2b), and Marina di Ginosa (Fig. 2c) basins were chosen as pilot sites for this study to investigate the present condition of natural water supply in the Apulian environment.

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Fig. 1. Operative workflow description. Tmax: Maximum Temperature; Tmean: Mean Temperature; Tmin: Minimum Temperature; PET: Potential Evapotranspiration; EU-DEM: European Union-Digital Elevation Model; AWC: Available Water Capacity; WS: Soil Water Content; A: Liquid Inflow; E: Actual Evapotranspiration; CIP: Potential Infiltration Coefficient; G: Ground-water Recharge; R: Surface Runoff; Vsoil: Variation in Soil Water Content.

The Candelaro watershed is in northern Apulia’s Tavoliere (the most extensive alluvial plain in southern Italy and the second largest in Italy). Its overall area is approximately 2330 km2 . The Candelaro is bounded to the west by the Apennine Chain and to the east by the Mesozoic carbonate platform that grows from the Gargano Promontory. The basin has a mean elevation of 300 m, a maximum elevation of 1150 m, and the lowest elevation of 0 m a.s.l. The Lesina-Varano catchment, on the other hand, extends from east to west and is linked to the Adriatic Sea by two canals called “Schiapparo” on the eastern side and “Acquarotta” on the western side. It comprises two watersheds: those produced by the Lesina and Varano lakes, respectively. Lesina basin spans about 20 km2 and has an average depth of 0.8 m. The southwestern half of the lake receives all of its water from the intensive aquaculture farm (3 km distant). The surface area of Varano Lake is 26 km2 , and its circumference of 33 km. The average depth is 4 m, reaching 5 m in the centre zone. Lastly, Marina di Ginosa is located between the Bradano and Lato river basins, in the southern half of the “Bradanic Trough” foreland basin. The Galaso stream passes

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Fig. 2. Study areas location: a) Candelaro basin; b) Lesina-Varano basin; c) Marina di Ginosa basin; d) Apulian Region context.

through this region, which covers 116.2 km2 and has a maximum elevation of 92.4 m a.s.l. 2.2 The BIGBANG Model In order to examine the fluctuation of meteorological factors as well as physical and hydrogeological features, the BIGBANG water budget model adopts a spatially dispersed technique [31]. It reproduces the primary hydrogeological components monthly, such as liquid inflow (A), actual evapotranspiration (E), ground-water recharge (G), Soil water content variation (Vsoil ), and surface runoff (R), using the Thornthwaite and Mather (1955) method [32] (Eq. 1). A − E = R + G + Vsoil

(1)

E was estimated using the soil sealing maps given by ISPRA for 2015–2018 (Table 1). According to [35], Ei was set equal to 0 due to the lack of vegetation and, as a result, evapotranspiration, whereas Ei was calculated using Eq. 2 for non-impervious surfaces: Ei = f (Ai , PETi , AWC, WSi−1 ,)

(2)

PETi denotes monthly potential evapotranspiration, estimated using the Hargreaves Equation [36]. Such an algorithm was chosen above the other models owing to its simplicity and flexibility to Mediterranean local conditions [37]. AWC and WSi-1 are the available water capacity and the soil water content in the month i-1 , respectively. The information concerning impervious and non-impervious surfaces were detected from the soil sealing maps, provided by ISPRA (Table 1).

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Conversely, R and G were computed by calculating the Potential Infiltration Coefficient (CIP) and the surplus (Eqs. 3 and 4):  for  impervious surface Ai , Ri =  (3) CIP 1 − 100 ∗ surplusi , for  non − impervious surface  0, for  impervioussurface (4) Gi = CIP   100 ∗ surplusi , for non − impervioussurface The information supplied by ISPRA’s Mouton’s hydrogeological complexes map was utilized to define CIP value. The surplus was estimating by using Eq. 5:   surplusi = max (Ai − PETi ) − (AWC − WSi−1 ) , 0 (5) Lastly, ΔV soil was calculated by inverting Eq. 1. Thus, in the adopted model, the rainfall is assumed to penetrate the soil; however, after the soil storage capacity is achieved, the surplus rainfall forms surface runoff and aquifer recharge. Evapotranspiration is expected to continue at its potential rate until soil water storage reaches an intermediate characteristic value WS*, which is commonly assumed to be half of AWS. 2.3 GEE Platform and JavaScript Code Development GEE (https://earthengine.google.com/) offers a reliable and effective cloud-based infrastructure for accessing and processing huge amounts of geospatial data. JavaScript as a programming language provides a versatile and user-friendly environment for code generation and analysis procedures [25, 26]. The GEE Application Programming Interface (API), which presents a set of libraries and tools for data manipulation, visualization, and analysis, is used to create JavaScript code. As a result, it has become the primary programming language for GEE due to its widespread adoption and its compatibility with web-based applications [33, 34]. JavaScript code development in GEE typically occurs in a structured manner. It starts with data ingestion, which involves importing satellite images, geospatial information, and auxiliary data into the GEE system. Table 1 shows the input data for this investigation. Following that, JavaScript code may be used to carry out various analyses and computations. As a result, this study created a suitable script to apply the BIGBANG model, as mentioned in the preceding Section. Consequently, ground-water recharge was calculated as a percentage of total surface runoff and ground-water volume as a proxy for the permeability of the underlying hydrogeological units.

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A. Capolupo et al. Table 1. Selected input data

Data

Source

Reference years

Link

Monthly mean observations (P, Tmax, Tmean, Tmin)

Apulia Region

2015 to 2018

https://protezionecivile. puglia.it/annaliidrolo gici-parte-i

Soil sealing maps

ISPRA

2015 to 2018

http://groupware.sin anet.isprambiente.it/usocopertura-econsumo-dis uolo/library/consumodisuolo

EU_DEM v1.0

Copernicus Land Monitoring Service

2000

https://land.copernicus. eu/imagery-insitu/eudem/eu-demv1-0-andderivedproducts

Available Water Capacity map

European Soil Data Center

2015

https://esdac.jrc.ec.eur opa.eu/content/topsoilphysical-propertieseu rope-based-lucastopsoildata

Mouton’s hydrogeological complexes map

ISPRA

1982

http://www.sinanet.isp rambiente.it/it/siaispra/ downloadmais/comple ssiidrogeologici/view

3 Results and Discussion Aquifer recharge is a challenging process to analyse since it is affected by a variety of factors such as climate, geo-hydro morphology and human activities. As a result, it is frequently carried out at a local scale using sophisticated and time-consuming models. Nonetheless, in contrast to the bulk of ground-water recharge studies, the simplified BIGBANG model was used to offer quick and straightforward estimates of the basic water budget components in this research. As stated by [27, 28], the monthly comparison shows significant consistency across the findings produced from several models at various scales, pinpointing the same times for deficiency and exceedance. Indeed, [27] found discrepancies between methodologies and scales of less than 15%. Thus, the BIGBANG method was adopted to extract the main water budget components for 3 years reference period (2015–2018) for the three selected case studies: Candelaro, Lesina-Varano and Marina di Ginosa basins, over a three-year reference period (2015–2018). Despite the fact that they are in three separate regions of the Apulian Region, the climatic and geological circumstances are very similar (Fig. 3). Indeed, precipitation, evapotranspiration, surface runoff, and groundwater recharge levels are comparable in the Candelaro and Lesina-Varano basins. The Marina di Ginosa catchment, on the other hand, has the lowest values. In particular, it experienced no ground water recharge in 2015–2016 and 2017–2018.

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Fig. 3. Annual water budget components for the hydrological years 2015–2016, 2016–2017 and 2017–2018 related to Candelaro (a), Lesina-Varano (b) and Marina di Ginosa (c), respectively.

The monthly analysis also confirmed such trends (Fig. 4). Indeed, the first two catchments have comparable tendencies, although Marina di Ginosa has a distinct pattern. Because Marina di Ginosa is one of the driest places, it has the highest potential for evapotranspiration. Such a parameter is affected by many factors, such as climate conditions and soil types. It increases with rising temperatures and wind decrement under the same geomorphological conditions. Figure 5 reports E, R and G maps for the three selected case studies of January 2017. According to the BIGBANG data, the Candelaro and Lesina_Varano basins are rainier than the Marina di Ginosa site and are characterized by a certain groundwater recharge between 2015 and 2018. Furthermore, E exceeds precipitation practically everywhere (Fig. 4). These factors suggest that they should be free of aridity. Marina di Ginosa, on the other hand, is prone to aridity due to comparable evapotranspiration and precipitation values. Actually, no ground-water recharge has been discovered during the research period.

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Fig. 4. Monthly water budget components for Candelaro (a), Lesina-Varano (b) and Marina di Ginosa (c), respectively

Fig. 5. E, R and G for Candelaro, Lesina-Varano and Marina di Ginosa basins related to January 2017.

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4 Conclusion The BIGBANG model, in conjunction with GEE, is a valuable tool for quickly assessing the supply of water resources at various temporal and spatial scales. Indeed, overexploitation and non-renewable resource depletion are mostly caused by quality degradation, water scarcity situations, and climate change. As a result, adequate planning and management measures are required to conserve and optimise water for long-term use. By giving trustworthy information in a timely manner, the BIGBANG model may eventually become an operational tool to aid in the sustainable and adaptive management of water resources, particularly in drought and water crisis situations. Its outcomes will be utilized as input data for a scenario-based approach to determining the best planning solution.

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Future Urban Setting and Effects on the Hydrographic System. The Case Study of Bologna, Italy Emilio Marziali(B)

, Gianni Di Pietro , and Cristina Montaldi

University of L’Aquila – Department of Civil, Construction-Architectural and Environmental Engineering, Monteluco Di Roio, Piazzale E. Pontieri 1, 67100 L’Aquila, Italy [email protected]

Abstract. Urban planning should include the natural features of the territory such as its geology, geomorphology, and urban settlements, but this only happens marginally. Hydrogeological risk affects 31% of the Italian territory, and extreme events are increasingly frequent. They put in crisis the systems of sewerage systems or that generate the flooding of waterways. For these reasons, it is important to study the role of natural infrastructure in flood hazards and the service of sediment retention in a catchment. The study area is the portion of the water catchment area of the Reno River, which collects water from the Tuscan-Emilian Apennines, upstream of the metropolitan area of the city of Bologna. The choice of the study area is linked to the extreme meteoric event that occurred in September 2021, which put in crisis the sewerage network of Bologna city and caused severe hardship to the population and strategic structures. The analyses concern two ecosystem services: urban flood risk mitigation and overland sediment generation and delivery. Specifically, using InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) software, it is assessed how the full implementation of the municipal planning forecasts can affect the provision of these services. Local planning transposes the overarching constraint planning, but it is essentially adding the knowledge of the ecosystem services that are usually neglected in the definition of plan strategies. The inclusion of ecosystem services, in addition to contributing to a holistic vision, guarantees a more resilient territory, especially concerning the growing threats related to climate change. Keywords: Ecosystem services · Sustainable urban development · Flood risk · Soil sealing

1 Introduction Water represents a fundamental value of the territory, as a priority asset of life and environmental protection, and as a historical, cultural, civil, and social support. However, it is also a presence that, being linked to natural hydrological dynamics, occasionally it becomes the protagonist of intense flooding events of a catastrophic nature that have always marked and defined the development of the territory [1, 2]. Currently, © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 36–46, 2024. https://doi.org/10.1007/978-3-031-54118-6_4

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it has even greater effects, given the extreme urban sprawl that has occurred in many metropolitan areas. Floods are natural phenomena that are very difficult to predict [3]. However, certain human activities such as the growth of human settlements, the increase in economic activities in floodplains, and the consequent reduction in the natural water retention capacity of the soil, all contribute to increasing the likelihood and aggravating the adverse effect of floods [4, 5]. A flood phenomenon is any episode involving the overflowing of water in areas that are usually not flooded. In urban areas, for example, two main phenomena are generally linked to flooding events: the overflowing of watercourses (river or embankment floods) and the surface runoff of rainwater during precipitation events [6]. Flood peaks in watercourses and sewerage networks are reached much earlier, increasing the likelihood of flooding in the watercourses into which the watercourses or networks discharge. As a result, flooding often occurs because there are not enough channels to handle the flows generated by heavy rainfall [7]. In addition to the increasing frequency and unpredictability of extreme events due to climate change, a major contributing factor is the increase in land consumption with a consequent increase in surface runoff and a decrease in deep water absorption [8–10]. Due to its geographical position, Emilia-Romagna is one of the Italian regions most affected by the phenomena mentioned above. The region is affected by numerous Apennine and Alpine genesis hydrographic basins. However, the hydrogeological risk is exceptionally high due to the strong impermeabilization that these soils have undergone over the years. As reported in the 2022 Istituto Superiore per la Ricerca e la Protezione Ambientale (ISPRA) soil consumption report [11], it is the first region in Italy for cementing in alluvial areas with more than 78.6 hectares in 2021 in areas of high hydraulic hazard. Between 2020 and 2021, Emilia-Romagna was the third largest Italian region in terms of soil consumption, with more than 658 hectares cemented in a single year, equal to 10.4% of all national soil consumption; in just a few years it has reached an 8.9% impermeable surface area against a national average of 7.1%. These data are completely at odds with the statements of the Po River District Basin Authority’s flood risk management plan [12]. The river basin authority encourages countering the soil consumption resulting from urbanization and sealing. The authority promotes national and regional policies for sustainable land planning and it aimed at rebalancing the relationship between urban spaces, agricultural spaces, and natural spaces. Starting from these assumptions, the work analyses how the transformative forecasts present in the municipal urban plans of the municipalities of the metropolitan city of Bologna can influence the water retention capacity of soils and, consequently, the possible effect on the existing urban system. The analysis was conducted through the evaluation of two specific ecosystem services for (Urban Flood Risk Mitigation and Sediment Delivery Ratio) a basin mainly contained in the metropolitan city of Bologna. The work led to the elaboration of models that allowed the identification of the geographical areas whose land cover changes could have a greater impact on the settlement system involved.

2 Study Area The study area covers 1,121 km2 between the region of Emilia-Romagna (905 km2 ) and the region of Tuscany (216 km2 ) and comprises 30 municipalities, 21 of which are in the metropolitan city of Bologna, 3 in the province of Pistoia and 2 in the provinces of

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Modena and Prato and the metropolitan city of Florence. The population density (DA) of the area is 266 inhab./km2 (higher than the national value), with considerable differences between the municipalities downstream of the catchment area, located along the Po Valley (Bologna and Casalecchio di Reno respectively with DA = 2.753 inhab./km2 and DA = 2.064 inhab./km2 ) and the upstream municipalities, located along the Apennine chain (Firenzuola and Sambuca Pistoiese, respectively with DA = 16 inhab./km2 and DA = 18 inhab./km2 ). Some municipalities are entirely contained in the catchment area, others are affected for variable portions of their territory (from 50% to less than 10%). In the study area, according to ISTAT (Istituto Nazionale di Statistica ISTAT) data on 1 January 2023, there were about 600 000 inhabitants (municipalities with less than 10% catchment area were excluded) (Fig. 1).

Fig. 1. Study Area

The average altitude of the study area is 593 m asl, with values above 900 m asl along the Tuscan-Emilian Apennines and a value of 100 m asl for the metropolitan city of Bologna, located downstream of the basin. In the study area, 61% of the territory is covered by forest areas, 11% by urbanized sites, 23% by agricultural areas, and 5% by watercourses and others (4%) [11]. According to ISPRA data, 20,400 ha of soil had been consumed by 2022, an annual increase of more than 20 ha over the previous year. As far as municipal planning instruments are concerned, 8 municipalities have a plan approved after 2015, 15 have a plan approved between 2009 and 2014, and 7 have a plan from before 2009. From an economic point of view, the per capita income of the study area is e 22,253 (MEF 2021), which is higher than both the national average (e 19,129), that of the Emilia-Romagna Region (e 21,709) and that of the Tuscany Region (e 20,358). The basin in question includes the Reno River, which extends for 82 km out of a total of

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1,326 km, and several streams, including the Setta (43 km), the river’s major tributary, and the Limentra di Treppio (29 km), both right-hand arms.

3 Material and Methods The analysis is based on assessments of two specific ecosystem services: urban flood risk mitigation and terrestrial sediment generation and release. The study was conducted in both cases using the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) software, which is one of the main references in this field. The software contains a set of models into which specific input data must be entered according to the ecosystem service being analyzed. Common starting data is the land use map. Specifically, the modules of interest are: Urban Flood Risk Mitigation (UFRM) and Sediment Delivery Ratio (SDR). The UFRM model calculates the flood retention due to green spaces and also estimates the economic damage avoided due to flooding (or the economic benefits due to flood retention) based on the footprint of buildings. The input data of the UFRM model are the basin area of interest, rainfall height, land use map, hydrological soil groups, biophysical table, and building infrastructure with a table of associated potential economic damage. The study area is contained in the catchment area of the Reno River with the closing section in Bologna at the point of coordinates (685986 E; 4934831 N; EPSG 32632). The area was obtained in an open GIS environment, using SAGA’s Fillsink – (Wang & Liu)” [13], “Channel” and “Unslope Area” algorithms, from the DEM downloaded from Tinitaly version 1.1 (updated to January 2023) [14, 15]. The output raster was vectorized to obtain the contour of the study area. The 27 September 2021 rainfall event was taken into account for the choice of rainfall height, which caused numerous inconveniences to the city of Bologna, and in which the measured rainfall height was 65.6 mm [16]. The rainfall height value was increased by about 7% by design assumptions. For the EmiliaRomagna Region, the land use data is that of 2017 [17] with a resolution of 10 m, whose Minimum Mapping Unit (MMU) is equal to 1,600 m2 , while the thematic detail goes up to level 4 of the Corine Land Cover nomenclature. For the Region of Tuscany, the land use is that of 2019 [18] with a 10 m resolution and thematic detail at level 3 of the Corine Land Cover legend. The land uses of the two regions were pre-processed, merged, and transformed into rasters (10 m resolution) for processing by the InVEST software. The map of soil hydrological groups [19] has a resolution of 250 m/pixel and each soil group is represented by the following categories: • Class A: very high infiltration potential (low surface runoff potential); includes deep, very permeable sands and gravels. • Class B: moderately high infiltration potential (moderately low surface runoff potential). • Class C: moderately high infiltration potential (moderately low superficial runoff potential). • Class D low infiltration potential (very high surface runoff potential); includes clays and thin soils. The biophysical table, which associates the Curve Number with each land use class, is derived from the literature [20]. The vector layer of the footprint of the buildings,

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with their classification according to their use, was obtained from the Emilia-Romagna regional geoportal. In analogy to [21], only the buildings of the City of Bologna, located downstream of the catchment area, were considered for this study. Damage data were made available by the European Community [22]. The InVEST SDR model estimates the annual soil loss for the basin of interest according to the Revised Universal Soil Loss Equation (RUSLE) model algorithm [23]. uslei = Ri · Ki · LSi · Ci · Pi

(1)

Ri = rainfall erosivity; Ki = soil erodibility; LSi = slope length-gradient factor; Ci = cover-management factor; Pi = support practice factor. The input data of the SDR model are the DEM, the rainfall erosivity map, the soil erodibility map, the land use, the catchment area of interest, the biophysical table, and other parameters from the scientific literature and the InVEST user manual [24]. The digital elevation model is the same as the one used to derive the catchment area. The rainfall erosivity map reflects the intensity and duration of rainfall in the area of interest. The soil erodibility map, on the other hand, represents the susceptibility of soil particles to detachment and transport by rain and runoff. Both were obtained from ESDAC (European Soil Data Centre); the soil erodibility (K factor) has a resolution of 500 m/pixel [25]; the global erosivity map (https://esdac.jrc.ec.europa.eu/content/global-rainfall-ero sivity) has a resolution of 30 arc seconds (~1 km) [26]. Since the K factor is a global figure, it has limitations and does not consider the municipality of Bologna as a whole. The land use raster is the same as used in the UFRM model. The biophysical table associates each land-use code with the biophysical properties of that class by considering the parameters C and P in Eq. (1). The default parameters are as follows: 1000 for the flow accumulation threshold, 2 for the Borselli k parameter, 0.5 for the IC 0 parameter, and 0.8 for the maximum SDR value. The used methodology is shown in Fig. 2. For both models, two scenarios were analyzed, one with only the land-use type in its current state and the other with the overlapping of municipal planning instruments, with the hypothesis that 100% of what is in the plans is approved. In the second scenario, only the urban plans of the metropolitan city of Bologna [27] are considered both because the other provinces of Romagna occupy negligible portions of territory and because the region of Tuscany has not yet made available all municipal urban plans. Finally, normalized indices given by the ratios of the difference between the results of the second scenario to that of the first scenario and the sum of the difference over the entire basin were determined for both models. These indices were compared with the ratio between the municipality’s area belonging to the bay of interest and the total area.

4 Results The maps in Fig. 3 show the results obtained from the analysis using the UFRM model and are representative of rainfall-related surface runoff, expressed in mm. The left-hand side of Fig. 3, depicting the first scenario, shows the result of the scenario in its current state. It can be observed that, with a rainfall event characterized by a rainfall height of 70 mm, most of the basin of interest has a runoff potential of between 15 and 20 mm.

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Fig. 2. Flowchart of used analysis methodology.

Lower runoff values can be attributed to water bodies, forest areas, and specific categories of agricultural regions, particularly those in the Apennine and sub-Apennine zones. Higher Runoff values, ranging between 50 and 60 mm, are instead located in the main urban centers in the northern part of the area of interest, downstream of the study basin. The UFRM model returned a series of outputs characterizing the phenomenon throughout the basin. In the present case, the average of the Runoff Retention values (min 0, max 1) is 0.66. The sum of the Runoff Retention volumes is 51,183,990 m3 . The flood volume is equal to 26,748,414 m3 . The right-hand side in Fig. 3, which is representative of the second scenario, shows the result of the second scenario with the overlay of municipal planning instruments on land use. The area downstream of the basin is characterized by higher Runoff retention values (50–60 mm). The average of the Runoff Retention values is 0.63, a difference of 3 percentage points implying the soil’s lower capacity to filter water than the current state. In absolute value, the sum of the Runoff retention volumes is 49,376,574 m3 , which is about 1.8 million m3 less than the current state. Lastly, the flood volume is 28,555,831 m3 . The higher values for the flood volume in the second scenario show that the full implementation of all plans would significantly worsen the surface runoff phenomenon. Based on these results, analyses were carried out by calculating normalized indices for each municipality of the metropolitan city of

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Fig. 3. UFRM Model – Runoff retention [mm]. Current state (left). Complete implementation of urban plans (right)

Bologna contained in the basin of interest. The results are shown in the graph in Fig. 4. Only municipalities with a runoff retention ratio value of more than 1% are present.

Fig. 4. Comparison of normalized indices. UFRM model

The graph in Fig. 4 shows that the municipalities with the highest percentages of Runoff retentions are:

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• Sasso Marconi, with a water retention index of 51.9% about the total retention in the basin, despite a percentage of contained area in the basin of 7.64%; • Bologna with a value of 15.4% water retention compared to the total retention in the basin compared to an area of 7.81%; • Marzabotto with an index of 9.6%, compared to a municipal area in the basin of 8.19%. In the municipalities listed above alone, the Runoff Retention value is equal to 1,391,371 m3 (about 77% of the total) for an area of 214 km2 (24% of the EmiliaRomagna area contained in the basin). A further output of the UFRM model is the economic damage to buildings by use. It has been estimated that for the buildings in the city of Bologna contained in the basin (45,427 out of 88,753 in the entire basin), there is a potential economic loss of more than EUR 6 billion. Regarding the outputs of the SDR module, data were obtained on the total amount of sediment exported over the entire basin, the full potential amount of soil loss, and the sediment deposited on the whole area of interest. The absolute values of the first and second scenarios for the analyzed area are reported. The total amount of potential soil loss in its current state is 1,158,889,320 Mg/ha, while there is a potential loss from the possible implementation of urban plans of 1,216,947,461 Mg/ha (5% higher). The total amount of potential soil loss in its current state is 1,158,889,320 Mg/ha, while there is a potential loss from the possible implementation of urban plans of 1,216,947,461 Mg/ha (5% higher). There is an increase of 7.7% in the loss of exported sediment. Finally, the amount of sediment deposited throughout the basin is 730,158,573 Mg/ha (current state) and 757,131,833 Mg/ha (future state). In the latter case, there is the smallest percentage increase (3.69%). Two normalized indices concerning Sediment Export and Soil Loss were developed for the SDR model. Both were compared with the ratio of the municipality’s area belonging to the basin of interest to its total area. The results obtained are shown in the graph in Fig. 5.

Fig. 5. Comparison of normalized indices. SDR model

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As with the UFRM model, municipalities with a Sediment Export and Soil Loss ratio of less than 1% were not taken into account. The three municipalities with the highest percentages of Sediment Export and Soil Loss are: • Sasso Marconi, with an index of sediment exported and soil loss of 76.6% and 73.2% respectively, compared to a municipal area contained in the basin of 7.64%. • Bologna, with values of the index of exported sediment and lost soil of 6.4% and 7.7% respectively, compared to an area of 7.81%. • Marzabotto, with an index of exported sediment and lost soil of 2.5% and 2.2 against an area of 8.19%. The total value of the difference between the second and first exported sediment scenario of the 3 municipalities is 10,446.573 Mg/ha (85% of the entire basin difference). The total value of the difference between the second and first Soil Loss scenarios is 48,257,478 Mg/ha (83% of the difference for the entire basin).

5 Discussion and Conclusion Biodiversity and ecosystem services play a fundamental role in human life and economic well-being [28, 29]; for these reasons, the need for protection and conservation is paramount. Quantifying ecosystem services spatially explicitly can help make planning decisions about the fate of soils certainly more effective and efficient [30]. Today there is a growing awareness of the value of soil as a primary element of our civilization, sustaining our existence and ensuring the survival of life on the planet [31, 32]. The proposed study analyzed the impact of the full implementation of urban planning tools in the municipalities of the Metropolitan City of Bologna on two essential ecosystem services: surface runoff and sediment transport. The results obtained from the UFRM and SDR analyses showed an apparent increase in surface runoff with risk increases (probability of flooding, sediment transport, and surface water erosion) for the urban areas involved. The combination of these factors increases the chances of flooding in areas that are particularly susceptible to hydrogeological disruptions such as those covered by this study. The study made it possible to identify the municipalities in which the plan transformation projections lead to a deterioration in the hydraulic condition. This makes it possible to intervene punctually on the territory through dedicated measures. Measures such as relocating forecasts, delocalizing them, or transferring building rights to other areas could be highly effective once the territories whose sealing would significantly impact the entire basin have been identified. This depends on the geographical location and the type of soil affected by the forecasts. The methodology adopted in this work can also be replicated in other contexts, which is certainly a point of considerable interest. The analysis at the basin scale, constitute an extremely important information base for the formation of the cognitive frameworks of the plans operating at the same scale (e.g. Piano di Assetto Idrogeologico and Piano Stralcio di Difesa dale Alluvioni). It would provide indications, prescriptions and constraints to reduce the risks associated with increased surface runoff and improve the provision of essential ecosystem services. On eof the limit of this study is linked to the data used. For example, the SDR model’s input data are global (K-Factor and hydrological soil groups) with gaps in the areas

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analyzed. The UFRM model provides an estimate of economic losses due to flooding, which can be of great use to administrative authorities and planners. Despite their simplifications, these models can represent a first approach to making water a protagonist in urban planning, as this is still done marginally today. The inclusion of the topic of water in urban planning appears to be extremely necessary also to comply with the increasingly frequent constraints of European and national regulations on water protection (EU Directive 2000/60 implemented by Legislative Decree 152/2006) and flood management (EU Directive 2007/60 implemented by Legislative Decree 49/2010). The proposed research provides an interesting and innovative insight into the use of InVEST models for the elaboration of risk scenarios (both geographical and numerical). These represent an indispensable information base for the implementation of measures to mitigate the increasingly probable impacts linked both to climate change and to the high level of sealing.

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15. Tinitaly, https://tinitaly.pi.ingv.it/, last accessed 20 February 2023 16. Agenzia Prevenzione Ambiente Energia Emilia-Romagna, https://www.arpae.it/it/temi-amb ientali/meteo/report-meteo/annali-idrologici/annali-idrologici-2021/view, last accessed 23 February 2023 17. Geoportale Regione Emilia-Romagna, https://geoportale.regione.emilia-romagna.it/, last accessed 01 MarchFebruary 2023 18. Geoportale Regione Toscana, https://dati.toscana.it/dataset/ucs/resource/c60342ad-e29747bd-ad40-dea69e619bf1, last accessed 01 March 2023 19. Ross, C.W., et al.: Global Hydrologic Soil Groups (HYSOGs250m) for Curve Number-Based Runoff Modeling. ORNL DAAC, Oak Ridge, Tennessee, USA (2018) 20. Quagliolo, C., Comino, E., Pezzoli, A.: Experimental flash floods assessment through urban flood risk mitigation (UFRM) model: the case study of Ligurian coastal cities. Frontiers in Water 3, 1–16 (2021) 21. Bose, S., Mazumdar, A.: Urban flood risk assessment and mitigation with InVEST-UFRM model: a case study on Kolkata city, West Bengal state (India). Arab J Geosci 16(320) (2023) 22. Huizinga, J., Moel, H., Szewczyk, W.: Global flood depth-damage functions. Methodology and the database with guidelines. EUR 28552 EN (2017) 23. Renard, K., Foster, G., Weesies, G., McCool, D., Yoder, D.: Predicting Soil Erosion by Water: A Guide to Conservation Planning With the Revised Universal Soil Loss Equation (RUSLE). U.S. Department of Agriculture, Agriculture Handbook, 703 (1997) 24. Sharp, R., et al.: InVEST user’s guide. The Natural Capital Project: Stanford, CA, USA (2014) 25. Panagos, P., Meusburger, K., Ballabio, C., Borrelli, P., Alewell, C.: Soil erodibility in Europe: A high resolution dataset based on LUCAS, Science of Total Environment, 479–480 (2014) 26. Panagos, P. et al.: Global rainfall erosivity assessment based on high-temporal resolution rainfall records. Scientific Reports 7(1) (2017) 27. Città metropolitana di Bologna, (http://cartografia.cittametropolitana.bo.it/catalogo/), last accessed 04 February 2023 28. Fisher, B., Polasky, S., Sterner, T.: Conservation and human welfare: economic analysis of ecosystem services. Environ. Resource Econ. 48, 151–159 (2011) 29. Srivathsa, A., Vasudev, D., Nair, T.: Prioritizing India’s landscapes for biodiversity, ecosystem services and human well-being. Nat Sustain 6, 568–577 (2023) 30. Woodruff, S.C., BenDor, T.K.: Ecosystem services in urban planning: Comparative paradigms and guidelines for high quality plans. Landsc. Urban Plan. 152, 90–100 (2016) 31. Boatti, G.: Un Paese Ben Coltivato: Viaggio Nell’Italia Che Torna Alla Terra e, Forse, a Sé Stessa. Laterza Editore (2016) 32. Martinelli, L.: Salviamo il paesaggio!: manuale per cittadini e comitati : come difendere il nostro territorio da cemento e grandi opere inutili. 2nd edn. Altreconomia (2013)

Using SAR Observation Data to Support the Spatial Planning in Areas Affected by Landslide Phenomena Alberico Sonnessa(B) Department of Civil, Environmental, Land, Construction and Chemistry (DICATECh), Polytechnic University of Bari, Via Orabona 4, 70125 Bari, Italy [email protected]

Abstract. Due to the hydro geological instability involving our territories, soil ecosystems and built areas are increasingly threatened by potentially catastrophic phenomena, such as subsidence or landslides, which can also pose a danger to people safety. In the light of this, a comprehensive characterization of the instability, in terms of spatial extent and evolution over time, is needed for managing the related risk, take the proper mitigation actions and drive the spatial planning activities. Geospatial data, such as Copernicus Sentinel-1 Synthetic Aperture Radar (SAR) observations, processed using Multi-Temporal Interferometric (MTInSAR) techniques, represent a well-established and reliable tool for controlling large areas interested by ground motion events. Open and free SAR data, provided by the European Space Agency through the European Ground Motion Service, constitute an additional support. The proposed research shows the results of an application of SAR geospatial observations in the monitoring of an anthropic area affected by a landslide. To this aim, satellite acquisitions have been utilized to thoroughly describe the instability occurrence, by retrieving its main kinematic parameters and quantifying its extent. The outcomes of the analysis addressed the design of the mitigation measures to be taken for securing the study area and helped the regional Government Commissioner for the environmental risk in the planning of the future use of the space involved in the landslide phenomenon. Keywords: Land management · Land monitoring · Copernicus · MTInSAR · EGMS

1 Introduction Due to its peculiar morphological and geological features, the Italian territory is increasingly prone to hydro geological instabilities [1] involving soil ecosystems and built areas, which are always more frequently threatened by potentially catastrophic phenomena, such as subsidence or landslides, posing a danger to people safety. Therefore, spatial planning and land management actions must consider the influence of these critical events on the territory and the urban centers, to properly address © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 47–56, 2024. https://doi.org/10.1007/978-3-031-54118-6_5

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the design of all the relevant activities related to the land transformations, in the most sustainable way possible [2, 3]. As well known, slow ground instability may impact the safety of structures and people [4]. The detection and the control of the associated kinematic parameters (i.e. displacements and displacement velocities) can encompass different methodologies, such as ground [5, 6] and/or satellite-based (e.g. SAR [7, 8], Global Navigation Satellite Systems – GNSS [9]) geomatic techniques. Radar images acquired by means of spaceborne SAR sensors and analyzed using the MTInSAR techniques (briefly described in par. 2) can effectively foster the understanding of ground deformation phenomena involving infrastructures and buildings [10, 11]. The capability of inspecting large portions of territory with a high-frequency temporal sampling allows to analyze diffuse instability through Persistent Scatterer Interferometry (PSI) [12], which provide information about motion/motion rates along the line-of-sight (LoS) of scatterers belonging to the investigated area. In the context of land monitoring, the European Space Agency (ESA) plays a key role through the Copernicus Programme which includes the Sentinel-1 (S1) mission, consisting of two quasi-polar-orbiting satellites, equipped with SAR devices operating in C-band [13]. Since 2022, ESA also provides free displacement SAR data through the Copernicus European Ground Motion Service (EGMS) [14]. Currently, displacement time series are available between February 2015 and December 2021, while additional data concerning the year 2002 will be available since October 2023 [15]. The presented study is aimed at bringing out the effectiveness of spatial techniques in the land management, where the prompt identification and the thorough analysis of the displacement field generated by the progression of an instability process is crucial to correctly implement the most effective strategies supporting the decision managers [16, 17]. Displacement maps derived from satellite SAR data have been used to characterize an anthropic area, affected by a slow landslide phenomenon, under the attention of the Government Commissioner for the environmental risk of the Apulia region, which is in charge for the implementations of proper interventions for mitigating the effects of the instability process. The presented outcomes are part of the results of a broader project, within which the geomatic analyses permitted to retrieve the main kinematic parameters characterizing the displacement field and highlight the presence of differential movements. These findings are supporting the geo-hydro-mechanical modelling of the landslide mechanism and the design of the mitigation actions. Furthermore, in the context of the Italian National Strategy for the Inland Areas [18], focused at countering the depopulation of Italian inner territories with poor and distant essential services (education, health, mobility), causing cultural, social, and economic impoverishment of these regions, this study wishes to contribute to the improvement of the resilience of the investigated areas vs. landslide, and provide elements useful for the planning of regeneration actions.

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2 The MTInSAR Technique and the EGMS Program MTInSAR technique is based on the coherent image principle of synthetic aperture radar (SAR), in which a sensor uses electromagnetic waves to acquire and collect information on amplitude and phase of the signal reflected/scattered back from the surface. This technique enables displacement measurements along the so-called LoS, (i.e. the direction sensor-to-target) exploiting the phase difference between the backscattered signals of two radar images acquired in different epochs, thus making possible long-term analysis of modifications in the Earth’s surface with centimetric or millimetric accuracy [19]. The technique allows identifying reliable coherent measurement points (MP), i.e. Persistent Scatterers (PS) associated with a single pixel of the image and Distributed Scatterers (DS), related with a group of statistically homogeneous pixels of the same image, for which motion velocity values and time series of deformation are extracted. As well known, the main limitations of this technique are the lack of MP in vegetated areas, and the low sensitivity to the North-South component of the displacement due to the quasipolar orbits characterizing the S1 satellite missions. However, under certain assumptions [20], the estimation of the velocity of an MP can reach an accuracy in the order of than 1 ÷ 2 mm/year. In this context, the European Union’s Earth observation space programme, named Copernicus, provides, among its Land Monitoring Services openly accessible to all users, the European Ground Motion Service (EGMS). Based on the MTInSAR analysis of S1 radar images at full resolution, the EGMS allows the analysis of deformations phenomena, natural or triggered by the anthropic activity, such as slow-moving landslides or subsidence, also serving as a starting point for detecting and investigating ground motion affecting urban areas and infrastructures [21]. The EGMS also provide, via webgis, tools for visualization, interactive data exploration and user uptake elements for further investigations [22].

3 The Case Study The analysis of the spatial dataset related to a ground instability phenomenon has been carried out on the municipality of Chieuti, located in the South of Italy. The town of Chieuti, sited in the Apulia region (Fig. 1), was founded in the 15th century by Albanian immigrants. Agriculture is the most important source of its economy income. The old town is perched on a hilltop at 221 m a.s.l., where a population of about 1600 people is currently living. Being the municipality closest to the northern border of Apulia, Chieuti has been awarded the title of Porta della Puglia (Apulian Door) by the Ministry of Economic Development. This strategic position, along with the care in preserving its cultural identity and traditions (e.g. the use of an ancient idiom called arbëreshë, typical of the southern Albania), make Chieuti a very peculiar hamlet. The historic center is characterized by masonry buildings and alleys. Evidence of instabilities affecting the old town has been recorded since 1800, as reported by archive documents referring to collapses of structures positioned in the north-western sector bordered by Largo Quattro Novembre, Via dei Martiri di Via Fani

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Fig. 1. Case study. The town of Chieuti (source: Google Earth).

and part of Via Vitalia (Fig. 2). Buildings located westward the red dash-dotted line have suffered from the cumulation of mainly downward displacements, caused by a landslide. Unfortunately, all the mitigation actions, implemented in the last decades to counter the landslide phenomenon, have had a reduced effectiveness. The most recent intervention, consisting of a concrete retaining wall connected to the pre-existing structure founded on shallow footings (dated 1987–1989), has been built between 2004 and 2006 (yellow line in Fig. 2). This construction shows the effects of a still ongoing instability.

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Fig. 2. The old town affected by the instability. Number 1,2,3, indicate the location of some of the damages clearly detectable on the field.

4 Analysis of the SAR Dataset The analysis of the MTInSAR measurements has been focused on the estimation of the distribution and magnitude of the displacement rates over the investigated area, by using an S1 interferometric dataset and made available by the Government Commissioner. Under the hypothesis of absence of deformation of the structures, the results can be considered indicative of the ground morphology evolution. Hereafter, the results refer to an image processing whose acquisition spans from 12 April 2015 to 30 November 2021. Their reliability takes advantage from the large image stack available, including 352 and 349 acquisitions along the ascending orbit and over the descending track respectively, and covering six years with an average revisit time of the area equal to six days after the introduction of the Sentinel-1 B satellite in September 2016. Mean displacement velocity maps estimated along the satellite LoS are shown in Fig. 3, where the sections a and b correspond to the results retrieved along the ascending and descending orbits, respectively. Both maps provide clear evidence of the location and extent of the settling area, confirming that it is mainly confined in the north-western sector of the old town, limited by Via dei Martiri di via Fani, Largo Quattro Novembre and the north part of Via Vitalia. The landslide involves an area of about 9000 m2 . Mean

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Fig. 3. PS obtained on the Chieuti area (both ascending (a) and descending (b) orbits) by the S1 satellites between April 2015 and November 2021

displacement rates away from the sensor, estimated along the LoS, range from millimeter to centimeter per year, with a maximum of −13 mm/year along the ascending orbit, and −15 mm/year along the descending orbit. Differential movements potentially harmful for the structures have been detected by setting a threshold on the coherence and velocity values on the PS map obtained along the descending track. A first classification allowed to highlight the areas characterized by the higher motion rates by selecting the PS according to the parameters listed below: • coherence ≥ 0.8 • velocity along the LoS (V LoS) ≤ −9 mm/year A close inspection of the velocity map in Fig. 4 reveals sectors characterized by different displacement velocities (A, B and C, D, emphasized in the red and orange squares). The A and B areas (dots located on the southern and northern part of Via dei Martiri di Via Fani respectively) are location of the highest mean displacement rate (−13 ÷ −14 mm/y). A lower speed was detected for C and D sectors, underlining the presence of differential movements along the Martiri di via Fani axis (Table 1). With the aim of confirming the extent and the magnitude of the instability, a very preliminary analysis of the dataset available via EGMS has been performed. The displacement map displayed in Fig. 5, even referring to a slightly different time span (February 2015 to December 2021), completely agree with the results obtained from the independent processing. The presence of differential motions is also confirmed, as evidenced by PS evidenced in the white squares in Fig. 4.

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Table 1. Cluster of PS selected by the coherence value and displacement velocity. A

B

C

D

Mean coherence

0.8

0.8

0.9

0.9

Mean V LoS (mm/year)

−14

−13

−10

−9

Fig. 4. Areas showing differential ground motions over the 2015–2021 period.

5 Discussion In this work, a C-band SAR image stack, acquired from April 2015 to November 2021 by the S1 satellite mission has been investigated to highlight the effect of the landslide phenomena affecting the western slope and part of the urban area of the town of Chieuti. The study of the retrieved velocity displacement maps confirmed the presence of a still on-going process located in the north-western sector of the town. Although the first evidence of this critical occurrence dates to the last decades of 19th century, the backanalysis performed over the last six years of SAR acquisitions permitted to better delimit the portion of the built-up area (about 9000 m2 ) affected by the instability and quantify the displacements and velocities suffered by the structures in the period considered. The analyses, which mainly focused on the zone overlooking the slope and the retaining wall carrying Via dei Martiri di Via Fani, allowed the identification of sectors characterized

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Fig. 5. Displacement map of the Chieuti area (both orbits are displayed) produced by the EGMS, between February 2015 and December 2021. White squares enclose PS characterized by higher displacement rates.

by different displacement rates, ranging from 9 to 14 mm/year along the LoS on the descending track, thus evidencing possible risk for the investigated structures.

6 Conclusions European Land Monitoring Services are acquiring an always increasing importance in supporting spatial planning. EGMS, in particular, could represent a fundamental tool in areas affected by landslide phenomena, as showed by the analysis of the S1 SAR dataset, suggesting a permanent displacement rate trend. A preliminary comparison with the data provided by the EGMS, indeed, fully confirms the location and the magnitude of the instability. As this work is framed in a broader project aimed at diagnosing the causes of the mechanism generating the instability phenomenon affecting the slope, to select the better

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strategy to mitigate the instability effects, the findings will be integrated in a joint analysis of geotechnical and geological data, along with deep displacement data, acq, IOPèired by means of inclinometric monitoring. Furthermore, the displacement data presented in this paper will be of reference for comparison with numerical predictions resulting from the three-dimensional modeling of the stress-strain equilibrium of the hillslope evolving with time under the external actions (e.g. climatic conditions). Obtained outcomes will help the Government Commissioner to implement the proper mitigation actions and, hopefully, generate a territorial management prototype for tackling potentially critical occurrences. Furthermore, thanks to the future availability of a comprehensive dataset including geomatics, geotechnical and geological data and information, the Chieuti case history could be eligible to become an open-air laboratory for all the scientific community interested in studying instability phenomena. Acknowledgments. This research has been conducted under the agreement between the DICATECh and Government Commissioner for the environmental risk of Apulia. Copernicus Land Monitoring Service products and services were produced with funding by the European Union.

References 1. Trigila, A., Iadanza, C., Bussettini, M., Lastoria, B.: Dissesto idrogeologico in Italia: pericolosità e indicatori di rischio - Edizione 2018 (2018) 2. Krishnan, A., George, G.: Spatial Planning for Flood and Landslide: A Case of Nilambur (2021) 3. Andersson-Sköld, Y., Bergman, R., Johansson, M., Persson, E., Nyberg, L.: Landslide risk management - A brief overview and example from Sweden of current situation and climate change. Int. J. Disaster Risk Reduction 3 (2013). https://doi.org/10.1016/j.ijdrr.2012.11.002 4. Esposito, D., Cantatore, E., Sonnessa, A.: A Multi Risk Analysis for the Planning, Management and Retrofit of Cultural Heritage in Historic Urban Districts. (2021). https://doi.org/10. 1007/978-3-030-68824-0_61 5. Crespi, M., Giannone, F., Marsella, M., Sonnessa, A.: Automated geomatic system for monitoring historical buildings during tunneling in Roma, Italy. In: Life-Cycle and Sustainability of Civil Infrastructure Systems - Proceedings of the 3rd International Symposium on Life-Cycle Civil Engineering, IALCCE 2012 (2012) 6. de Luna, R.M.R., Garnés, S.J. dos A., Cabral, J.J. da S.P., dos Santos, S.M.: Groundwater overexploitation and soil subsidence monitoring on Recife plain (Brazil). Natural Hazards 86 (2017). https://doi.org/10.1007/s11069-017-2749-y 7. Sonnessa, A., et al.: Integration of multi-sensor MTInSAR and ground-based geomatic data for the analysis of non-linear displacements affecting the urban area of Chieuti, Italy. Int. J. Applied Earth Observ. Geoinfo. 117 (2023). https://doi.org/10.1016/j.jag.2023.103194 8. Scifoni, S., et al.: On the joint exploitation of long-term DInSAR time series and geological information for the investigation of ground settlements in the town of Roma (Italy). Remote Sens Environ 182 (2016). https://doi.org/10.1016/j.rse.2016.04.017 9. Sonnessa, A., Tarantino, E.: Using GNSS Observation for Mitigating the Impact of SODs and RODs on the Built Environment – Introducing the New SNIK Continuously Operating Reference Station and Its Applications (2021). https://doi.org/10.1007/978-3-030-87007-2_8

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10. Bovenga, F., et al.: Assessing the Potential of Long, Multi-Temporal SAR Interferometry Time Series for Slope Instability Monitoring: Two Case Studies in Southern Italy. Remote Sens (Basel) 14 (2022). https://doi.org/10.3390/rs14071677 11. Dong, J., et al.: Tri-decadal evolution of land subsidence in the Beijing Plain revealed by multi-epoch satellite InSAR observations. Remote Sens Environ 286 (2023). https://doi.org/ 10.1016/j.rse.2022.113446 12. Crosetto, M., Monserrat, O., Cuevas-González, M., Devanthéry, N., Crippa, B.: +èersistent Scatterer Interferometry: A review (2016). https://doi.org/10.1016/j.isprsjprs.2015.10.011 13. ESA: Copernicus Programme, https://www.copernicus.eu/en, last accessed 21 June 2023 14. ESA: EGMS, last accessed 21 June 2023 15. Crosetto, M., et al.: The evolution of wide-area DInSAR: From regional and national services to the European ground motion service (2020). https://doi.org/10.3390/RS12122043 16. Festa, D., et al.: Nation-wide mapping and classification of ground deformation phenomena through the spatial clustering of P-SBAS InSAR measurements: Italy case study. ISPRS J. Photogra. Remote Sensing 189 (2022). https://doi.org/10.1016/j.isprsjprs.2022.04.022 17. Pereira, S., et al.: A landslide risk index for municipal land use planning in Portugal. Science of the Total Environment 735 (2020). https://doi.org/10.1016/j.scitotenv.2020.139463 18. Agenzia per la Coesione Territoriale: Strategia Nazionale Aree Interne, https://www.agenzi acoesione.gov.it/strategia-nazionale-aree-interne/, last accessed 21 June 2023 19. Franceschetti, G., Lanari, R.: Synthetic aperture radar processing (2018). https://doi.org/10. 1201/9780203737484 20. Ferretti, A., Prati, C., Rocca, F.: Permanent scatterers in SAR interferometry. IEEE Trans. Geosci. Remote Sensing 39 (2001). https://doi.org/10.1109/36.898661 21. ESA: IREA-CNR: European Ground Motion Service (EU-GMS) A proposed Copernicus service element (2017) 22. ESA: EGMS Explorer, https://egms.land.copernicus.eu/, last accessed 21 June 2023

Geodesign for Informed Collaborative Spatial Planning and Design

Geodesign as a Supplementary Tool to Strategic Environmental Assessment Luanita Snyman-van der Walt(B) Council for Scientific and Industrial Research, Stellenbosch 7600, South Africa [email protected]

Abstract. Strategic Environmental Assessment (SEA) is applied to inform decisions on sustainable development but may be limited in its mechanisms for unlocking the potential spatial information, and facilitating actual and effective collaborative planning and decision-making. Geodesign has been highlighted as a concept, workflow and tool that may address some of the shortcomings of SEA. In South Africa SEA is widely used to inform decisions on sustainable development. However, there are no examples of the explicit use of geodesign approaches to support decision-making in this context. Furthermore, although geodesign has been identified and explored as a tool to enhance SEA, it has not yet been empirically evaluated against SEA performance criteria. This research aimed to pilot a geodesign workshop and evaluate its potential as a supplementary tool to SEA, based on a South African case study. An online pilot geodesign workshop was executed as an SEA scoping phase activity for the Saldanha Bay Local Municipality of South Africa. The workshop demonstrated that implementing geodesign approaches in the scoping phase of SEA has the potential to enhance SEA performance by facilitating more Focused, Integrated, Iterative, Participative, and Accountable workflows and outputs. Workshop participants perceived geodesign as a potentially useful tool for SEA, as well as for other environmental management and planning tools. Concerns were raised around the veracity of local knowledge contributions and the general accessibility of digital geodesign tools in under-resourced communities and countries. Keywords: Geodesign · Strategic Environmental Assessment · Geographic Information Systems · Geodesignhub · Performance criteria · Participatory planning

1 Introduction Strategic Environmental Assessment (SEA) integrates spatial and non-spatial concepts of social, economic, and environmental sustainability – often informed by stakeholder participation – into strategic-level planning and decision-making [1–3]. The process aims to proactively assess potential impacts on the environment (biophysical, social and economic), and has successfully been applied to support large-scale and complex sustainable development issues in South Africa (e.g. [4–7]). Spatial data and Geographic Information Systems (GIS) are inherent to SEA processes, most commonly as a specialist tool to visualise, describe, model and evaluate receiving environments [8]. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 59–67, 2024. https://doi.org/10.1007/978-3-031-54118-6_6

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Although SEA is broadly accepted as a flexible and adaptable process with the potential to foster innovation [9, 10], the power of spatial data in SEA can be hindered by ill-suited GIS tools and workflows [10]. Furthermore, South African SEA has been found to often focus mainly on situation analysis (collating and presenting existing information), therefore lacking value-driven and innovative approaches [11]. Geodesign has been highlighted as a pioneering tool to address some of the pitfalls in SEA [10, 12]. Broadly, geodesign is a mostly digital planning approach that provides a collaborative platform for technical, political and social stakeholders to interact with geospatial knowledge and technologies. This enables participants to iteratively share knowledge, propose spatial interventions, consider the impacts and implications of their proposals, and ultimately make negotiated and collective decisions on a final design – a shared vision of the future of a place [10, 13, 14]. Whilst SEA is widely applied in South Africa, there are no examples of the explicit use of geodesign approaches to support decision-making in the context of South African SEA. Furthermore, although geodesign has been identified and explored as a tool that holds potential to enhance SEA (e.g. [10, 12, 15, 16]), it had not been empirically evaluated against SEA performance criteria. This research aimed to pilot a geodesign workshop and evaluate its potential as a supplementary tool to SEA, based on a South African case study.

2 Methodology In 2019 an SEA was executed for the Saldanha Bay Municipality (SBM), located in the Western Cape province of South Africa [17]. This provided a case study for evaluating the potential of geodesign as a supplementary tool to SEA. The SBM SEA was conducted through the lens of natural capital and ecosystem services underpinning human wellbeing. Status quo environmental descriptions, identified strategic issues / needs, and spatial sensitivity models of natural capital features developed in the SBM SEA were available as initial input models for the geodesign process. 2.1 Geodesign Tool The selected tool for the geodesign workshop was Geodesignhub (https://www.geo designhub.com/), including its Survey capability (https://survey.geodesignhub.com/). Geodesignhub is a digital negotiation platform aimed at managing complex spatially explicit projects efficiently, transparently and in a highly participatory way, whilst Geodesignhub Survey enables the collection of respondents’ spatial knowledge about or ideas for a place using a simplistic interface [18]. 2.2 Participants and Their Role A total of eleven (11) participants took part in the geodesign workshop. Participants were recruited based on their previous experience with SEA, environmental spatial planning and decision-making, and / or involvement in the 2019 SBM SEA. Participants were affiliated with the policy, planning and environmental conservation spheres within

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government (at national and provincial levels), as well as consultancies and research institutes within the environmental assessment industry. Participants were divided into three interest groups (‘design teams’), each with four to five participants: 1. Socio-economic development – concerned with promoting socio-economic development, job creation and revenue generation, and any projects / policies that will facilitate this goal. 2. Natural capital management – concerned with environmental protection and management, and any projects / policies that will facilitate this goal. 3. Government – concerned with ensuring sustainable development, the protection and management of socio-economic and natural capital, quality and inclusive living environments and any projects / policies that will facilitate this goal. The participants were assigned three main geodesign tasks to complete (Fig. 1): 1. Augment existing data with local knowledge to describe the status quo of environmental pressures undermining the natural capital and ecosystem services of the SBM; 2. Propose spatially explicit projects and policies that would advance their team interests; and 3. Design a spatial future for the SBM that matches their interests, followed by an inspection of the potential conflicts and synergies between the different design teams’ visions for the future.

2.3 Data Collection Data for the research were collected through participant questionnaires and researcher observations that were structured according to principles and criteria that guide good quality and effective SEA: Integrated, Sustainability-led & Strategic, Focussed, Accountable, Participative, Iterative, Precautionary & Adaptive, Future-thinking, and Limit-setting [2, 19]. Questionnaires aimed to glean participants’ perception and experience of the geodesign workshop, geodesign in general, and its potential utility to enhance SEA. The questionnaires consisted of 28 statements linked to SEA performance criteria. For example, “The baseline information and local knowledge contributions provided me with a sufficient understanding of the SBM”, linked to the Integrated principle; “I am able to propose and identify ideas for the SBM spatial future that represent sustainable development options” reflected the Sustainability-led & Strategic principle, and “I was better able to understand and reconcile the ideas of those who have different interests from mine” linked to the Participative principle. The questionnaires were developed as 5point Likert scale surveys (1: strongly disagree; 2: disagree; 3: undecided; 4: agree; 5: strongly agree). Researcher observations of the workshop process and outputs aimed to record general participation and interaction between participants, participant experience with the geodesign process and outcomes, and the quality of the outputs generated during each geodesign task. For example, participant attitude to the local knowledge contributions

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Fig. 1. Summary of the SBM geodesign workshop process, showing the inputs, tasks, and outputs of each day’s activities.

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reflected the Accountable principle of SEA, interaction between participants was linked to the Participative, Iterative and Accountable principles, and whether participants provided logical, informed and clearly named contributions demonstrated the Focussed principle.

3 Results and Discussion The geodesign workshop for the SBM was successfully executed over three half-day virtual sessions with eleven (11) participants. At the inception of the workshop, the participants’ previous exposure to geodesign and participatory mapping was queried. Most participants reported having heard of geodesign or taking part in participatory mapping exercises. Of the latter, the majority have taken part in participatory mapping predominantly for scoping or assessment phases of SEA. These participatory mapping exercises were predominantly through annotating hard copy maps (direct participation) or via a GIS technician capturing inputs digitally (indirect participation). Participants reported being interested in working directly with the online geodesign tools, whilst some expressed concerns about the level of skill required to effectively participate in the digital geodesign workshop. Based on the questionnaire results, the participants affirmed the potential of geodesign to enhance SEA performance (Fig. 2).

Fig. 2. Mean score of the questionnaires indicating participant perception of the potential of geodesign to enhance SEA, across all tasks, summarised per selected SEA performance criteria. N = 11, 5-point Likert scale: 1 = strongly disagree; 2 = disagree; 3 = undecided; 4 = agree; 5 = strongly agree.

The general utility of geodesign as a supplementary tool for SEA was demonstrated in the way in which participants worked with the geodesign tools and executed the

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geodesign tasks. Participants could make their inputs, after a short demonstration, without requiring significant additional assistance. The geometry of participant contributions varied from being quite detailed and precise, to rather rough with potentially problematic topology. Crude contributions would require some conditioning if the data were to be used for subsequent spatial analyses. More precise inputs may indicate the participant’s confidence in the spatial extent of the input, as well as better use of basemaps, zoom and pan functions. Geodesign showed promise in focussing SEA by providing clear tasks, and relatively simplistic tools and information (basemaps and design aids) as reference for inputs. Through tiering information across multiple geographic scales, policies, and projects, as well as generating and making information available as design aids for subsequent tasks, geodesign showed the potential to enhance the integrative and iterative nature of SEA. However, some shortfalls were identified when observing the participants performing the geodesign tasks and during general discussions with the participants. Geodesign may not necessarily be seen to contribute to the accountability of SEA due to a lack of trust in participant-generated information – often a concern in data gathered through Participatory GIS and citizen science processes [20, 21]. For example, participants noted that: “Geodesign is suited to the scoping phase [of SEA] mostly in terms of knowledge gathering (local and specialist) but additional processes to verify information would need to be considered during the scoping phase as well.” Interestingly, the communication between participants was also less effective than expected, thus not fully demonstrating the potential role of geodesign in enhancing participation in SEA. This could, however, be attributed to the workshop being conducted virtually. Communication and interaction were more pronounced during Tasks 2 and 3 where design teams were divided into smaller break-out rooms. However, participants commented favourably on geodesign as: “Very useful for engaging with different perspectives - both people and from a discipline perspective.” Participants further noted that: “Geodesign as part of the SEA Process would be valuable, especially using targeted groups and audiences, such as Expert Reference Groups and Specialist Workshops”. In terms of outputs, geodesign furthermore showed promise to contribute to the focus, iteration, and integration of SEA processes based on the diversity and spatial distribution of contributions made by participants. All contributions were logical with minor topological issues. However, participants had difficulty with naming their inputs with enough detail (Task 1 and 2) within the character constraint limits imposed by the Geodesignhub Survey tool and felt that:

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“The diagram descriptions were sometimes a bit limiting, for example, we struggled in trying to understand what was meant by a specific selection and/or why a certain area was indicated.” Overall, participants seemed positive about the potential of geodesign, not only for SEA, but also for other integrated environmental management instruments. One participant noted: “I enjoyed the inter-activeness of the session and people. The [geodesign] tool looks like it can be most useful for our work in the coastal and biodiversity spaces as it relates to SEA and Environmental Management Framework development”

4 Conclusion Geodesign was found to be a fit-for-purpose approach to engage with stakeholders and people of the place, collect local knowledge, develop desired future state scenarios, and identify potential synergies / conflicts between various interest groups during SEA scoping phases. Ultimately, geodesign activities in SEA may contribute to more transparent and collaborative planning and decision-making on sustainable development issues. The workshop demonstrated that implementing geodesign approaches in the scoping phase of SEA has the potential to enhance SEA performance by facilitating more Focussed, Integrated, Iterative, Participative, and Accountable workflows and outputs. Participants perceived geodesign as a potentially useful tool for SEA, as well as other environmental management and planning tools. Based on participant feedback and researcher observations, geodesign demonstrated the potential to address some of pitfalls of SEA and enhance procedural effectiveness of SEA through: 1) better integration of GIS into SEA (e.g. improving on analogue or nonreciprocal participatory mapping traditionally utilised in South African SEA); 2) facilitating the inclusion of values in SEA (e.g. capturing participant interests through spatial proposals and designs); and 3) providing a highly collaborative, adaptive and interesting avenue for stakeholder engagement and participation in SEA. Two key constraints of geodesign for South African SEA were identified during the research that may limit the potential of geodesign to enhance the legitimacy of SEA. Firstly, stakeholder trust in participant-generated information (e.g. local knowledge inputs). It is recommended that, when geodesign workflows are implemented in SEA, appropriate information validation tasks are incorporated in the SEA workplan to verify participant-generated data. In this regard, it is also important to convey clearly to participants and stakeholders when and how geodesign is used in SEA, and how inputs will be utilised moving forward in the SEA and decision-making processes. Conflict of interest may also be mistaken for trust in participant contributions, in which case subsequent in-depth deliberation, negotiation and conflict resolution would be critical for producing legitimate geodesign outputs to support decision-making. Secondly, access to digital tools and skills (e.g. access to computer hardware, internet connection, computer literacy and proficiency), especially in under-resourced communities. Accordingly, the target audience of geodesign workshops must be profiled to ensure

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that appropriate geodesign tools and workflows are used. For this research, Geodesignhub was determined as an appropriate tool for the workshop and matched the capabilities of the participants. Alternative geodesign tools and workflows may include analogue or simplified tools, different platforms (e.g. cell phone geosurveys, touch tables), dedicated conductors to capture participant inputs, and a greater focus on capacitating participants to effectively use geodesign tools. This is the first study to explicitly evaluate geodesign against selected SEA performance criteria. A limitation of this research is that the geodesign workshop was conducted fully online, which may have restricted communication between participants, to some extent, and thus skewed the findings of the potential of geodesign to enhance participation in SEA. However, this did not limit the selection of participants for the SBM workshop and participants were able to take part in the workshop regardless of their location. The research was further limited by the small number of participants involved and the results can therefore not be considered definitive. Further research is thus needed to establish a comprehensive understanding of the role geodesign in enhancing SEA. Whilst the research demonstrated that geodesign is a promising approach for SEA scoping phase, using targeted steps of geodesign within an online workshop format. It is recommended that a full geodesign process, with negotiation and final decision outcomes, be tested for all phases of SEA and in various formats. Furthermore, it is suggested that geodesign implemented in SEA be monitored for evidence of success / enhanced substantive SEA effectiveness (i.e. the impact of real decisions for sustainable development based on SEA outcomes). Additionally, there is an opportunity to test the utility of geodesign for other integrated environmental management instruments and spatial planning approaches, to establish what the specific requirements of each process in terms of geodesign might be. This will presumably also further demonstrate the flexibility of geodesign workflows. Acknowledgements. This research was conducted in fulfillment of an MSc Geographic Information Sciences degree under the supervision of Dr. Ron Janssen, at the Spatial Information Laboratory (SPINLab), School of Business and Economics, Vrije Universiteit Amsterdam, The Netherlands.

References 1. Sadler, B., Verheem, R.: Strategic Environmental Assessment: Status. Challenges and Future Directions, The Hague (1996) 2. Department of Environmental Affairs and Tourism: Strategic Environmental Assessment in South Africa. Guideline Document. Department of Environmental Affairs and Tourism (DEAT), Pretoria (2000) 3. Sadler, B.: A framework approach to strategic environmental assessment: aims, principles and elements of good practice. In: Dusik, J. (ed.) Proceedings of International Workshop on Public Participation and Health Aspects in Strategic Environmental Assessment, pp. 11– 24. The Regional Environmental Center for Central and Eastern Europe (REC), Szentendre (2001) 4. Department of Environmental Affairs: Phase 2 Strategic Environmental Assessment for wind and solar photovoltaic energy in South Africa. Pretoria (2019)

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5. Department of Environmental Affairs: Strategic Environmental Assessment for wind and solar photovoltaic energy in South Africa. Pretoria (2015) 6. Department of Environmental Affairs: Strategic Environmental Assessment for electricity grid infrastructure in South Africa. Pretoria (2016) 7. Scholes, R.J., Lochner, P., Schreiner, G.O., et al.: Shale Gas Development in the Central Karoo: A Scientific Assessment of the Opportunities and Risks. CSIR, Pretoria (2016) 8. González Del Campo, A.: GIS in environmental assessment: A review of current issues and future needs. J. Environm. Assess. Policy and Manage. 14 (2012). https://doi.org/10.1142/ S146433321250007X 9. Retief, F.: A performance evaluation of strategic environmental assessment (SEA) processes within the South African context. Environ. Impact Assess. Rev. 27, 84–100 (2007). https:// doi.org/10.1016/j.eiar.2006.08.002 10. Campagna, M., Matta, A.: Geoinformation technologies in sustainable spatial planning: a Geodesign approach to local land-use planning. In: Proceedings of SPIE 9299. Paphos, p. 92290T (2014) 11. Retief, F., Jones, C., Jay, S.: The emperor’s new clothes — Reflections on strategic environmental assessment (SEA) practice in South Africa. Environ. Impact Assess. Rev. 28, 504–514 (2008). https://doi.org/10.1016/j.eiar.2007.07.004 12. Campagna, M., Di Cesare, E.A., Matta, A., Serra, M.: Bridging the gap between strategic environmental assessment and planning: A geodesign perspective. Environmental Information Systems: Concepts, Methodologies, Tools, and Applications 2, 569–589 (2018). https://doi. org/10.4018/978-1-5225-7033-2.ch024 13. Steinitz, C.: A framework for geodesign: changing geography by design. Esri, Redlands (2012) 14. Lee, D.J., Dias, E., Scholten, H.J.: Introduction to geodesign developments in Europe. In: Lee, D.J., Dias, E., Scholten, H.J. (eds.) Geodesign by integrating design and geospatial sciences, pp. 3–9. Springer (2014) 15. Campagna, M.: Geodesign from theory to practice: From metaplanning to 2nd generation of planning support systems. Journal of Land Use, Mobility and Environment (Special issue) 8th International Conference INPUT, June 2014 (2014) 16. Di Cesare, E.A., Floris, R., Cocco, C., Campagna, M.: Linking knowledge to action with geodesign. In: Papa, R., et al. (ed.) Green Energy and Technology, pp. 179–201 (2018) 17. Department of Environmental Affairs and Development Planning: Risk and Resilience Assessment of Natural Capital in the Greater Saldanha Bay Municipality: A Navigational Tool for Strategic-Level Decision-Making. Western Cape Department of Environmental Affairs and Development Planning (DEA&DP) (2019) 18. Geodesignhub: Software for negotiations & mediation over the future of a place. In: https:// www.geodesignhub.com/ (2021) 19. International Association for Impact Assessment: Strategic Environmental Assessment: Performance Criteria (2002) 20. Jordan, R.C., Brooks, W.R., Howe, D.V., Ehrenfeld, J.G.: Evaluating the performance of volunteers in mapping invasive plants in public conservation lands. Environ. Manage. 49, 425–434 (2012) 21. Tang, Z., Liu, T.: Evaluating Internet-based public participation GIS (PPGIS) and volunteered geographic information (VGI) in environmental planning and management. J. Environ. Planning Manage. 59, 1073–1090 (2016). https://doi.org/10.1080/09640568.2015.1054477

Geovisualization and Geodesign in a Framework for the Evaluation of Landscape Units as a Basis for the Sustainable Planning of the Quadrilátero Ferrífero, Brazil Ana Clara Mourão Moura1(B) , Christian Rezende Freitas2 , Alfio Conti1 , Ítalo Sousa De Sena3 , Nicole Andrade Rocha4 , Danilo M. Magalhães5 , and Gustavo A. T. Martinez1 1 School of Architecture, Geoprocessing Laboratory, Federal University of Minas Gerais

(UFMG), Rua Paraíba 697, Belo Horizonte, Brazil [email protected] 2 GE21 Geotechnologies, Av. Afonso Pena 3130, Belo Horizonte, Brazil 3 University College Dublin, Dublin, Ireland 4 Granbery Methodist College, Rua Sampaio 300, Juiz de Fora, Brazil 5 Paulista State University (UNESP), Avenida 24 A 1515, Rio Claro, Brazil

Abstract. The paper proposes a methodological framework for the definition and characterization of Landscape Units for the use in regional planning, emphasizing landscape as a new planning category in Brazil. The case study is the Iron Quadrangle, an area with distinguished cultural value due to its role in the formation of Brazilian urban network during the Gold Cycle, as well as the more recent Iron Ore Cycle. It’s an area of conflicting interests, as it presents, in the same place, remarkable environmental resources, urban growth and mining exploitation. Through a procedure of systemic approach, based on decomposition, composition and recomposition, the methodological process produced significant information on the area, using geovisualization resources. It applied geospatial technologies on drone-captured images, Spatial Data Infrastructure organized as a Web-GIS and a web-based Geodesign platform to the co-creation of ideas by shared decision. A group of experts was divided in the axis of urban landscape, rural landscape, environmental landscape, geomorphological landscape and geosystemic landscape, to construct qualified data and analysis and to present spatial units according to each thematic. A geodesign workshop was held to share decisions about the integration of the previous classifications, to define final Landscape Units and Landscape Scopes (20 zonings divided into 109 parcels). In a second Geodesign workshop the participants co-created ideas to each area, as a principle of Landscape Plan. Keywords: Geodesign · Territorial Planning · Regional Planning · Geospatial Technologies · Isometric Perspective · Drone images

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 68–79, 2024. https://doi.org/10.1007/978-3-031-54118-6_7

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1 Introduction Brazil faces a significant lack of processes and training about the managing and planning of landscapes. It lacks specific norms for the protection and doesn’t apply methods for the identification, representation, analysis, simulation, and definition of planning units in landscape studies. There are rules and laws about urban master plans (when to do, how to do, the main steps to be constructed) and laws about environmental protection (conservation units, legal reserve, non-buildable and protection areas), but there are no references or norms at the scale of landscape planning. This paper is a contribution about how to apply Geodesign and Geovisualization to construct a Landscape Plan, based on references about Landscape Units and Landscape Scopes. The importance of discussing methods to plan the landscape territory was made clear in face of two major environmental disasters involving ruptured dams in the Iron Quadrangle, both used for mining operations. The accidents destroyed the landscapes of Mariana (where 19 were found dead) and Brumadinho (270 casualties). Faced with the need to propose a plan for restructuring the area, it was noted that there was nowhere to start from, since there were not studies regarding landscape units, nor environmental, social, and cultural values or invariant factors (notable elements). Without a characterization of the previous landscape, before the disasters, it is very hard to create a proposal for the future, particularly when it comes to recovering the area. This is an important contribution of this paper: Brazilian Master Plans area limited to urban areas or even to municipal areas, but never in the scale of Landscape Plans. There is no experience or even political intention to think on a regional scale that can cover a larger area, interconnected by transformed and protected landscapes, considering cultural and environmental values. To work based on that, the first step to do it is the definition of landscape units. Regarding landscape heritage, these laws and processes are limited to an instrument called “Seal of Brazilian Cultural Landscapes”, proposed by the Institute for National Historic and Artistic Heritage in 2009. But it focuses on landscapes with extraordinary value, without tackling the issue of ordinary landscapes, which are part of everyday life, but nonetheless have local cultural value and are significant as planning units. Geographical sciences present the concept of landscapes with the goal of understanding the arrangement of elements and their relations, captured through contemplation, which in turn represent the relationship between humans and space. These principles are already established in European countries, that can manage their landscapes, notwithstanding the many transformations observed from the XX century until present days, particularly in the cases of France (unités de paysage) and Italy (unità di paesaggio and ambito paesaggistico). Italy stands out because it takes landscape into account since the late 1930’s, through the Law for the Preservation of Natural Beauty (Italy 1939), and the 1947 Italian Constitution, that defined landscape management as a duty of the State. In the context of the 1960’s, the work of Sereni (1961) proposed that a landscape is beautiful when it is well cultivated, which equates to treating it as a product of the interaction between humans and their environment, seen as a support and resource for maintaining cultural and productive activities. However, it was only from 1985 onwards, due to the mandatory establishment of Regional Landscape Management Plans, as part of the Galasso

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Law, that regional territorial planning became institutionalized, placing landscape as the central factor in environmental-territorial analysis (Italy 1985). In Italy, the creation of a Regional Territorial Landscape Plan (Piano Territoriale Paesistico Regionale or PTPR) involves an analytical diagnosis, though it does not necessarily contemplate goals for future transformation, an issue that will be tackled later through the studies of “landscape scopes”. These actions are based on the 2000 European Landscape Convention, which argues in defense of this analytical unit, in consideration of the need to adopt specific measures towards the protection, management and organization of landscapes as a common good. In that sense, definition of landscape units is the first and necessary step, that with the evolution of planning is followed by the studies about landscape scopes. In Brazil, there are no rules for landscape planning, or laws that regulate land use and occupation according to landscape units or scopes. For this incorporation to take place, it would be necessary to define landscape units as planning references. There are laws and plans to urban planning and to define environmental protection, but none about landscape plans. With that in mind, this research presents a methodological proposal for the definition of landscape units, presenting steps supported by geovisualization and geodesign. Geovisualization is an effort towards the representation of an abstraction of reality, with the goal of simplifying a complex set of information, and to place the focus on processes, rather than hard facts (MacEachren 2001). Batty (2007) reflects on the historical process of geospatial technology and defines two main lines of interest on the subject: “We identify two main drivers—the move to visualization which dominates our very interaction with the computer and the move to disseminate and share software data and ideas across the web”. In our framework we used both: geovisualization and web-based spatial data infrastructure in geodesign workshops. Geodesign is a shared planning method, which means planning “with” and “for” geography. Once the area and its potentials and vulnerabilities are clearly represented, the participants collectively develop ideas that correspond to a master plan for an area, in shared decision workshops, projecting alternative futures. The principles are collective understanding of the problem, proposition of ideas, discussion of the impacts, negotiation, and decision (Dangermond 2009; Ervin 2011; Flaxman 2010; Miller 2012; Steinitz 2012). In this investigation Geovisualization and Geodesign are applied in decision-making process, based on spatial integration of variables by Combinatorial Analysis. This means that initially a broad and complete representation of the characteristics of the place is produced, and by processes of combinatorial analysis of these initial maps, landscapes units are composed according to 5 axes: Rural, Urban, Environmental, Geomorphological and Geosystemic approaches. Combinatorial Analysis is a procedure of map algebra that combines layers to identify possible existing compositions. It is a procedure that recognizes categories of possible spatial combinations (Moura, 2021). For decision-making at the stage of integrations of landscape units, geovisualization products are designed to better inform the expected syntheses. They are based on synthetic sketches and images of drone capture, composing geo views. Supported by geovisualization, decisions are made for the delimitation of

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Landscape Units along the 5 axes and for the Landscape Scopes (sub-units) and the final Landscape Units, the so-called Structuring Landscape Units. Once the Landscape Units are defined, in Geodesign workshops the co-creation of ideas for each unit is carried out to suggest the main uses, according to vulnerabilities and potentialities, for each of the parcels. Scientific innovation is in the support of geovisualization as a support for the construction of opinions, and geodesign workshops for decision making. Geovisualization was elaborated by drone capture and representation in oblique perspective of the Landscape Units. The organization of data and maps was through the structure of a Spatial Data Infrastructure (SDI) and the full interoperability of the use of resources, through the Brazilian Geodesign platform, GISColab. 1.1 The Case Study: Quadrilátero Ferrífero (Iron Quadrangle) The Iron Quadrangle is the most relevant area of cultural and historical heritage of the state of Minas Gerais, not only due to its historical cities and works of art, but also because of its notorious landscape, natural resources and environments that were transformed by mining enterprises. The first settlers arrived in Minas Gerais guided by the mountains of the Iron Quadrangle, where mineral riches were discovered, and they founded first cities, an important area of Brazilian historical heritage (Fig. 1). The Iron Quadrangle is an area with relevant cultural and environmental heritage, made up of unique architectural works, water supplies and landscapes of reference. There are fragments of the Atlantic Forest and Rupestrian Field, with significant natural landscapes, composed of the mountains that are cognitively associated with Minas Gerais. But is also an area of mining activities and urban sprawl pressure.

Fig. 1. Iron Quadrangle—altimetry, geological formation, urban land use and municipalities, 2021. Source: Alos Palsar 2020, IBGE, 2020, CPRM, 2020. Source: the authors, 2021.

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2 Methodology According to Moura (2020), spatial representations and studies are based on analyses and syntheses, in which variables are manipulated to respond to the main phenomena, occurrences and characteristics of a given site (McHarg 1969). Analytical investigations require the decomposition of reality into its most relevant variables, to observe each theme in detail (Chorley and Hagget 1967). Synthetic investigations require the composition of variables into interpretative visions that respond to real scenarios. The modeling process, hence, involves the analysis (decomposition) and synthesis (composition) to create evaluations regarding a territory in relation to possible scenarios (recompositing). Spatial data modeling, in such sense, follows the principles of the systemic approach (Bertalanffy 1968). The framework applied includes the stages of decomposing reality into its main variable components, followed by composition of integrated syntheses for a better understanding of the existing relations. Then, finally, there is the recomposition into Landscape Units. The decomposition produces the data, composition stage produces information and recompositing stage produces knowledge about the area. (Fig. 2).

Fig. 2. Key logic stages. Source: The authors, 2021.

The study produced 65 initial maps, decomposing the region according to variables of interest. Then they were composed into 28 interpretive maps that indicate potentialities, vulnerabilities and spatial arrangements. The integrations considered the 5 axes: urban, rural, environmental, geomorphological and geosystemic approaches. Drone images were captured and sketches were elaborated to provide geovisualization and to synthesize the essence of the landscape units according to the 5 axes of studies. Once the division of the spatial units according to 5 axes was done, there was the challenge to combine them, as recomposition, to finally present the Landscape Units. All the steps to arrive to Landscape Units were based on production of maps, combination of maps according to main analysis, definition of spatial units based on the Combinatorial Analysis and negotiation of the final polygons to each spatial unit on geodesign. Once the polygons of Landscapes Units were negotiated, a second geodesign workshops was held on to the proposition of ideas to each area.

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As state-of-the-design, the study begins with step 1, the decomposition of variables, starting from land use land cover map, separating urban areas. The urban areas were classified according to morphology, separating regular or irregular pathways. Using data about the volume of the buildings the areas were separated according to the predominant height. Finally, using spatial information about historical architecture the areas were classified in historic and non-historic, and the historic was separated according to the predominance of baroque, positivist/eclectic/neoclassical, and modernist. Dependency relationships between the cities were identified, due to commuting and commercialization activities. These data allowed the identification of dependency relationships between urban areas. Roads and geographic features of mountains and rivers were mapped, which resulted in the identification of geographic limitations. In the composition between the geographic limitations and the dependency relationships between urban areas, the Landscape Units of Urban Influence Areas were defined. The studies about Rural Landscape Units also followed three steps. Step 1 was the decomposition into variables: Land use and land cover map was used to extract data regarding the classes of vegetation; the data provided by the rural cadastre was used to separate agricultural systems and economic activities; and data regarding mountains and rivers were used to indicate the areas of influence for the occurrences. Step 2 was the composition of synthesis, classifying in groups according to vegetation and economic activities. Step 3 was the recomposition into Rural Landscape Units. The studies about Environmental Landscape Units considered vegetation and water resources. In the first step, that was the decomposition, land use and land cover maps were used to identify the main vegetation, represented by forest and rupestrian field. Data about water resulted in maps about the rivers and the springs. In the second step, that is the compositions, the vegetation was classified according to its robustness and metrics of Landscape Ecology. In water studies the compositions were about the concentration of springs and water channels. In third step, that is the recomposition, there were proposed the Environmental Landscape Units, according to combination of characteristics of vegetation and water. A map of geomorphological typologies was used to define Geomorphological Landscape Units, according to physical characteristics. Finally, Geosystemic Landscape Units were constructed, using all data and analysis provided by previous studies. The Geosystemic Landscape Units, according to Webber et al. (2006) and Grey (2011), identifies spatial portions where there are similar conditions of culture, knowledge, provisioning, regulating, and supporting, It was a challenge to integrate the 5 axes of landscape studies: urban, rural, environmental, geomorphological and geosystemic units. The work was held on a geodesign workshop, in which the participants received the collection of initial maps (the decomposition), plus the collection of analytical maps (the studies of composition) and also the initial synthesis (the recomposition). The goal was to arrive to a final synthesis, negotiating the limits of the polygons. In 4 meetings, the negotiations combined: (a) urban and rural limits; (b) urban + rural and environmental limits; (c) urban + rural + environmental and geomorphological limits; (d) urban + rural + environmental + geomorphological and geosystemic limits.

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Geovisualization was an important support during the workshop. According to Moura (2003) the viewing of cartographic, zenithal, or top-down projections favors the synthetic interpretation, since the elements are placed side-by-side and the representation aims to identify elements and their distributions. Azimuthal view is immersive, taking place at the height and according to the observer’s view; it is analytical because it is composed by the sum of the views which, in a synchronous process, sum up the information in an immersive experience. On the other hand, isometric visualization, in an oblique perspective, places the landscape as an object in its whole, without inducing the rationality of the azimuthal nor the sensory effect of the zenithal, but acts as a motif for observation and interpretation. The geovisualization in this study begins with a collection of maps on a webbased platform, in cartographic representation; has the support of isometric perspectives captured by drone and presents analogical representations (sketches) as interpretation of landscapes’ main characteristics. The methodological process follows the same three-step logic that produces data, information, and knowledge (Figs. 3 and 4). Once the Landscape Units and Landscape Scopes were defined, also in a geodesign workshop, the experts proposed ideas to each unit, as a first draft to a Landscape Plan to the area of Iron Quadrangle.

Fig. 3. Resources toward geovisualization. Source: the authors.

Fig. 4. Analogical sketches and drone images in isometric perspective. Source: the authors.

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3 The Development of the Case Study The process of creating Landscape Units required a broad characterization of the area, consisting of initial maps, followed by analytical maps resulted from variables integration to identify predominant characteristics. The combination of variables and the subdivision of homogeneous areas resulted in 109 sub-units, as parcels (Landscape Scopes), which were integrated into 20 Structuring Landscape Units. The logic was to decompose, compose, recompose, the main method being Combinatorial Analysis, with the support of Geovisualization. Combinatorial Analysis was used as a geoprocessing resource to identify possible feature arrangements in the area. It is a well-known process, but still very useful as logic and method. It is based on defining the main components of each map, qualitatively, by categories. Afterwards, a matrix of possible combinations is created, which are also categorized according to a description of the combination, identifying the main characteristics of interest (Moura 2020). After the combinations, in a geodesign workshop, with extensive geovisualization support, the boundaries of the polygons of Structuring Landscape Units were collectively drawn. All geodesign workshops were held on a web-based platform: GISColab, the Brazilian geodesign platform (Moura and Freitas, 2021). The workshops were attended by 9 experts in the fields of vegetation, hydrology, cultural heritage, regional planning, urban planning, geomorphology and risks, archaeological heritage. They worked in the definition of landscape units by research axis, and in the integration workshops to construct Structuring Landscape Units, and also in a final geodesign workshop to propose ideas for the Landscape Plan. The results about Urban, Rural, Environmental, Geomorphological and Geosystemic Landscape Units are presented in the following figures (Figs. 5, 6, and 7).

Fig. 5. Urban morphology, volumetry, and historic areas. Source: the authors.

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Fig. 6. Rural (a) and Environmental (b) Landscape Units. Source: the authors.

Fig. 7. Geomorphological (a) and Geosystemic (b) Landscape Units. Source: the authors.

This final map, the Structing Landscape Units, presents not only the 20 landscape units, but also the 109 landscape scopes, that are internal subdivisions, considering the interests in regional landscape plans and strategic local landscape plans (Fig. 8). During all the process, the support of geovisualization resources were used. There were classification-keys, according to the axes of urban, rural, environmental, geomorphological and geosystemic points of view. (Fig. 9).

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Fig. 8. Structuring Landscape Units. Source: the authors.

Fig. 9. Geovisualization: Analogical sketches, visual inspection by Google Maps and CBERS (Brazilian satellite), drone images, as classification-keys. Source: the authors.

With the composition of Landscape Units and Landscape Scopes, a geodesign workshop was carried out to create ideas to each polygon of the area. The participants registered vulnerabilities, potentialities and ideas about appropriate future of each unit. There also considered the subdivisions of Landscape Scopes, in the case there were specific proposal for a part of the larger unit. Using GISColab, the units’ polygons were connected to Google Forms, in which the participants wrote their ideas, more comfortably and without size limitations. GISColab web-platform is able to connect to web-based application, expanding the technological support possibilities (Fig. 10).

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Fig. 10. GISColab: the web-based interface using Google Forms. Source: the authors.

4 Discussion and Conclusion The work explores the potential of geospatial technologies. According to Peuquet and Marble (1990) these technologies have already gone through the stages of a “processoriented approach”, an “application approach” and a “toolbox approach”. Further continuing these stages, some authors defend that the most relevant contemporary contribution is the “visualization approach” (Kingston 2007; Andrienko et al. 2011). Moura (2015) defends visualization to favor the participation of agents, associated with a methodological framework to avoid the labyrinth of applications. The logic of decomposition, composition and recompositing, applied in the method based on combinatorial analysis of maps and with the support of geovisualization is a contribution to other Brazilian case studies, but also to any other countries in which the regional planning and landscape planning are still not part of a formal regulation and laws. The division in 109 scope units and 20 main units resulted from the 5 axes of analysis, in complex approach of different axes of landscape characterization. There were initially 5 areas of urban influence units, 7 rural units, 8 environmental units, 5 geomorphological units, and 16 geosystemic units, what makes 22,400 possible combinations, but the method of combining, composing and recomposing allowed to define 109 subunits and 20 main units. It is a rather effective recompositing for a region of around 150 per 150 km, in a total area of 11676 km2 , of which the urban area measures 789 km2 . It results in an average of 106 km2 per Landscape Unit, although it is necessary to note that they vary a lot in size, from 1194 km2 to 11636 km2 , due to the homogeneity and contiguity of the spatial arrangements. As a contribution to the state-of-the-art, stands out the framework based on interoperability between the participants and the interoperability of the technological resources employed. Interoperability means using shared code that favors dialogues: between machines (digital applications) and between people (a common language, allowed by geovisualization). The replicability of the executed processes is also highlighted, what is a sign of defensible and reproducible criteria. This research is a methodological contribution towards the creation of landscape units as the basis for regional and territorial planning. The public administration needs to develop plans to characterize local values, to identify potentialities, vulnerabilities and restrictions on uses, so that the state is not

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surprised by the lack of data in face of disasters, causalities or territorial transformation. In Brazil the principle of landscape unit and planning are not legally implemented yet, and this is where the contribution of the work lies, as there is significant lack of processes and training in Brazil regarding landscape management and planning. Acknowledgments. CNPq 401066/2016–9 and FAPEMIG PPM-00368–18.

References Andrienko, G., Andrienko, N., Keim, D., Maceachren, A.M., Wrobel, S.: Challenging problems of geospatial visual analytics. J. Vis. Lang. Comput. 22(4), 251–256 (2011) Batty, M.: Planning support systems: progress, predictions, and speculations on the shape of things to come. UCL. Working Papers Series. Paper 122, 1–25 (2007) Bertalanffy, L.: General System Theory. G. Braziller, New York (1968) Chorley, R., Haggett, P.: Models in Geography. Methuen, London (1967) Dangermond, J.: GIS: Designing our future. ArcNews (2009) Ervin, S.: A system for Geodesign. Keynote. Abstract, pp. 158–167 (2011) Flaxman, M.: Geodesign: Fundamental Principles and Routes Forward. Talk at GeoDesign Summit (2010) Gray, M.: Other nature: geodiversity and geosystem services. Environ. Conserv. 38(3), 271–274 (2011) Italia: Legge n. 1497 del 29 giugno 1939. Protezione delle bellezze naturali. Roma: Gazzetta Ufficiale, p 44 (1939) Italia: Legge n. 431 del 08 agosto 1985. Conversione in legge, con modificazioni, del decreto-legge 27 giugno 1985, n. 312, Roma: Gazzetta Ufficiale, p 32. (1985) Kingston, R.: Public participation in local policy decision-making: the role of web-based mapping. Cartogr. J. 44(2), 138–144 (2007) Magalhães, D.M., Moura, A.C.M.: Aerial images and three-dimensional models generated by RPA to support geovisualization in geodesign workshops. LNCS, Springer International Publishing 12252, 296–309 (2020) McHarg, I.: Design with nature. American Museum of Natural History, New York (1969) Miller, W.R.: Introducing Geodesign: the concept. Esri Press, Redlands (2012) Moura, A.C.M.: Escolhas Conscientes em Tecnologias de Geoinformação para Representação, Análise, Simulação e Proposição para um Território: Suporte ao Geodesign. In.: Sutil, T. et al. Geoprocessamento na análise ambiental. Criciúma, Unesc. pp. 11–68 (2020) Moura, A.C.M.: Geodesign in parametric modeling of urban landscape. Cartogr. Geogr. Inf. Sci. 42(4), 323–332 (2015) Moura, A.C.M.: [2003]) Geoprocessamento na gestão e planejamento urbano. Interciência, Rio de Janeiro (2014) Peuquet, D., Marble, D.: Introductory readings in Geographic Information Systems. Taylor & Francis, London (1990) Sereni, E.: Storia del paesaggio agrario italiano. Bari: Laterza (1961) Steinitz, C.: A Framework for Geodesign: Changing Geography by Design. ESRI Press, Redlands (2012)

Participatory Mapping to Improve Urban Resilience Starting from the Experiences in the Scientific Literature and Virtuous Cases Ilenia Spadaro1(B)

, Fabrizio Bruno1,2 , Maria Cristina Lobascio1 and Francesca Pirlone1

,

1 Department of Civil, Chemistry and Environmental Engineering, University of Genoa, 16145

Genoa, GE, Italy [email protected] 2 Class STS, University School of Advanced Studies IUSS Pavia, 27100 Pavia, PV, Italy

Abstract. Participatory mapping plays a key role in increasingly embedding citizen participation in urban planning decision-making processes in our complex cities. There are several experiences suggesting how participatory mapping reduces vulnerability, strengthens resilience, and encourages local adaptive capacities. However, there’s a certain pluralism in the design and implementation of participatory mapping processes at the level of variables and actors to be mapped, technology to be used and place concerned, such as to compromise the effectiveness of interventions on the territory. First, this paper takes up the challenge posed by the fragmented nature of existing practices and provides an updated literature review on collaborative land use planning and design that has employed participatory mapping methods in the field of disaster risk management and promotion of urban resilience. All the different contributions included in the review are examined through specific indicators: mapping tools and techniques, innovative contribution and actors involved; the strengths and weaknesses that emerged are also reported. Starting from the analysis of the competent literature and its virtuous cases, the contribution proposes a multiphase methodological approach which, by integrating participatory mapping and Geodesign workshop, aims to promote urban resilience to climate change. This preliminary research lays the foundation for the further development of a spatial decision support system in which participatory mapping (as listen to the local actors first) integrates co-design workshops (co-creation of ideas then) and technical and policy interventions-assessments, in order to improve urban resilience to climate change at the municipal level. Keywords: Participatory mapping · urban resilience · spatial planning · decision support system

1 Introduction Resilience is often considered a polysemous concept that has been used in (and to link) ecology, natural sciences, computer science, psychology, health studies, etc. [1]. Although definitions differ from field to another, and even within the same field, there © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 80–89, 2024. https://doi.org/10.1007/978-3-031-54118-6_8

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is general agreement on at least two points: it is rather a capability or process than an outcome; it requires adaptability rather than stability. When it comes to urban planning, resilience emerges as a very attractive prospect for cities, which are prey to the phenomena of rapid urbanization (with associated increases in energy-related carbon emissions), political instability, globalization, and climate change. One of the most comprehensive and accepted definitions is as follows: “Urban resilience refers to the ability of an urban system-and all its constituent socioecological and socio-technical networks across temporal and spatial scales-to maintain or rapidly return to desired functions in the face of a disturbance, to adapt to change, and to quickly transform systems that limit current or future adaptive capacity” [2]. Planning resilient cities calls for a holistic approach of addressing urban assets and risks, creating risk-aware, place-based, integrated and future-oriented solutions. It is also increasingly recognized that broader participation and co-design—in which multiple actors work together to address a common set of problems—are key elements in the process of increasing resilience [3], while enhancing the legitimacy, context-specificity, innovativeness, and feasibility of the solutions achieved [4]. Participatory and map-based planning tools, such as participatory mapping (Pmap) and Geodesign workshops, have proven to act effectively in the collaborative planning for urban resilience [5, 6]. They are tools that encourage the exchange of ideas between laymen and professionals: they have simple and easy-to-use interfaces; they use the map as a common and transversal language between different groups of participants. Compared to other participatory methods, they encourage actors to translate their specific knowledge, experiences and values into clear spatial representations that fit the territory. Pmap is an umbrella term encompassing different types of methodologies: Public Participation GIS (PPGIS), Participatory GIS (PGIS), or Volunteered Geographic Information Systems (VGI) are the ones more applied by the scientific community. The use of mapping tools allows for the involvement of the population (at different levels) in land use planning through the creation of specific maps built with the data collected by the main stakeholders; these maps can constitute a tool able to guide decision-making. Whether they are based on the use of paper support tools (some sketch mapping experiences) or digital (such as ad hoc platforms), often the information collected and spatialized can be processed in GIS software to obtain georeferenced maps associated with databases, which can be updated and representable which also give the possibility of producing different cartographies according to the layers and data available [7, 8]. Geodesign is a collaborative planning and decision-making approach that closely associates the creation of design proposals with impact simulations informed by geographic contexts, systems thinking, and digital technology. Geodesign tools provide stakeholders with spatial data to support them in evaluating design alternatives [9]. Besides hard GIS information, data from crowded sources or from Pmap methods can be combined easily and effectively with Geodesign workshops, allowing for a more integrative and inclusive overall co-design process (gathering information from a wider range of citizens) [10, 11]. The whole research responds to the need to plan effective solutions for urban resilience in a participatory way. The methodology involves the development of a spatial decisions support system (SDSS) through a co-design process in which to apply the Pmap

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methods (deliberative approach to listen to local actors) and the Geodesign workshops (instrumental approach to co-create urban solutions), integrating technical and policy assessments to improve resilience to climate change at the municipal level. The belief is that this combination has great potential as both beforementioned approaches are based on georeferenced maps and assume the primary importance of clearly spatialized social values. Furthermore, the integration of Pmap methods can be a strategy to avoid the involvement of the so-called “usual suspects” and, moreover, enrich the collection of data available for the Geodesign workshops. Indeed, at the small-scale level, there are often very serious information gaps, especially in terms of territorial information on community risks, resources, and capabilities; Pmap methods not only help compensate for the typical scarcity of data available to political and technical leaders, but they can also clarify information normally excluded from conventional maps: characteristics and vulnerabilities of families, environmental knowledge and specific needs, for instance. The proposed methodology is in the initial conceptualization stage; so, this contribution proposes the first results of the research, especially at the level of study of Pmap. When it comes to Pmap there is a pluralism and a fragmentation of experiences with respect to the variables and actors to be mapped, the technology to be used and the territory involved, which can compromise the effectiveness of interventions on the territory. Therefore, this article mainly addresses the following research questions: how to properly use Pmap techniques in urban resilience projects [RQ1]? How to ensure broad intergenerational participation [RQ2]? In doing so, a thorough literature review was implemented. Finally, a first version of what the general co-design process could be is summarized.

2 Literature Review This study conducted a systematic literature review to provide an evidence-based answer to the before mentioned research questions. The search was performed in April 2023 from some widely accepted citation databases, relying on PRISMA 2020 methodology [12]. Figure 1 reports a summary scheme of the adopted research protocol. The comprehensive search found 165 papers. After excluding duplicates and articles not in line with the criteria deducible from a skimming of articles, 115 were further screened against the actual topic. Only 57 full-text articles were screened and then evaluated against the inclusion and exclusion criteria. Although they all appeared to reflect the topic of interest, 15 were screened out because they were otherwise unlikely to meet the objectives of the review. This screening led to the 42 of papers used for the in-depth review. The steps of the literature search are illustrated in Fig. 2. After the final selection of the papers, the information was manually extracted from each article and inserted into a specific spreadsheet aimed at bringing out the type of mapping, the actors involved, the technological contribution, strengths and weaknesses (columns) for each of the revised paper (rows). An excerpt of the in-depth review is shown in Table 1. Section 3 describes the results of the review and proposes a methodological approach to improve urban resilience to climate change.

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Fig. 1. Research protocol adopted for the literature review.

Fig. 2. PRISMA 2020 flowchart.

3 Development of a Methodological Proposal As emerged from the literature review, Pmap has been spreading in various fields (especially when it comes to cultural ecosystem services), but it is still poorly applied in the field of urban resilience to climate change. The examination of the Table 1 reveals how this methodology ranges from ephemeral maps drawn on the ground to paper sketch maps, from three-dimensional survey models to aerial maps and satellite orthophotos (Tools and techniques). The actors involved in the mapping activities themselves range

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I. Spadaro et al. Table 1. Excerpt of the in-depth literature review.

Paper

Tools and techniques

Innovation

Visconti C (2020) Co-production of knowledge for climate-resilient design and planning in Naples, Italy [13]

ULLab, video-documentary, service-learning, PGIS, collective mapping, online PPGIS platform

Gave the willingness to continue an action-research way and to implement the co-production methodology in an extended mapping

Pietta A et al. (2020) Re-Naturing the City: Linking Urban Political Ecology and Cultural Ecosystem Services [14]

Digital maps and interviews

Introducing in planning processes the socio-ecological relationships between tangible and intangible aspects

Primi A, Dossche R (2020) Mappatura partecipata e analisi della percezione del rischio alluvionale (Val Bisagno, Genova) [15]

Dataset of posts on social channels (data taken to geolocate them and calculate risk perception) and interviews

Replication of the experience to obtain a more complete picture of risk

…

…

…

Actors involved

Strengths

Limitations

Political administration, (local) experts, social workers, garden users, students (and communities)

Inclusiveness in planning decisions and in learning about urban risks and ways to cope with them

Gap amongst scientists, administration, and communities; limited n. of mappers; inertia of administration

Local community and experts

Valorization of suburban area and increase in public awareness to protect urban nature

Conflicts of interest given by gap of attribution of meaning and value of the area

Citizens, administrators, students, pensioners

Analysis of perception of hydrogeological risk

Gap between perception of flood risk and its real level

…

…

…

from the citizens of the neighborhood or city in which the study is carried out to defined categories of participants, such as students, researchers, representatives of territorial functions and local administrators. Lack of attention is given to the younger parts of the population, which results in an inability to consider the needs of all age groups in the population (non-intergenerational approaches) and to implement long-term activities (Actors involved). The integration in the approaches of specific questionnaires focusing on quali-quantitative variables (e.g. risk perception, awareness, risk management) and the development of GIS applications that can be operated online, with functional, easyto-use, and flexible adaptation on different platforms, are the innovative methodological aspects of the analyzed studies; these methodologies, in fact, ensure the socio-ecological relationships between tangible features, such as biophysical characteristics and physical

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artifacts, and the intangible attributes provided by the community; they also enable the collection of the needs of citizens, who are no longer considered only as spectators, but as active participants in the processes of spatial planning and management (Innovation). Finally, from the analysis in the literature, it emerges that the share of studies that have applied active Pmaps and co-design workshops in a combined way is negligible. Starting from the literature review, a methodology is developed to implement an effective, intergenerational, and inclusive process that exploits the application of Pmap and specific co-design workshops. Figure 3 graphically summarizes the methodology.

Fig. 3. Process of methodological approach.

First: analyze the case study of the territory (A.1). It is necessary to examine the planning tools that protect the territory by regulating its use and transformations. In Europe, the Basin Plan plays an important role in the case of urban resilience to climate change, as a cognitive, regulatory and technical-operational tool at the basis of the planning and programming of the rules of use and of the conservation, defense and enhancement interventions of the soil, as well as for the correct use of water. Additional information not found on typical planning tools can be downloaded from platforms such as OpenStreetMap. The cognitive phase, then, presupposes the carrying out of well-planned inspections, such as to visually verify the reality in which one is going to operate. The inspections aim to evaluate appropriate indicators of urban resilience to climate change such as: damp spots in the buildings, the presence of underground and basement floors, the slope of the streets, etc. In order to structure an effective, highly participatory and intergenerational methodology, the mapping of local actors—categorizable by urban function—to be included in information gathering and participatory planning activities is essential. Participation, in fact, cannot be just a work of information or consultation on which of the planning alternatives to finance; the involvement of local actors also finds legitimate space in the territorial study phase, integrating the data contained in the official public-private databases and in the planning tools (often deficient, outdated or in any case not applicable at a medium-low territorial level, such as for instance the neighborhood). Furthermore, citizens, being experts of the place they live in, can guide and devise ideas for design solutions that fit well into the socio-cultural, economic, and environmental fabric of the

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area, guaranteeing good long-term results. Figure 4 shows the target group of participants identified as significant for the purpose of the mapping activity.

Fig. 4. Local actors/urban functions to be involved.

The methodology combines 3 different Pmap methods, dedicated to all 7 identified urban functions. At first, an ad hoc online PPGIS survey (A.2) is developed and shared (snowball sampling). The questionnaire aims at identifying and spatializing social and environmental variables related to urban risks, such as: perception of environmental and anthropic risk; previous experiences; social narratives; adoption of self-protection behaviors; territorial criticalities; preferences, and project proposals. It is also possible to insert in the questionnaire items relating to socio-demographic variables and resilience indicators that guide the inspections (for confirmation or enrichment of the data). There are several platforms that can adequately serve this purpose (e.g., Maptionnaire, Spraycan, ArchGIS online, etc.). LimeSurvey is the one that should be used in this case as it provides the possibility of structuring online questionnaires—which do not require any registration on the platform by those participating in the research—in a clear and simple format; moreover, it is possible to condition the appearance of some questions in relation to the previous answers; it is provided with a function by which to georeferencing (easily uploaded to GIS software) some information given by the respondent. A PPGIS-facilitated in-person survey session (A.3) also is conducted to engage that part of society that is not very familiar with digital tools. This session takes up the sketch map concept and applies it to the field of urban resilience to climate change: the participants—divided into working groups of up to 8 people—analyze a paper map depicting the area of the case study seen from above; each working group is led by a facilitator, whose task is to stimulate the involvement and analysis of the issues, and by an assistant who notes what emerges during the Pmap activity. Participants are asked to inhabit the map by indicating with special stationery items (markers, post-its, round stickers, tracing paper, etc.): the most critical points and areas to report; previous experience; knowledge of the building conditions; barriers/facilitating factors to new interventions; resources and good practices adopted by local communities, etc. Participation in the session is voluntary; participants are enrolled partly through a questionnaire and partly through word of mouth or personalized emails. The methodology envisages to activate a VGI survey (A.4) to contribute the spatial data collection and map updating. The open-source platform identified for this purpose is MyMaps, a Google extension that allows you to configure shared maps. Participants can

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indicate the most critical areas (by attaching photos taken on site and a brief description to the report), tell past experiences, indicate places to be regenerated and made safe. This is an example of active mapping [16], which occurs when the user provides information knowingly, typically as a volunteer, and knows how the information will be used. The sharing of the initiative can take place through the publication of the QR code on the official websites of the partners, on posters in local meeting places and newspapers— local media. The methodology requires that all data emerging from these activities (technical analysis of the status quo, PPGIS, in-person survey and MyMaps-VGI), are georeferenced into a GIS—Geographical Information System—software platform (A.5), producing, managing, and analyzing the territorial data by associating alphanumeric descriptions to each geographical element. The approach proposes the use of the open-source software QGIS, which has a user-friendly user interface, allows easy analysis of spatial data, and has a structure that can be adapted to different functions thanks to the use of plugins. It is also able to communicate with various software: first, Microsoft Excel, which allows you to manage and produce spreadsheets that can then be imported into QGIS to implement the file. Furthermore, it is noteworthy how the use of MyMaps is also strategic for the possibility of exporting all the data of the personalized collaborative map in.kml or.kmz format, which can be easily imported on the QGIS platform (plug in: KML tools). Finally, the co-design process includes at least 2 workshops (to be carried out in presence or remotely: e-participation). The first is dedicated to analyzing-confirming the state of affairs of the territory and building development scenarios (C); the second aims at co-creating urban solutions (D). For these 2 workshops, the participation of the representatives of the identified urban functions takes place mainly through: a formal invitation; sharing of the initiative through the mailing list that is structured during all the previous work phases; and promotion through the communication channels of the partners of project. It is desirable that a one-day pilot workshop (B) is carried out to test the collaborative process, the tools, and the digital interfaces with which the participants interact. In the first workshop (C) participants are provided with the Pmap resulting from the previous phases of the process; they are asked to comment on the results and integrate them. Participants are also asked to develop different scenarios (what if?) describing how the territory could change in relation to the current policies and projects; then, the creation of a common vision among the actors involved is stimulated. For the last co-design workshop (D), a collaborative platform with a simplified interface is created using QGIS, allowing participants to share their ideas by inserting inputs directly on a shared digital map through georeferenced layers. MyMaps is also proposed to be used for this purpose. 3 rounds of co-design are done to develop and prioritize planning strategies for building urban resilience in the form of policies or projects, inspired by the GeodesignHub process. Each round begins with individual inputs to ensure all ideas are picked up, followed by shared discussion and negotiation to combine these ideas. In the single phases, laptops, tablets, or smartphones are used, while in the joint comparison phases, a data projector is used. A library of cartographic layers is provided to be used as a background for the various design phases.

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4 Conclusions Starting from the literature review, the paper proposes a methodological approach that integrates Pmap (as listen to the local actors first) and Geodesign workshops (co-creation of ideas then), to improve urban resilience to climate change. The research is still in its initial phase. Some aspects should be further explored, for example, the terms used for the analysis in the literature have probably not been able to bring out some contributions concerning the use of Pmap techniques in the field of Geodesign. The methodology could therefore undergo further changes during its application and testing—learning by doing approach. Already now, however, this methodological approach offers many ideas: 1_ in building urban resilience to climate change, the proposal of effective Pmap techniques both in the case study analysis phase and in the design phase [RQ1]; 2_ in the integration of analogue (paper map) and digital tools (MyMaps, online questionnaire) to adequately balance the technical need to collect and process qualitative-quantitative data with the need to reach the largest possible slice of local actors (from 11 years of age), regardless of their degree of digital domesticity [RQ2]. The methodology therefore makes it possible to collect the contributions of actors representing the functions of the territory to integrate them harmoniously into a SDSS to implement tailor-made solutions, monitor their progress and therefore support the local public administration in the choice of resilience and urban regeneration interventions. This approach was designed to be flexible and therefore capable of dealing with territorial dynamics at different scales, starting from the municipal level, to be integrated into Plans for Adaptation to Climate Change or into other sectoral plans, such as the Basin Plan. Author Contributions. § 1 was written by FP, IS; § 2 was written by FP, MCL; § 3 was written by IS, FB; § 4 was written by IS, MCL. This paper and related research have been conducted during the Italian national inter-university PhD course in Sustainable Development and Climate change (link: www.phd-sdc.it).

References 1. Piégay, H., Chabot, A., Le Lay, Y.: Some comments about resilience: from cyclicity to trajectory, a shift in living and nonliving system theory. Geomorphology 367, 106527 (2020) 2. Meerow, S., Newell, J.P., Stults.: Defining urban resilience: a review. Landscape Urban Plann. 147, 38-49 (2016) 3. United Nations Office for Disaster Risk Reduction (2023) GAR Special Report 2023: Mapping Resilience for the Sustainable Development Goals. UNDRR, Switzerland 4. Gaete Cruz, M., Ersoy, A., Czischke, D., van Bueren, E.: Towards a framework for urban landscape co-design: linking the participation ladder and the design cycle. CoDesign: Int. J. CoCreation Design Arts 1–20 (2022) 5. Debnath, R., Pettit, C., Zarpelon Leao, S.: Geodesign approaches to city resilience planning: a systematic review. Sustainability 14(2), 938 (2022) 6. Hung, H.C., Yang, C.Y., Chien, C.Y., Liu, Y.C.: Building resilience: mainstreaming community participation into integrated assessment of resilience to climate hazards in metropolitan land use management. Land Use Policy 50, 48–58 (2016)

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7. Fagerholm, N., Raymond, C.M., Olafsson, A.S., Brown, G., Rinne, T., et al.: A methodological framework for analysis of participatory mapping data in research, planning and management. Int. J. Geogr. Inf. Sci. 35(9), 1848–1875 (2021) 8. Kahila-Tani, M., Kytta, M., Geertman, S.: Does mapping improve public participation? Exploring the pros and cons of using public participation GIS in urban planning practices. Landsc. Urban Plan. 186, 45–55 (2019) 9. Steinitz, C.: A framework for geodesign: Changing geography by design. Redlands (2012) 10. Ducci, M., Janssen, R., Burgers, G.J., Rotondo, F.: Co-design workshops for cultural landscape planning. Landscape Res., 1–17 (2023) 11. Gottwald, S., Brenner, J., Albert, C., Janssen, R.: Integrating sense of place into participatory landscape planning: merging mapping surveys and geodesign workshops. Landsc. Res. 46(8), 1041–1056 (2021) 12. Page, M.J., McKenzie, J.E., Bossuyt, P.M., Boutron, I., Hoffmann, T.C., et al.: The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. The BMJ 372(71), 1–9 (2021) 13. Visconti, C.: Co-production of knowledge for climate-resilient design and planning in Naples. Italy. Habitat Int. 135, 102748 (2023) 14. Pietta, A., Tononi, M.: Re-naturing the city: linking urban political ecology and cultural ecosystem services. Sustainability 13, 1786 (2021) 15. Primi, A., Dossche, R.: Mappatura partecipata e analisi della percezione del rischio alluvionale (Val Bisagno, Genova). Bollettino della Associazione Italiana di Cartografia 169, 128–144 (2020) 16. Cloudoveu, A.D.J.: Challanges in crowdsourcing geospatial data to replace or enhance official sources. DisegnareCon 11(20), 1–15 (2018)

Geodesign in the Shared Decision to Create Full Protection Conservation Units, as a Mitigating and Compensatory Action for the Transformations of Iron Mining in the Landscape Flávia Las-Cazas de Brito1(B)

and Ana Clara Mourão Moura2

1 Geosciences Institute, Federal University of Minas Gerais Minas Gerais (UFMG),

Avenida Presidente Antônio Carlos 6627, Belo Horizonte, Brazil [email protected] 2 School of Architecture, Geoprocessing Laboratory, Federal University of Minas Gerais (UFMG), Rua Paraíba 697, Belo Horizonte, Brazil

Abstract. The state of Minas Gerais, in Brazil, has iron mining as one of its main economic activities, a process whose nature is to transform the landscape. Due to serious environmental disasters, discussions about counterpart actions, environmental protection and recovery had increased interest. Among the environmental initiatives, the possibility of creating Full Protection Conservation Units stands out, which may result of hierarchizing other types of existing conservation units, requalification and expansion of existing areas, or even the proposition of new areas to receive the benefit. The discussion about the definition of these areas is not trivial and requires specific knowledge about the area, its main characteristics, vulnerabilities and potentialities. The process requires, above all, sharing decisions that may result from listening to different sectors of society, through a process of co-creation. In this sense, an experimental academic study was carried out in the Piranga River sub-basin, an area seriously impacted by an environmental disaster in 2015. Although academic, the study invited representatives of society, related to institutions of economic, environmental and social activities. The Geodesign framework was applied through the creation of analytical maps of the area, organized in an SDI (Spatial Data Infrastructure) and the workshop took place on the Web-Based GISColab platform, through the steps of enrichment of reading about the area, proposition of ideas, discussions and criticisms, measurement of compliance using proposed metrics, voting and decision. The study is an example of how Geodesign can give broad support to the decision to choose suitable areas for Full Protection Conservation Units. Keywords: Geodesign · Geovisualization · Conservations units · Environmental planning · SDG

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 90–101, 2024. https://doi.org/10.1007/978-3-031-54118-6_9

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1 Introduction Mining activity, more specifically iron mining, is an important part of the economy of the state of Minas Gerais, in Brazil, whose historical origins and economic, social and cultural development were associated to mineral production, initially gold and diamonds, followed by iron ore. The natural landscapes were transformed by mining, while the cultural landscape resulted from the occupation of territory encouraged by mining. There is, therefore, a relationship of impacts and results. Despite the many discussions that may result from this duality, the society is facing the stage in which the transformations caused by disasters or by exploitation activities need to be balanced by mitigating and compensatory actions, within the principles of sustainability, what means considering economic, social and environmental concerns. The case study is developed in the Piranga River sub-basin, region of Minas Gerais where the Mariana disaster occurred, an event in which a dam of mining tailings broke in November 2015. The dam was used to store the iron ore tailings operated by the company Samarco. The rupture caused environmental impacts, contamination of the soil, expressive impact on water tributaries and in the main course of the River Doce. The impact covered 853 km from the town of Bento Rodrigues to River Doce mouth, in the Atlantic Ocean. Along the river 39 municipalities in Minas Gerais and Espírito Santo states were affected. The Piranga River sub-basin was the most directly affected area. The Piranga river sub-basin comprises an area of 17,562.49 km2 , representing 24.65% of the territory of the river Doce basin [1], along which a population of 711,026 thousand inhabitant lives in 77 municipalities [2]. (Fig. 1).

Fig. 1. Location of the study area. Data source: Elaborated by the authors, using data from official SDIs—Spatial Data Infrastructures (IBGE and SISEMA) [2, 3].

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In face of the impacts of the disaster, and as a result of society maturing in the questions about territorial planning, there is the interest in participatory consultation and strategic planning. There is a growing demand for discussions about the definition of new environmental protection areas, as the Conservation Units, as well as investments in the requalification of existing units.

2 Geodesign Methods Among the methods and techniques that can support processes of this nature, geoinformation technologies stand out and, more specifically, geodesign. Geoinformation is the product of georeferenced spatial data that aims to characterize the area, mapping its potentialities, vulnerabilities and specificities. It relies on the production of information from geodatabases, satellite images and, above all, the application of spatial analysis models. It results in characterization, diagnostic, prognostic and predictive studies. In another hand, geodesign is an evolutionary stage of geoinformation technologies, as it advances from evaluative towards propositional studies [4]. Geodesign is based on the use of spatial information organized by geovisualization for consumption by users, preferably on web-based devices. It favors the construction of opinions through georeferenced annotations and designs made by citizens, technicians or not, and it is a support for the co-creation of ideas for an area. Co-creation takes place by registering ideas, comments and debates on the proposals, applying mechanisms to verify possible impacts to be achieved and, finally, voting to arrive to final decision. The idea of geodesign was initially proposed by Steinitz [5], when the author presented his framework indicating that a complete study must go through six models, in three rounds of review procedures. The models aim to answer the questions: 1) 2) 3) 4) 5) 6)

How can the work area be described? By Representation Model; How does the desktop work? By Process Model; Does the desktop work well? By Evaluation Model; How can the desktop be changed? By Change Model; What differences can the changes cause? By Impact Model; How should the desktop be changed? By Decision Model.

In the case study developed, adaptations of the geodesign framework proposed by Moura [6] were chosen. Following the same intention of the six models, it is based on the initial creation of a complex collection of maps, resulting from models of spatial analysis and treatment of geospatial data. In the stage of Representation Models (data collection) and Processes Models (analytical maps that indicate how information occurs in the territory) a collection of maps is organized as an SDI—Spatial Data Infrastructure, made available in a Web-GIS (Geographic Information System on the web). The stage of Evaluation Models in Steinitz’s framework [5] are synthesis thematic maps displaying the locations of areas defined as feasible to receive proposals. According to the point of view of Moura [6] these models are not necessary and may cause reactions of the participants, if they don’t agree with the definition about the indicated areas, or even have a pacific role during the workshop, losing critical decision-making power. Instead of presenting a synthesis about where to draw ideas, in the applied framework

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the participants combine, by themselves, the geospatial data in the Web-GIS, to decide about their own opinions about the appropriate place to design proposals. Once the workshop starts, participants take notes on the platform, inserting georeferenced pins and containing annotations of their assessments, which can be read and considered by geeks. This process replaces the Evaluation Model, but it is not reductionist, as each participant constructs his own combination of information to decide about the feasible area for proposals. The Change Model takes place in the drawing of proposals by participants during the workshop. They can use points, lines or polygons, to which titles and descriptions are associated. The Impact Model is supported by widgets (windows with graphs or numbers) that dynamically calculate the effect of the proposals designed in face of the objectives established for the workshop, presented in metrics that can be translated into quantitative results. Finally, the Decision Model takes place in the dialogue stage, when participants register comments on the proposals, as well as opinions with criticisms and suggestions, followed by the voting process [7].

3 Conservation Units in Brazil The concern for nature protection is an issue that has been discussed over the years. The International Union for Conservation of Nature (IUCN) that defines a protected area as “a clearly defined, recognized, purpose-built geographical space managed through effective means,…, to achieve the long-term conservation of nature, with associated ecosystem services and cultural values” [8]. The IUCN has classified protected areas into seven categories based on their main management objectives: Strict nature reserve, Wilderness area, National Park (ecosystem protection, cultural value protection), Natural monument, Habitat/species management area, Landscape /protected marine and Protected areas, with sustainable use of natural resources. In Brazil, the Federal Constitution [9], in its article 225, declares that “everyone has the right to an ecologically balanced environment, an asset for common use by the people and essential to a healthy quality of life…”. Federal law 9,985, of July 15, 2000, regulated the National System of Nature Conservation Units (popularly known as the SNUC law). And one of the goals for the law is to enhance the role of Conservation Units. The SNUC divided the units into two groups: Sustainable Use and Full Protection [10]. These Conservation Units are of fundamental importance for the preservation and conservation of the Atlantic Forest Biome. The objective of the Sustainable Use Units is to “make nature conservation compatible with the sustainable use of part of its natural resources” [9]. This group has the following categories: Environmental Protection Area, Area of Relevant Ecological Interest, National Forest, Extractive Reserve, Fauna Reserve, Sustainable Development Reserve and Private Natural Heritage Reserve [10]. The group of Full Protection Units aims to preserve nature, allowing only indirect use of its natural resources, and has the following categories: Ecological Station, Biological Reserve, National Park, Natural Monument and Life Refuge Wild [10].

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The allowed uses in a conservation unit may vary according to the unit’s category, which enables the conservation of the environment and sustainable use, contributing to a wide range of ecosystem services (tourism, fruit and seed harvesting), among others), resulting in economic diversification, focusing on sustainability and the integration with society. In the state of Minas Gerais there are 472 conservation units for Sustainable Use and 125 for Full Protection, both at the federal, state and municipal spheres. In the Atlantic Forest Biome there are 91 units of Sustainable Use and 91 of Full Protection, in the three spheres.

4 Representation and Process Models: The Production Maps For the elaboration of Representation and Process models, studies about data were carried out in official SDIs, such as the Brazilian Institute of Geography and Statistics (IBGE), Brazilian Agricultural Research Corporation (EMBRAPA), State spatial data infrastructure (IDE-SISEMA, MG), National Mining Agency (ANM), among others. The first maps of the Representation Model were the limits of the Piranga River sub-basin and the municipal limits (Fig. 2A and B). These models aim to present the spatial delimitation of the study area. In the thematic of vegetation, maps of the Full Protection and Sustainable Use were organized, and the Ramsar Site (List of Wetlands of International Importance) were prepared (Fig. 2C and D). These maps help to identify areas with some protection and to analyze if these areas need some improvements, comparing their limits with land use and land cover map (Fig. 2E). It was also included the map of Priority Areas for Conservation, that is a strategic planning of the state of Minas Gerais for the conservation of biodiversity and ecosystems (Fig. 2F). Consulting the map of Legal Reserves (Fig. 2G) it is possible to verify the areas that are already legally protected, since Brazilian legislation specifies that each rural property is required to have a percentage of the area untouched, covered by native vegetation. This percentage varies according to the region, and in the sub-basin of the case study it is 20% of the total area of the rural property. The map of the potential occurrence of cavities (Fig. 2H) was prepared by CECAV (National Center for Research and Conservation of Caves) related to the Chico Mendes Institute, with the objective of characterizing the Brazilian regions that may have a greater probability of occurrence of caves [11]. To complete the Representation Models, maps with urban plots were prepared (Fig. 3A), highlighting population concentrations and the main existing roads in the study area (Fig. 3B). Water resources were mapped in hydrology maps (Fig. 3C) and granting points with resource capture (Fig. 3D). Natural resources were mapped in soil map (Fig. 3E), iron ore formation (Fig. 3F), geomorphology (Fig. 3G), and mining exploitation rights and activities (Fig. 3H). For the Process Models, analytical maps were made with information that indicate the spatial distribution of phenomena and occurrences in the area. Regarding economic data, the Capillarity and Accessibility map (Fig. 4A) allows observing capacity and possibility of displacement in the area. About socioeconomic conditions, the map of percentage of Sewage Services (Fig. 4B), Income Distribution (Fig. 4C) and Population Density (Fig. 4D) allow to understand the quality of life in the area.

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Fig. 2. Representation models, Boundary of sub-basin (A), Municipal Boundaries (B), Full Protection Conservation Units and Ramsar site (C), Sustainable Use Conservation Units (D), Land Use and Land Cover (E), Priority areas for conservation (F), Legal Reserve (G) and Potentiality of Caves (H). Source: organized by authors, using initial data from official SDIs.

Fig. 3. Representation models, urban stain (A), major roads (B), major river (C), water use grant (D), soil types (E), iron formation (F), geomorphology (G) and mining right (H). Source: the authors, using initial data from official SDIs.

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In addition to these maps, to represent the geomorphology of the area, Slope maps (Fig. 4E) and Hypsometry (Fig. 4F) were prepared, allowing participants to analyze the landscape according to its topography. To contribute to environmental analysis, it was prepared the NDVI (Normalized Difference Vegetation Index) map (Fig. 4G), to analyze the robustness of the vegetation, in addition to indicating the primary production and local humidity. Through the hydrography and the springs, it was possible to elaborate the Density of the Headwaters (Fig. 4H).

Fig. 4. Process models: Accessibility and Capillarity (A), Percentual of Sewage Services (B), Income Distribution (C), Population Density (D), Slope (E), Hypsometry (F), NDVI (G) and Concentration of Headwaters (H). Source: produced by the authors.

Maps were also produced according to the principles of Landscape Ecology, related to metrics of Core Area (Fig. 5A), Shape Factor (Fig. 5B) and Connectivity of Patches (Fig. 5C), and combination of them in synthesis map was prepared (Fig. 5D). The synthesis was based on the Multicriteria Analysis by Weights of Evidence, resulting in the classification of conditions and indicating the best patches. In addition to Process Models, a Land Surface Temperature map (LST) (Fig. 5E) was prepared, using Landsat Satellite Band 10 (thermal band) data, and the Local Climate Zone (LCZ) map (Fig. 5F), that is a classification prepared by Stewart and Oke [12] that is quite useful at urban climate studies with the aim of detailing climate responses in different urban structures, considering built typologies and land cover.

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Fig. 5. Process models: Core Area (A), Shape Factor (B), Connectivity (C), Landscape Ecology Synthesis (D), Surface Temperature (E) and Local Climate Zones (F). Source: produced by the authors.

5 Change, Impact and Decision Models: Co-creation of Ideas During the Workshop The workshop took place in 4 meetings in April 2023 and had the participation of 13 people, comprising the group of academics (post-graduate and graduate students) and the group of expert technicians who work in the study area. Among the technicians were invited participants from the mining company Vale, from the IEF (State Forestry Institute) and specialists in the subjects of water, vegetation cover and of basin committee planning. Participants were told that the objective was to build proposals for Full Protection Conservation Units. The proposals could be to requalify and enlarge existing units, to hierarchize parts of conservation units of another nature (such as APAs - area of environmental protection and sustainable use) to the Full Protection class, or even the creation of new Full Protection areas. While designing polygons of proposals the participants were expected to achieve the goal of a percentage of increasement of areas, aiming the recovery of trees. The performance was dynamically measured during the workshop, as a result of Impact. The first stage consisted of Reading Enrichment, through which participants made notes in the web-platform using georeferenced pins, to indicate alerts or additional information not contained on the maps. It is called enrichment, because the participants enrich themselves with structured information about the study area, but they also enrich the data collection with complementary information. The group of participants was divided into 3: group A, composed of the technical team, groups B and C, composed of students. The participants visualized the collection of available maps and inserted pins with the description and observations they had of the area, helping to enrich information about the study case. In total, 53 annotations were georeferenced (Fig. 6A).

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The second stage consisted of designing proposals, separated into Social/Cultural, Economic and Environmental interests, the tripod of sustainability. All the proposals had titles and descriptions to explain their purposes. The 3 groups made proposals on each axis of interest, in a cycle, going from Environment context to Social and to Economic contexts. While designing the polygons of ideas they had to inform whether the proposal was to create FPCU (Full Protection Conservation Unit), to expand the existing FPCU and/or to recover the FPCU. As a result, 10 proposals were designed in the Environmental axis, 10 in the Social/Cultural axis and 9 in the Economic axis, (Fig. 6B), resulting in 29 proposals of Full Protection Conservation Units.

Fig. 6. A) Reading Enrichment step—georeferenced pins distribution. B) Creation of ideas step— new polygons of FPCU. Example of Economic context. Source: the authors, using GISColab web platform.

The third stage consisted of Critical Dialogues and evaluations of the proposals. The participants were asked to analyze the assertiveness of the ideas according to place, priority and thematic approaches. As the final project was expected to reach the goal of area and tree protection increasement, a widget was used to measure the sum the of polygons’ areas in each context. The metric used Crowther and colleagues’ references [13] that proposed an increasement of trees’ protection in 30% until 2050 to contribute to clime global changes and carbon sequestration. As well as Crowther et al., Bastin [14] defends that a global forest restoration of around 30% would reduce a considerable proportion of carbon emissions, mitigating climate change. The organizers calculated that in the case study this goal represents the increasement of 60% of the area of existing FPCU, so that a target of 20% was established for each group (Environmental, Economic and Social). Atlantic Forest represents 5671 km2 , from which 30% is 1701 km2 , and in another hand the Full Protection Conservation Units presents an area of 683 km2 , that means 40% of 1701 km2 . To arrive to the goal of 30% of robust vegetation, the proposals need to increase the area of FPCU in 60%. Finally, the voting stage was held for the final decision about the best ideas to increase Full Protection Conservation Units in the Piranga River Sub-basin. The ideas that had more than 60% of “like” votes were considered automatically approved, proposals with less than 40% of “like” were rejected, and those between 60 and 40% were separated to

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be discussed again in the fourth stage. From the proposals of the Environmental group 8 were approved, and 2 were rejected by the participants. In the Social group, 9 were approved and only 1 was rejected (Fig. 7). In the Economic group, 5 ideas were approved, 1 was rejected and 2 were in the range of 40 to 60% and were separated to be discussed, reviewed and voted again in the fourth stage.

Fig. 7. Third stage—Discussing and voting on the proposals. Example of Social context. Source: the authors, using GISColab web platform.

The fourth stage consisted of a new discussion of the contexts that did not reach the target of 20% of area increasement (Social and Environment contexts), in which the participants enlarged some polygons of proposed FPCU. Subsequently, the two proposals of the Economic context were put to vote, and as a result one was approved and one was rejected by the participants. The Workshop was concluded reaching a 63.73% increase in the FPCU in relation to the existing ones, distributed as 19.58% in the Environmental context, 26.38% in the Economic context and 17.77% in the Social context. The increment of area was used to calculate the metrics about the possible number of trees that could be preserved or planted in the new areas, according to the media of units in robust vegetation in the area, calculated from the Crowther Map of Data Points and Raw Biome-level Forest Density Data [14]. Using the maps Above Ground and Below Ground Biomass Carbon Density organized by Spawn and Gibbs [15], it was also calculated metrics about the possible increasement in carbon sequestration. The Table 1 presents the numbers achieved: Table 1. Results achieved with the Workshop. Context

Area (km2 )

Environmental

133.65

Economic

180.31

CO2 above/km2 (MgC)

CO2 below/km2 (MgC)

4,724,972

28,817.34

11,978.69

6,374,343

21,360.08

8,878.89

Total trees (units)

Social

121.31

4,288,523

31,748.72

13,197.20

TOTAL

435.27

15,387,838

81,926.14

34,054.77

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6 Conclusions and Discussions The creation of Full Protection Conservation Units is of fundamental importance in order to have a more effective protection of the remaining Atlantic Forest vegetation. Geodesign enable the planning process to become more effective, as the co-creation of ideas gives support to decision about the best places and produces a design with defensible criteria, resulted from consensus maximization, as the participants act as representatives of science and citizens. The study area is inserted in the Atlantic Forest, a biome that covers approximately 15% of the Brazilian territory, being only 9% of what it used to be in the past. In the country 70% of the population lives in this biome and 35% of the biodiversity of plant species in Brazil is in it. In view of such importance, it is essential that this biome has special protection, what justifies the target for increasing 60% of the FPCU. There are only 8 FPCU along the entire basin, what means that with the new proposals this number would increase by 287%, with the implementation of the 23 new units. The proposal considers the tripod of sustainability, presenting ideas to meet the goals of environment, economic and social approach (Fig. 8).

Fig. 8. Proposals approved. Source: the authors, using GISColab web platform.

The analysis of the development of the workshop allowed the observation of the commitment of the participants in the process, as well as the assessment of the level of negotiation difficulties and consensus maximization. Surprisingly, the workshop took less time than planned, allowing steps to refine proposals and adjust decisions. This was understood by the very high rate of approval of proposals and the wide difference in positive or negative votes when the decision was for approval or for disapproval. Of the set of proposals, 78.6% were approved and 14.2% were rejected. The percentage of polygons that were put under to review and discussion was only 7.14%, and of these, only one was adjusted and accepted in the final decision. In view of the above, a possible answer to the ease negotiation during the workshop, and the ease of reaching a final design, can be associated with the confidence to issue opinions favored by the quality of the information presented as support for the decision,

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as well as the possibility of preparing adjustments and revisions, exhausting the interests of discussion. As future developments, it will be important to test the process with a larger number of residents of the place, and to compare the design obtained with a technical analysis to indicate potential areas for the installation of new FPCUs.

References 1. IGAM – Instituto Mineiro de Gestão das Água: Plano de ação de recursos hídricos da unidade de planejamento e gestão. DOI1-PARH-Piranga. (2010) http://repositorioigam.meioambie nte.mg.gov.br/handle/123456789/974. Last accessed 03 Mar 2023 2. IBGE – Instituto brasileiro de geografia e estatística. Censo Brasileiro de 2010: Rio de Janeiro: IBGE. (2012) https://censo2010.ibge.gov.br/. Last accessed 03 Mar 2023 3. IDE-Sisema – Infraestrutura de Dados Espaciais do Sistema Estadual de Meio Ambiente e Recursos Hídricos. https://idesisema.meioambiente.mg.gov.br/webgis. Last accessed 10 May 2023 4. Moura, A.C.M., Freitas, C.R., Rosa, A.: O Geodesign como suporte aos valores contemporâneos em planejamento ambiental e urbano. In.: Fruehauf, A.L., Rosa, A.A., Maruyama, C., Coelho, M.A. (Org.) Geodesign no Brasil: abordagens para o planejamento ambiental urbano. Pedro & João Editores, São Carlos, pp.13–39 (2022) 5. Steinitz, C.: A Framework for Geodesign: Changing Geography by Design. ESRI Press, Redlands (2012) 6. Moura, A.C.M., et al.: Quadrilátero Ferrífero: um caso emblemático para o Geodesign. In.: MOURA, A. C. M. (Org.). Unidades de Paisagem e Geodesign no Quadrilátero Ferrífero. Pedro & João Editores. São Carlos, pp. 85–108 (2022) 7. Moura, A.C.M., Freitas, C.R.: Brazilian Geodesign Platform: WebGis & SDI & Geodesign as Co-creation and Geo-Collaboration. Lecture Notes in Computer Science. 1ed.: Springer International Publishing, 12252: 332–348 (2020) 8. Borrini-Feyerabend, G., et al.: Governança de Áreas Protegidas: da compreensão à ação. Série Diretrizes para melhores Práticas para Áreas Protegidas, No. 20, Gland, Suiça: UICN (2017) 9. BRASIL: Constituição. Constituição da República Federativa do Brasil (1988) 10. BRASIL: Lei nº 9985, de 18 de julho de 2000. Sistema Nacional de Unidades de Conservação. Brasília (2000) 11. Jansen, D.C., Cavalcanti, L.F., Lamblém, H.S.: Mapa de potencialidade de ocorrência de cavernas no Brasil, na escala 1:2.500.000. Revista Brasileira de Espeleologia, Brasília, 2(1):42–57 (2012) 12. Stewart, I.D., Oke, T.R.: Local climate zones for urban temperature studies. Bulletin American Meteorol. Soc. Boston 93(12), 1879–1900 (2012) 13. Crowther, T.W., Glick, H.B., Covey, K.R., Bettigole, C., Maynard, D.S., Thomas, S.M., Smith, J.R., Hintler, G., Duguid, M.C., Amatulli, G.: Mapping tree density at a global scale. Nature 525, 201–205. [CrossRef] [PubMed] (2015) 14. Bastin, J.B., et al.: The global tree restoration potential. Science 365(6448), 76–79 (2019) 15. Spawn, S.A., Gibbs, H.K.: Global Above ground and Below ground Biomass Carbon Density Maps for the Year 2010; ORNL DAAC: Oak Ridge. TN, USA (2020)

Geoprocessing, Geodesign and Urban Parameters: Geoinformation and Co-Creation of Ideas in Urban Planning Teaching Ashiley Adelaide Rosa1(B)

and Ana Clara Mourão Moura2

1 Programa de Pós-Graduação Em Geografia, Universidade Federal de Minas Gerais (UFMG),

Instituto de Geociências da UFMG, Av. Antônio Carlos 6627, Belo Horizonte, Brazil [email protected] 2 Laboratório de Geoprocessamento, Universidade Federal de Minas Gerais (UFMG), Escola de Arquitetura, Rua Paraíba 697, Belo Horizonte, Brazil

Abstract. This paper presents an academic experience that uses geospatial technologies and geodesign in urban planning teaching considering citizens’ listening, place characterization and propositional design. In addition, it makes use of alternative urban parameters, the Completeness Indicators, applied in local scale urban planning in an undergraduate degree course in Architecture and Urbanism, at the Federal University of Minas Gerais, Belo Horizonte, Brazil. It was an experience of space diagnosis, followed by a geodesign workshop to propose changes to the central area of Belo Horizonte city. The students learned about co-creation of ideas with the goal to achieve the condition of completeness of the urban space, considering mobility, environment and place quality of the streets. As a result, it was possible to see from this experience that while the geoinformation and geovisualization of the study area were consolidated, the assertiveness of the proposals improved and the mastery over the study area by the students increased. Thus, the article is structured as follows: (i) brief presentation and description of the case study area; (ii) details of the methodological steps used in the course; (iii) report on the development of activities and experiences of the geodesign workshop with the students; (iv) results and analyzes of the experience and, finally, (v) considerations about the academic experience, methods and tools explored for local scale urban planning teaching. Keywords: Urban spaces · Landscape quality · Environmental assessment · Co-creation process · Geovisualization · Complete streets

1 Introduction The values applied to urban planning are constantly changing and are moving towards safe, lively, sustainable and healthy cities – returning to the human scale of the street [1]. This process highlights the role of the urban planner as decoder of collective demand, offering technical support and expertise for this transposition, necessarily in a collaborative way and to promote citizens’ listening in the urban planning process [2, 3]. This way, © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 102–113, 2024. https://doi.org/10.1007/978-3-031-54118-6_10

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it is important training future urban planners to give support to collaborative planning processes and to having ability to translate collective values to designs that represents the place’s people. In this scenario, there is the Completeness Index for Complete Streets, based on 3 street functions or analytical contexts: environment, place and movement [4]. The completeness of the streets is the capacity of this free and public urban space to absorb its competing functions depending its vocation. In the study carried out, based on a bibliographical review of reference papers, it was proposed that the referred index be composed of 12 urban indicators that help both in the elaboration of ideas and in the evaluation of the performance of urban streets: (i) street afforestation, (ii) efficient drainage, (iii) environmental comfort, (iv) landscape quality, (v) active facades, (vi) flexibility of uses, (vii) universal accessibility, (viii) permanence spaces, (ix) road capacity, (x) road safety, (xi) mode connectivity, and (xii) active mobility. At the same time that the use of georeferenced information supports the teaching of urban planning, it allows work with spatial variables and the investigation of phenomena related to spatial distribution. Then, the use of technologies of geoinformation qualifies the planning process by providing capture and distribution of geospatial data; giving support to the use of spatial analysis algorithms; allowing combination of variables; presenting syntheses in diagnostic and prognostic studies; and being a tool for propositional and co-creative processes. Among the data capture resources, stands out the Volunteered Geographic Information (VGI), or crowd-mapping, with the potential to measure “citizens as sensors” through web-based tools, in which participants actively and voluntarily register their opinion using georeferenced points [5]. According to Davis Jr et al. [6] collaborative data collection can happen passively, when the user accepts general terms of digital platforms and has his behavior monitored, including his spatial location. But it can also be in active mode, when the user accesses a web-based platform to register his opinions using spatial location, and that this data will compose a visualization set for all interested users. The Geodesign methodology is intended of the collective construction of proposals for alternative futures of a place, planning “with” and “for” the geographic place [3, 7– 9]. In other words, it means recognizing the characteristics, vulnerabilities and potential of an area and developing local planning proposals through shared decision-making. Geodesign can be supported by geoinformation technology, and in this scenario, there are gains in scale of work, number of participants, flexibility and adaptability of the activities, geovisualization and data processing. So, this article aims to present an academic experience that uses geotechnology and geodesign as a teaching process. In addition, it presents the use of alternative urban parameters, the Completeness Indicators, in an urban planning course at the local scale, of the undergraduate degree course in Architecture and Urbanism, at the Federal University of Minas Gerais, Brazil. The students learn the process of collective construction of ideas at the same time that they are informed about values that further the condition of completeness of the urban spaces. The article is structured as follows: (i) brief presentation and description of the case study area; (ii) details of the methodological steps used in the course; (iii) development report of activities and experiences of the geodesign

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workshop with the students; (iv) results and analyzes of the experience and, finally, (v) considerations about the aca-demic experience, methods and tools explored for urban planning teaching in local scale.

2 Materials and Methodological Steps This article reports a methodological and teaching experience with an emphasis on alternative urban parameters and the use of geotechnology, in the course “Urban planning workshops: local planning problems”. The course took place in the second semester of 2022 for undergraduate students in Architecture and Urbanism, from the School of Architecture and Urbanism of the Federal University of Minas Gerais (EAU-UFMG), taught by professor Ana Clara Mourão Moura and doctoral student Ashiley Rosa. The content of the course consisted of five parts: (i) spatial perception and cognition; (ii) urban regulations and legislation; (iii) geoprocessing and spatial analysis; (iv) geodesign as a co-creation process; and (v) urban design proposal (Fig. 1). This experience had several by-products and a final product. The discipline functioned as an accumulation of geospatial, conceptual and theoretical information that were worked on and consolidated by the students collectively, but also individually, through proposals for urban designs at the end of the course.

Fig. 1. Workflow, technological resources and products.

2.1 Study Area: Central Area of Belo Horizonte, Minas Gerais (Brazil) The central area of Belo Horizonte city, capital of the state of Minas Gerais (Brazil), was planned by a team led by Aarão Reis and inaugurated in 1897. An urban design that presents the morphology of an orthogonal road network, composed by large avenues and by presence of squares and parks, under the strong influence of the Positivist School of

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urban planning of “garden cities”. The initial plan intention was for the city to remain within the boundaries of the road that surrounds it, the so-called “Avenida do Contorno” (Contour Avenue), which measures 11.86 km and cover an area of 8.63 km2 . Nowadays it is a highly dense and verticalized area, that concentrates many points of economic and cultural-historical interests. It is also a reference for the education and health of residents of the capital and metropolitan region of Belo Horizonte. The central area has an intense movement of people and vehicles that taking to some inconveniences large urban concentrations deal with when planned under the perspective and scale of the motor vehicle. The main results are less connection be-tween people and the place, wide streets, a lot of noise, air pollution, among others. On the other hand, the central area is characterized by its tree-lined streets and wide sidewalks along the entire length of the then-planned garden city by Aarão Reis. Regarding the hydrography of the region, most of the watercourses that pass through the central area were channeled, presenting as consequences flooding points in rainy period. This and another’s characterization and diagnosis of the study area was elaborated by the students in the academic experience, and is described in a specific section. 2.2 Technological Resources ArcGIS was used for the processing of georeferenced data, allowing the reading of information, creation of maps and spatial analysis. In the course it was also used ViconSAGA [10], a web-based platform for volunteer mapping (VGI), contributing to the registration of impressions and urban reading in field camp by the students. For the geodesign step, the web-based GISColab platform was used. The VGI platform used, ViconSAGA, was developed by Professor Tiago Marino from Federal Rural University of Rio de Janeiro (UFRRJ). It is intended for the voluntary and active capture of spatial information recorded by the user. The project creator is free to define an initial visualization point and zoom (being able to choose satellite, terrain or road map views), to be presented in Google Earth for the beginning of navigation by users, as well as the graphical symbology for the records and the list of attributes that the participant must answer when registering a contribution. The Vicon SAGA application is free of charge and accepts the import and export of KML files (Google Earth) for mass registration of records in the system, SHP (ArcGIS shapefile) for the production of thematic maps, XLS (Microsoft Excel) and CSV (Comma Separated Values) for general analysis of records from a locality, which means wide system interoperability [11]. The GISColab platform [12] was initially proposed to work as an SDI (Spatial Da-ta Infrastructure) by GE21 Geotechnologies, and it was adapted, through task support scripts, by Moura and Freitas [13] to be used as a Brazilian platform for geodesign and co-creation. The platform allows the visualization of a collection of maps, presents tools to improve geo-visualization, resulting in spatial analysis and proposition of georeferenced ideas. Maps can be organized in a geoserver, but they can also be loaded through connection with other SDIs, or additional layers can be inserted by participants during the workshop. There are dynamic resources to supported the geodesign workshop stages. In synthesis, it works with WMS (Web Map Service), WFS (Web Feature Service) and WPS (Web Coverage Service) resources.

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Finally, VistaSAGA [14] was used, an environmental analysis system with an application available for desktop that provides maps and reports as results that support the decision-making process. The application was developed by Jorge Xavier da Silva [15] and is available free of charge from the Federal University of Rio de Janeiro (UFRJ). The use of VistaSAGA made it possible to carry out the Multicriteria Analysis, combining the variables as a synthesis of the collected data and urban analyzes developed by the students.

3 Development In the spatial perception and cognition stage, students first took theoretical classes on Spatial Perception, from Kevin Lynch’s perspective [16], carrying out experiments to identify the urban elements according to the author. They also had theoretical class on spatial cognition, according to the perspective of Gordon Cullen [17], carrying out field work through the central area of Belo Horizonte. The study area was divided into 12 subareas, and in turn, one student per subarea. Still at the same stage, students had contact with the concept of Completeness Index proposed by Rosa [4], which consists of a set of urban indicators that together contribute to the complete-ness and quality of urban spaces with emphasis on the streets. The students used the technical support ViconSAGA application to capture their perception and cognition in field camp, and also incorporating the concepts of topophilia and topophobia [18]. While registering their opinions, they were also instructed to mark the identified completeness indicators. The use of ViconSAGA could be directly in their mobiles or tablets, but some of them preferred registering on paper and pictures, and use a browser on a computer in a posterior time, in their home, due to insecurity risks of been stolen on street. The initial visualization point was the Sete de Setembro Square, an urban landmark city, and students scrolled through the tabs: (i) “locate”, in which they should chose a position in the record (point); (ii) “fill in”, in which they should mark the indicators identified in the section analyzed, and could register comments; and the tab (iii) “image”, in which they could insert photos. A total of 224 records were made (Fig. 2). In parallel to spatial analysis, students learned about regulations and urban legislation, to understand the impact of urban laws and parameters in the land use and city scape of Belo Horizonte. In the geoprocessing and spatial analysis stage, the diagnosis and analysis of completeness indicators was performed. The students developed an important work of creating maps in the EA-UFMG Geoprocessing Laboratory, considering social, environmental, land use and volumetric landscape aspects, identifying main characteristics, vulnerabilities and potentialities of the area, with emphasis on the 12 completeness indicators. Students created an urban analysis map for each indicator in ArcGIS, resulting in 12 thematic maps based on available spatial data (Fig. 3). From the 12 specific maps, 4 Multicriteria Analysis Weighted Sum maps were prepared in VistaSAGA (Fig. 4), for the contexts of environment, movement and place, and a general synthesis. The weights applied in the completeness indicator variables were discussed with students in a Delphi consultation (Table 1). For the final synthesis, the same importance was adopted for all 3 contexts, generating a global diagnostic scenario regarding the completeness indicators for the central area of Belo Horizonte (Fig. 5).

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Fig. 2. Vicon SAGA interface with the records and subdivision of the study area.

Fig. 3. Set of thematic maps created in ArcGIS for the diagnosis of the study area - Central Area of Belo Horizonte.

In the co-creation stage, a Geodesign workshop was held on in the classroom, dividing the students into 3 groups. They were first asked to do the reading enrichment, that is the analysis of maps followed by the annotations of alerts, additional information, and general comments. In the second step, also in groups, they were asked to create ideas as diagrams, associating them with a title, a description and informing to which completeness indicators it could contribute to (Fig. 6). The groups worked in a cycle,

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Fig. 4. Multicriteria Analysis Maps for: (i) Environmental, (ii) Movement, and (iii) Place.

Table 1. Weights assigned for the multicriteria analysis Indicators

Weights

Contexts

Weights

street afforestation

20

environment

33,33

place

33,33

movement

33,34

efficient drainage

20

environmental comfort

20

landscape quality

30

active facades

25

flexibility of uses

25

universal accessibility

25

permanence spaces

25

road capacity

15

road safety

25

mode connectivity

30

active mobility

30

going from one context to the other (environment, place and movement). To measure dynamically the impact of the ideas, GISColab provided a widget with a histogram

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Fig. 5. Multicriteria Analysis Map: Synthesis Indicators of Urban Completeness.

for monitoring the distribution of number of ideas per completeness indicator, so that students could control their performance during the workshop (Fig. 7).

Fig. 6. Proposition of ideas: geodesign workshop in the classroom.

Finally, in the last stage the students were asked to develop individually an urban design, as a consolidation and application of the values and knowledge built throughout the course. The students developed urban design proposals contemplating the completeness indicators and based on the ideas previously collectively negotiated in the workshop. The graphic representation was free and each student had only to de-scribe their ideas briefly and textually. The results of this stage were solid, demonstrating the students’ reliability in proposing solutions to the identified problems in qualified proposals in terms of completeness indicators.

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Fig. 7. Context interface in the GISColab platform.

4 Results and Discussion The data collected in the survey field by the students using ViconSAGA was systematized and analyzed in maps of Kernel Density, resulting 12 maps of the spatial distribution, one of each indicator. These maps were combined in 3 syntheses, according to the contexts of environment, movement and place, and a final combination of the 3 contexts was also produced (Fig. 8). From this analysis, it could be seen that the distribution of the existing conditions of completeness indicators along the study area were concentrated in some axes, and were considered the more qualified area also in the perceptions students registered. In this sense, the students learned about different geospatial analyses: a technical analysis composed by official public data, and a analysis resulted from field camp that they registered using technological VGI tool. In both cases, they produced 12 initial maps, followed by 3 multicriteria synthesis map and a final synthesis map. They learned about knowledge driven and data driven analysis [19]. The time allocated to the final task (urban design) was very short, just being 3 classes. However, it was possible to observe that the training acquired by the students in earlier stages (reading the territory by perception and cognition, data representation through field collection and mapping by geoprocessing, multicriteria analysis for understanding the existing place relationships, and geodesign stage for the collective co-creation of initial ideas) was fundamental for the execution of this final activity. In the final stage, the students showed ability to elaborate complex and qualified proposals, which resulted from well-conducted previous processes. In the final proposals prepared by the students, some areas were presented in more than one idea, such as solutions for João Pinheiro Avenue and Andradas Avenue. It can be seen in the proposals that some indicators were more frequent than others, being landscape quality the most explored, and, on the other hand, road capacity being the least explored indicator (Fig. 9). In this way, when defining the importance and weights to the indicators in multicriteria analysis, the environmental context was the most relevant (43.04%), followed by the place context (29.11%) and finally the movement context (27.85%) in the final proposals. All proposals contemplated completeness indicators,

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Fig. 8. Kernel Density Maps from Vicon SAGA records.

and students justified their ideas using the previously constructed maps, evidencing the importance of measurable urban metrics in the project teaching-learning process.

Fig. 9. Frequency and importance analysis of completeness indicators in urban design final proposals.

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5 Conclusions The framework and steps proposed for the course allowed the students to consolidate and build knowledge, while they passed through the methodological stages (in class hours) of urban reading (32h), regulations and urban legislation (12h), geoprocessing and spatial analysis (36h), geodesign as a co-creation process (20h), and urban design work (20h). There was a progressive expansion in the understanding of the theme of urban planning on a local scale. In this way, the individual proposal stage, the last one, which is usually more difficult and developed in many hours, happened in a more organic way, resulting from the qualification and understanding previously built. The use of measurable criteria, such as completeness indicators during the geodesign workshop, favors that the processes were guided, presenting objectives and goals to be met. They used defensible and clear criteria to create ideas, for the judgments and of proposals, to measure the impacts of the suggested ideas, as well as a support to decision-making in the negotiation and proposals acceptance. It is important to highlight that the use of different technological applications was not a problem, as all of them had the condition of interoperability. It was possible to go, for example, from ViconSAGA and from VistaSAGA and to ArcGIS, and from them to GISColab. Thus, learning about geoinformation technologies and geospatial data was also favored throughout the course in a practical and applied way. Finally, the students were able to learn about the role of the architect and urban planner as a decoder of the collective will, as a team member and in co-creation activities, and finally, the importance of the moment when they could and should have an authorial action, bringing their individual creativity as a development to the previously created collective agreement. Acknowledgment. The authors thank FAPEMIG through the project FAPEMIG - APQ-00779– 22 and FAPEMIG PPM-00368–18. Also, for the doctoral research financial support from CNPq (141092/2021-1) and from Graduate Program in Geography (PPGGEO/IGC-UFMG).

References 1. Gehl, J.: Cidades para pessoas, Perspectiva, São Paulo, SP (2015) 2. Moura, A.C.: O Geodesign como processo de co-criação de acordos coletivos para a paisagem territorial e urbana, in Ladwig, N.I. & Campos, J. B. (eds), Planejamento e gestão territorial: o papel e os instrumentos do planejamento territorial na interface entre o urbano e o rural, UNESC, Criciúma, SC, pp. 16–59 (2019) 3. Steinitz, C.: A framework for Geodesign: changing geography by design. Esri Press, Redlands (2012) 4. Rosa, A, Moura, A.C, Fernandes, B.: Geodesign teaching experience and alternative urban parameters: using completeness indicators on GISColab Platform. In: Gervasi, O., Murgante, B. (eds) Computational Science and Its Applications – ICCSA 2022. Lecture Notes in Computer Science, vol 13379. Springer, Cham (2022) 5. Goodchild, M.: Citizens as sensors: the world of volunteered geography. GeoJournal 69, 211–221 (2007)

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6. Davis Jr, C, Moro, M, Matevelli, G, Machado, N.: Contribuições voluntárias: impactos potenciais dos cidadãos online e seus dispositivos móveis. In: Moura, A. C. M. (Org.). Tecnologias de Geoinformação para Representar e Planejar o Território Urbano. 1ed. Rio de Janeiro (RJ): Editora Interciência, p. 23–34 (2016) 7. Miller, W.: Introducing Geodesign: The Concept, p. 36. ESRI Press, Redlands (2012) 8. Dangermond J (2009), GIS: Designing our future. ArcNews, Summer 9. Ervin S (2011), A system for Geodesign. Keynote. Abstract. pp. 158–167 10. Vicon SAGA Homepage, https://viconsaga.com.br, last accessed 2023/06/05 11. Moura, A.C., Marino, T., Ballal, H., Ribeiro, S., MOTTA, Silvio R,: Interoperability and visualization as a support for mental maps to face differences in scale in Brazilian Geodesign processes. Rozwój Regionalny i Polityka Regionalna 35, 89–102 (2016) 12. GISColab Homepage, http://www.giscolab.com/geodesign/#/, last accessed 2023/06/05 13. Moura, A.C., Freitas, C.: Scalability in the application of geodesign in Brazil: expanding the use of the Brazilian geodesign platform to metropolitan regions in transformative-learning planning. Sustainability 13(12), 6508 (2021) 14. Vista SAGA Homepage, http://liga.ufrrj.br/downloads/, last accessed 2023/06/05 15. Da Silva, J.X.: Geoprocessamento para análise ambiental (apostila do Curso de Especialização em Geoprocessamento - Midia CD-rom), p. 15. Lageop, Rio de Janeiro (1999) 16. Lynch, K.: The Image of the City. The MIT Press, Cambridge (1960) 17. Cullen, G.: Townscape. The Architectural Press, London (1961) 18. Tuan, Y.: Topofilia: um estudo da percepção, atitudes e valores do meio ambiente. DIFEL, São Paulo (1980) 19. Bonham-Carter, G.: Geographic Information Systems for Geoscientists: Modelling with GIS. Elsevier (1994)

Geodesign: (a Personal) Retrospective, and Perspectives Michele Campagna(B) University of Cagliari, Cagliari, Italy [email protected]

Abstract. The paper presents a critical retrospective of the author’s experiences on the application of the geodesign methodology in spatial planning research, education, and practice. Referring to two main case studies re-iterated along several years in different contexts, the benefits of the approach are highlighted, as well as limitations. The benefits are particularly evident in relation to both the knowledge-building and design process, and the development of skills, capacity building, and innovation of practices, multi-actor collaboration, and consensus building. However, more time will be needed for careful ex-post evaluation which may confirm in the future the quality of the final design products and their implementation, as well as the ability of the involved local communities to support adaptive processes of sustainable transformation of the territory in the medium and long term. The future research directions, therefore, beside covering the monitoring and evaluation of the ex-post impacts of the results of past experiences, should focus on the current challenges of sustainability, and, on the impact of the design on climate change. While early geodesign studies proved effective in integrated strategic spatial planning and design and adaptive planning and governance of urban and territorial systems, integrating the principles and the values of strategic environmental assessment, further research is still needed to understand the applicability of the concept in different contexts with regards to scale, or in the making of traditional planning instruments which still characterize consolidated planning systems, or vice versa, to what extent, geodesign may affect it evolution, and under what circumstances. Keywords: Geodesign · Adaptive Planning · Strategic Planning · Sustainability · System-thinking · Sustainable Planning

1 Introduction Current sustainability challenges require urgent actions to contribute at the local level to solving serious global issues that treat the terrestrial ecosystem from the environmental, social, and economic point of view: climate change, migrations, consumption of resources, production of pollutants, population consistency and distribution, geopolitical conflicts, pandemics, are just some of the most serious issues we are currently facing. How do we address these challenges locally? How may spatial planning at the local level contribute to rebalance the global human-environment relationships? © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 114–121, 2024. https://doi.org/10.1007/978-3-031-54118-6_11

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Policies at European level have been strongly oriented towards environmental, social, and economic sustainability, particularly in recent years when the COVID19 pandemic and the war in Ukraine have further worsen previous, already precarious, socio-economic and environmental conditions. The EU green and digital transitions are, at least in principle, ambitious examples in this direction. However, addressing ecological, social, and economic crises requires the development of strategies and actions to be developed and implemented through collaboration and partnership, although often in conditions of conflicting interests and objectives. At the local level, there is a need for innovation in order to innovate towards more adaptive forms of spatial planning, that may replace established models which are no longer adequate to respond to global dynamics characterized by complexity and uncertainty, and which have major negative impacts. In this sense, the concept of resilience is changing from an absolute perspective to an evolutionary one, for the construction of which it is necessary in fact to refer to innovative models of adaptive planning (Davoudi, 2021). In a context, such as Italy, characterized by urban planning regulations based on assumptions now largely outdated, in their inadequacy to promptly react to the current challenges of sustainability, the diffusion of strategic planning and Strategic Environmental Assessment (SEA) have brought elements of innovation in recent decades. Nevertheless, the results of their application are often below expectations. The SEA practices often fail to properly apply its principles and expected outcomes. The potential for knowledge enrichment in spatial planning and decision-making is difficult to appreciate in substantive forms, as SEA often turn out to stay confined within bureaucratic boundaries. The desired construction of design alternatives informed by environmental considerations and savvy use territorial resources promoted by the SEA is difficult to be appreciated in explicit forms in the practice, as well as are explicit responsibility and transparency conditions. In addition, despite their availability, the adoption of innovative digital tools for planning support is often overly limited in the practice, postponing the future evolution of professionals towards a new paradigm of digital planning (Batty & Yang, 2022), and limiting the potential innovation in supporting communication, collaboration, or quantitative impact assessment, to name but a few of the underlying principles of SEA. Addressing these operational issues would already provide an important contribution to the role of spatial planning with regards to the green and digital transition, and, in general terms, would enable to develop more responsive solutions to sustainable spatial development issues. The most recent policies on sustainable spatial planning include substantive aspects related to the design (as a noun) of territorial systems such as housing, mobility, health, well-being, safety, consumption, land uses, etc. to be all oriented in the “green” sense, as well as design (as a noun) process requirements related to governance, collaboration, leadership, accessibility, equity, democracy, transparency, participation, digitalization, etc. The question is however still open on how current local practices may combine the two complementary dimensions of design, which are often tied to different disciplinary approaches, in order to achieve, in principle largely agreed, sustainable development

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goals. Strategic planning - defined as a transformative process, guided by public initiative but collaborative and open to the community, capable of integrating socio-spatial processes based on shared visions or frameworks of reference, synergistic coherence of the actions and of the means of implementation that define places and their possible futures (Albrechts, 2017)- can provide a more actual and effective approach in this regard. It is with strategic planning, in fact, that a variety of public and private sector actors and stakeholders meet in new institutional contexts to define future development scenarios that integrate interrelated strategies in order to provide a coherent input to the management of changes (Hersperger et al, 2019). Hence, this appears to be the appropriate tier in the spatial governance framework where, perhaps more than in others, the substantive and the procedural dimensions can be integrated into more sustainable spatial planning processes, towards the construction of more equitable development scenarios for the entire local community through collaboration.

2 The Geodesign Approach In the last decade geodesign gained momentum in academia as an approach able to mediate the accounting of the environmental dimension of planning with collaboration and negotiation, relying on digital computational and communication technologies. Geodesign can be defined as a set of techniques and enabling technologies for planning built and natural environments in an integrated process, including project conceptualization, analysis, design specification, stakeholder participation and collaboration, simulation, design alternatives creation and impact evaluation (among other stages). Geodesign applies system-thinking and makes the relationships between design and its geographical context explicit, as the design is dynamically related to a multi-scale digital computational twin of territorial systems. The geodesign methodology approach mainly refers to the framework proposed by Carl Steinitz (2012). If it is true that in the literature other methodological planning and design frameworks may be found, the Steinitz’s framework for geodesign is particularly effective in that it is general enough to be applied to a variety of theoretical models and operational contexts in planning, while providing a comprehensive and robust guide for the construction of design processes. The Steinitz framework for geodesign entails - with reference to a set of territorial subsystems (e.g. green and blue infrastructure, transport, residence, cultural heritage, etc.) - the iterative construction of six models: the representation model describes the evolution of the study area from the past to the present (intended either as the starting moment of a geodesign study or last date for which up to date data are available); the process model describes the probable or possible evolution of the territorial system (depending on the considered time span and possible underlying uncertainties) without considering any design change: it represents the donothing alternative; the evaluation model defines the possible need for changes with regards to their suitability in space (e.g. evaluation maps); the change model represents possible design alternatives; the impact model simulates the impacts of those alternatives; and lastly the decision model defines the decision-making context. The robustness of the geodesign framework to support the SEA-plan-making process was discussed by Campagna and Di Cesare (2016).

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International experiences based on the application of the Steinitz’ framework have recently produced effective process and workflows and digital tools to support their implementation, including the so-called “geodesign workshop” which turn out to be particularly robust in strategic spatial planning. Geodesign workshops usually take as input the output of the first three models, which constitute the knowledge building base for a geodesign study, and iteratively produces alternative scenarios, and, through collaboration and negotiation, leads to consensus with regard to a final agreed scenario. The explicit link between knowledge and decision is obtained by using the evaluation maps (Campagna et al., 2020a, par. 3): the latter represent a central element of this methodology, an element which is often unfortunately limited or absent in many traditional urban plans. Typically, a geodesign workshop applied to strategic planning can produce effective results with the collaborative involvement of several dozens of participants (i.e., community actors) and it can do that in very short time (i.e., equivalent to approximately to two working days). A geodesign workshop can be supported by several digital tools, but the one which proved most effective in research, education, and practice is the Geodesignhub web-based planning support system, which, in fact, was designed to implement the geodesign framework (Ballal, 2015) in full-digital settings. The following section summarizes the main feature of various case studies of implementation of geodesign workshops with Geodesignhub by the author, in research, education, and in the planning practice.

3 Case Studies: (a Personal) Retrospective, and Prospective In this section, several geodesign studies conducted by the author are described comparatively aiming at identifying successful methodological and operational elements, which may contribute to addressing some of the most pressing challenges inherent in the development of adaptive sustainable strategic spatial planning processes, in the respects outlined in the introduction. 3.1 Retrospective Starting from 2016 a series of design studies involving geodesign workshop were developed by the author in different areas of Sardinia, at different scales, with different objectives, and in different working contexts. Altogether, these case studies offer useful materials to evaluate the potential of the geodesign approach in planning research, education, and practice (and, in particular, in strategic spatial planning). The two main study areas were the Metropolitan City of Cagliari (CMC) and the Gulf of Oristano Municipalities (OGMun), where a strategic study on sustainable tourism development was conducted. The study area of the CMC has been the object of several iterations of the study, initially in a research context, then in planning education, and, most notably, in the making of the Strategic Plan of the Metropolitan City of Cagliari, approved thereafter in 2021. Table 1 summarizes the main features of the case studies. The first CMC case study in 2016 was developed in a research context. In this case the main value in the application of the geodesign methodology was to approach exploratively a new project at an unusual scale, that of the CMC, which had essentially

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Case Study

CMC 2016

CMC 2018

CMC 2017–23

OGMun 2019

CMC 2021

Context

Research

Education

Training

Strategic Tourism Planning

Strategic Planning

Focus

Methodology, design

Methodology, design

Methodology

Design, capacity building

Design, capacity building

Tools

Geodesignhub Geodesignhub Geodesignhub, Zoom

Geodesignhub

Geodesignhub, Zoom

Mode

Presence

Presence

Presence/online Presence

Online

Duration

15 h in 2 days

5 × 3 h in 2 weeks

9 h in one or more sessions

About 16 h in 3 days

4 × 3 h in 2 weeks

100 + BSc and MSc Students of Engineering / Architecture

Educators, Researchers (20–40)

5 municipalities (20 + decision-makers and technical staff), enterprises, NGOs

17 Municipalities (30 + Decision-makers and technical staff)

Participants Researchers (30 +)

never been previously considered in terms of design by the local scientific, technical, and public administration community. Previous studies had in fact focused on the area of Cagliari and the municipalities of the first ring, which is remarkably smaller than that of the current CMC. The establishment of the CMC in 2016 (LR Nº 2, 2016) with its seventeen municipalities introduced a totally new working scale compared to the context of traditional planning practices in Sardinia, and the case study represented a first exploratory experience to investigate the relevance of territorial phenomena and design scenarios at this new scale. The case study also allowed to test the application of the methodology and to train young researchers, as well as some technical staff from the public administration as well as some freelancers who participated in the project workshop. A research context can be considered very appropriate for a first test as learning exercise for those approaching a geodesign study for the first time, as it was in the case of this authors and many others. The second iteration of the case study on the CMC has been developed within the education program of the Urban Planning course of the MSc in Civil Engineering, and the Geodesign Course of the BSc in Architecture at the University of Cagliari. More than one hundred students participated to the two studio classes each of which produced a set of scenarios developed by the students collaboratively (Campagna et al., 2020b). In particular, the aim of the project workshops was to assess the impact of the introduction of technological innovations in the territorial project with regards to selected territorial subsystems (e.g., green and blue infrastructure, agriculture, transport, trade

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and industry, energy, residence, etc.) in line with the International Geodesign Collaboration assumptions. The learning curve by the students was very positive in relation to both understanding the spatial planning and design approach integrated with systemthinking at the territorial scale and using state-of-the-art digital planning and design tools. The collaborative design methodology, in addition, enriched the design methodologies toolbox of the students, who would normally be trained to design individually, or in small working groups, with an anticipatory approach, typical of large-scale design in architecture and civile engineering. In the period from 2017 to 2023, moreover, the CMC geodesign study has been used internationally in many geodesign tutorial workshops for educators and researchers in satellite conference events in presence (e.g. Digital Landscape Architecture, DLA, https///www.dla-conference.com/), and online, as part of the International Geodesign Collaboration (IGC) networking activities, or in the training of educators, students, and young researchers during scientific visits to universities in Italy and abroad, or during intensive schools for PhD students. In all these cases, the goal of the application of geodesign intensive tutorial workshops (usually limited to six to nine hours) was the learning of the methodology and of new digital planning and design support tools by the participants. In the case study of the geodesign workshop for the sustainable strategic tourism development planning in the municipalities of the Gulf of Oristano, which was the first real-world planning practice case dedicated to supporting public administrations and stakeholders of the local community, the main goal of the workshop was to support dialogue and consensus building under conditions of diverse and potentially conflicting spatial development objectives. The workshop was attended by elected representatives and technical staff from the local authorities, as well as by representatives of private enterprises and NGOs. The workshop was held in presence for a total of about sixteen hours divided into two working days. The evaluation by the participants of the application of the geodesign methodology was overall very positive, underlining the fact that the collaborative design activity facilitated communication and constructive dialogue between public administration, enterprises, and NGOs, to a substantially higher level than in the traditional practice. The working methodology allowed to explore new development perspectives for the study area, helping to reach consensus on a shared and coherent development scenario. Last in order of time, and a most relevant example in terms of complexity both with regards to the territorial dynamics and to the decision-making process, was the geodesign workshop for the Strategic Planning of the CMC. The latter involved the CMC’s seventeen municipalities represented both by elected representatives and technical officials. The workshop was a central element in the making of the CMC Strategic Plan, within which process it was developed. With the geodesign workshop, the Municipalities had the opportunity to express their local point of view, both in relation to the wider territorial area and the related wider development objectives of the CMC. The workshop took place in four plenary meetings of three hours each over two weeks, which allowed participants to share their local planning perspectives and integrate it into the wider scenario of the whole CMC area. More than two hundred local projects and policies were collected and integrated in an agreed design scenario during the workshop, for which consensus was

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reached through negotiation on four priority levels. The project results of the workshop were incorporated into the final documents of the strategic plan, which was approved in its final version a few months later, in July 2021. 3.2 Prospective Two new case studies are currently under development aiming at testing new application contexts for geodesign and to assess their effectiveness. The first case study under development represents a local grass-root planning initiative in the coastal area in Quartu Sant’Elena (Italy). The study area is characterized by a low density coastal residential development, affected by occasional illegal building phenomena, and limited or poor urban infrastructures, in an area of sensitive landscape value. The objective of this project is to involve active citizenship in a geodesign workshop that, starting from the assessment of local issues, expectedly will allow participants to develop an integrated strategic spatial vision for the sustainable development of the wide coastal area, building an agreed development scenario, and, at the same time, building capacities for the local community to improve the dialogue with the local public administration. The second case study currently under development deals with the whole regional area of Sardinia, and it is a local contribution to an international research project coordinated by the IGC, called the Climate Change Grand Challenge (GC2, https://www-igc ollab.hub.arcgis.com/pages/gcgc). The GC2 project has the ambitious goal of exploring planning and design solutions to reduce anthropogenic carbon emissions and protect and strengthen ecosystems and carbon storage. Through a shift of scale between local and global studies, the objective is to study spatial design solutions aimed at obtaining a negative carbon cycle balance in which the amount of carbon emitted into the atmosphere is lower than that sequestered by the territorial system. This base research project ultimately aims to investigate concepts, methods, and tools to develop local designs that may contribute to a global sustainable design.

4 Discussion and Conclusions The geodesign studies described in synthesis in this paper highlight a flexible geodesign methodology approach that allows to build agile and open spatial planning design processes based on multi-actor collaboration, also thanks to the support of state-of-the-art digital planning support tools with user-friendly interfaces. The variety of actors, with or without technical background, with or without digital skills, more or less accustomed to design practices, coming from different geographical and socio-cultural contexts, which took part in the case studies, shows how technology adapted to methodology, not viceversa, can effectively support planning, and facilitate fast and effective collaboration and cognitive mediation. The workflow of the geodesign workshop has proved effective in achieving the objectives of the studies, both in research, in education, and in the real-world planning practice; and it enabled to do that in extremely short time. The model is therefore particularly suitable to support adaptive strategic planning where speed, rather than detail, is an added value. Still, the quality of design results and their implementation is to be

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further assessed with respect to its application to the planning practice, which in this case may need time. However, the speed of consensus-building by groups of diverse actors is perhaps the most interesting feature as rapid iterations of the same geodesign study can be cyclically repeated with the acquisition of more information and knowledge as territorial conditions change, thus addressing gradually the uncertainty that characterizes many of the most serious current sustainability challenges. This appears to be an important feature, in the transition from traditional to new adaptive processes aimed at addressing the resilience of territorial systems with an evolutionary approach.

References Albrechts, L.: Strategic planning as a catalyst for transformative practices. In: Haselsberger, B. (ed.) Encounters in planning thought, pp. 184–201. Routledge (2017) Ballal, H.: Collaborative Planning with Digital Design Synthesis. Ph. D. Thesis, UCL (University College London), London, UK (2015) Batty, M., Yang, W. (eds) A Digital Future for Planning – Digital Task Force for Planning. ISBN: 978–1–9162056–2–8. (2022) https://digital4planning.com/a-digital-future-for-planning/ Campagna, M., Di Cesare, E.A, Cocco, C.: Integrating Green-Infrastructures Design in Strategic Spatial Planning with Geodesign. Sustainability, 2 (2020a) Campagna, M., Cocco, C., Di Cesare, E.A.: New scenarios for the Metropolitan City of Cagliari, Sardinia, Italy. In Fisher T., Orland B., & Steinitz C. (eds) The International Geodesign Collaboration: Changing Geography by Design. ESRI Press, Redlands, CA (2020b) Campagna, M., Di Cesare, E.A.: Geodesign: Lost in regulations (and in practice). In Papa R. Fistola R. (eds.) Smart Energy in the Smart City. Springer (2016) Campagna, M., Steinitz, C., Di Cesare, E.A., Cocco, C., Ballal, H., Tess, C.: Collaboration in planning: The Geodesign approach. Rozwój Regionalny i Polityka Regionalna 35, 55–72 (2016) Davoudi, S.: Resilience, Uncertainty, and Adaptive Planning. In: Peker, E., Ataöv, A. (eds.) Governance of Climate Responsive Cities. TUBS, pp. 9–19. Springer, Cham (2021). https://doi. org/10.1007/978-3-030-73399-5_2 Hersperger, A.M., Gr˘adinaru, S., Oliveira, E., Pagliarin, S., Palka, G.: Understanding strategic spatial planning to effectively guide development of urban regions. Cities 94, 96–105 (2019) Nyerges, T., et al.: Geodesign dynamics for sustainable urban watershed development. In Sustainable Cities and Soc. 25, 13–24 (2016) Pettit, C.J., et al.: Breaking down the silos through geodesign – envisioning Sydney’s urban future. Environment and Planning B: Urban Analytics and City Science 46(8), 1387–1404 (2019) Rivero, R., Smith, A., Ballal, H., Steinitz, C.: Promoting Collaborative Geodesign in a Multidisciplinary and Multiscale Environment: Coastal Georgia 2050, In Buhmann E., Ervin S., Pietsch M. (eds) Digital Landscape Architecture 2015, Herbert Wichmann Verlag, Berlin (2015) Steinitz, C.: A framework for geodesign: changing geography by design. ESRI Press, Redlands, CA (2012) Wahl, D.C.: Unpublished paper “Design and Planning for People in Place: Sir Patrick Geddes (1854–1932) and the Emergence of Ecological Planning, Ecological Design, and Bioregionalism”. (2017) Available at: https://designforsustainability.medium.com/design-and-planningfor-people-in-place-sir-patrick-geddes-1854-1932-and-the-emergence-of-2efa4886317e

Geodesign in the Teaching Process of Global Agreements: Sustainable Development Goals and Smart Cities Fabiana Carmo De Vargas Vieira1(B) , Tiago Mello2 and Ana Clara Mourão Moura1

,

1 Federal University of Minas Gerais, Belo Horizonte, Brazil

[email protected] 2 ICLEI – Local Governments for Sustainability, São Paulo, Brazil

Abstract. This paper presents an academic experiment report on the application of Geodesign in the context of Architecture and Urban Planning seminars, for both undergraduate and graduate programs. The idea is to test the methods for preparing planning professionals on dealing with contemporary global challenges. In this case study, different concepts, i.e., United Nations’ Sustainable Development Goals (SDGs) and smart cities, and different areas – Belo Horizonte and Florianópolis Island, Brazilian southeast and south municipalities, respectively – were utilized to test methodological functionalities, and to develop students’ skills. Initially, the group took lectures about the methodology, topics related to the studies, and study areas. Thereafter, the participants were supposed to co-create proposals considering their positive and negative impacts on the SDGs and the fulfillment of Smart Cities strategies. In the final step, the groups were asked to answer to a survey in which questions about Geodesign, SDGs, and Smart Cities were held, in order to understand the expansion of their knowledge regarding such themes. It was possible to identify a more conscious learning process about global agreements, mainly about SDGs, as Geodesign brought those discussions to the scale of their professional practice. The framework proposed and the use of Geodesign methods were suitable for their role as a teaching method. Keywords: Geodesign · Sustainable Development Goals · Smart Cities

1 Introduction The world is urban. According to the United Nations [1], 55% of the world’s population lived in cities in 2019, and the forecast is that this percentage will be 68% by 2050. World leaders, in 2015, at its headquarters to define an action plan to eradicate poverty, protect the planet and ensure that people achieve peace and prosperity: the 2030 Agenda for Sustainable Development, which contains a set of 17 sustainable development goals [2]. Belo Horizonte is the capital of the state of Minas Gerais, located in the Southeast Region of Brazil. The presence of the capital resulted in the urban density in its surroundings, forming the Metropolitan Region of Belo Horizonte. The city was initially planned, © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 122–133, 2024. https://doi.org/10.1007/978-3-031-54118-6_12

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but the development and sprawl expanded the initial area and resulted in a very dense city, with economic activities related to services. Florianópolis Island, in the south of the Atlantic Ocean, is an important tourist destination located in the state of Santa Catarina, in the South Region of Brazil. Both case studies, Belo Horizonte and Florianópolis, are considered digital cities, in the sense of Smart Cities, due to the presence of services related to Start-ups and level of technologies in services. Smart Cities are emerging in different parts of the globe, each limited by its own preestablished hierarchical level. However, it should be noted that the concept of smart is no longer limited to technological resources, but also includes sustainability and meeting social needs. Although there is still no single conceptual definition for them, these cities seek to be more sustainable: a characteristic suggested by the 2030 Agenda. Brazil has a history of social inequality; therefore, few cities can be considered as Smart Cities according to this new approach. This research focuses on the organization of Geodesign workshops in the cities of Belo Horizonte and Florianópolis Island. The main objective is to assess the educational process and training of professionals in the fields of Geography and Architecture and Urban Planning, specifically in terms of their ability to make urban planning processes using Geodesign principles. Additionally, the study aims to examine the integration of Sustainable Development Goals (SDGs) and proactive approaches to Smart Cities (SC) in the workshop participants’ learning experience. Undergraduate students in Architecture and Urbanism and graduate students in Geography from the Federal University of Minas Gerais and the State University of Santa Catarina took part in the workshops. Based on Geodesign workshops, it was measured the improvement and the develop the participants’ ability to understand the Sustainable Development Goals and their relationship with Smart Cities.

2 Concepts Rapid global urbanization, along with the world’s growing population of over 7 billion people, combined with the advancement of computing and the spread of the internet has resulted in a huge increase in the volume of digital data over the last few decades. This scenario gave rise to the concept of so-called “smart cities”. However, it is important to emphasize that the New Urban Agenda is aligned with a new approach, associating the concept of “smart” with qualified life, sustainable development and reduction of inequities, associating with the SDGs – Sustainable Development Goals. 2.1 Smart Cities Castells [3] states that from the 1970s onwards, the world underwent a major technological change, which resulted in the Information Technology Revolution, also known as the Third Technological Revolution of Humanity. With that, there was a great concern about how the big data would be stored and analyzed, as demonstrated by Moura [4] who says, “the excess of information, if not faced correctly, can lead to unsustainable conclusions, governed essentially by the apparatus technician”.

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Geoinformation technologies and the use of geospatial data, applying methodological models through geoprocessing, brought some applications and answers to this problem. Concomitantly, with the introduction of new technologies, the ICT (Information and Communication Technologies) stand out, which refer to a set of technologies that involve communication, processing and storage of information, covering a wide range of devices, software and networks. The exchange of data and communication between people, organizations and systems, facilitated the rapid exchange of information, the automation of tasks, collaboration in real time and the expansion of access to services and knowledge. Importantly, there are also challenges, such as security, privacy and digital exclusion issues. In the 1990s, the so-called digital cities emerged, which, according to Lemos [5] consisted of access to computers and the implementation of the internet in urban space. In that decade, the population began to have greater access to new technologies, facilitating their interaction in the network. The terms smart cities and big data emerged. Lemos [5] explains that “[…] intelligent refers to context-sensitive computerized processes, dealing with a huge volume of data (Big Data), cloud networks and autonomous communication between various objects (internet of things)”. The main meaning associated with smart is still to identify cities that have measurement intelligence and dynamic data production. These are examples of capturing the movement of people by sensors, for decision-making; capture of temperatures by sensors to define action strategies, among other examples [6]. Goodchild [7] came to think of “citizens as sensors” and Batty et al. [8] presented “smart cities of the future” in these terms. With the rapid progress of urbanization and information technology, new cities known as big cities have emerged, providing modernization in various aspects of people’s lives. But they also generated big challenges, such as air pollution, increased energy consumption, and traffic congestion [9]. A few years ago, it was impossible to think about solving complex problems, but nowadays, with the large-scale development of computational infrastructures, they provide knowledge about the variety of urban spatial big data [9]. In this way, governance increasingly appropriated technologies, mainly geospatial data, as a way to improve the service through databases, used to plan urban infrastructure as well as to provide services to citizens (Fig. 1). However, given the environmental and social vulnerabilities in large cities, it would not be appropriate to aim only at broad access to technologies, as the resource only makes sense if reverted to expanding the quality of life, based on sustainability. Thus, the principle of Smart Cities was approaching the expectation of intelligence not only as a technology for collecting and using data, but, above all, as a resource made available to meet the SDGs. The new concept, built by the European Commission, broadens the sense of smart city and associates it with the term sustainability. For them, a smart city is one that employs technology to ensure intelligent processes and enable people, companies and public management to act harmoniously [12]. Thus, the present study adopts the concept of the European Commission as a way of measuring development and favoring urban planning. In Brazil, the subject is still not widely discussed as a fundamental role in urban planning, cartography, or geography courses in academic settings. However, it is observed

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Fig. 1. Representation of Smart Cities. Source: Scientific American [10].

that in certain cities, such as Belo Horizonte, São Paulo, Rio de Janeiro, and Florianópolis, there are planning initiatives that involve the use of ICT and are moving towards the concept of smart cities. 2.2 Sustainable Development Goals In 2015, the United Nations Organization proposed the 2030 Agenda with “a global call to action to end poverty, protect the environment and climate and ensure that people, everywhere, can enjoy peace and prosperity”. In this document they present the 17 goals, arranged in 169 global goals, aim to achieve a more balanced life in the anthropogenic environment, with emphasis on life in cities (Fig. 2).

Fig. 2. Representation of SGD – Sustainable Development Goals. Source: UN [13].

The UN emphasizes that the SDGs are integrated and indivisible, correlated with each other, in a balanced way according to the four dimensions of sustainable development: economic, social, environmental and institutional [13]. The SDGs are divided into three main dimensions: economic, social and environmental. The UN recognizes that these dimensions are interconnected and interdependent, being essential to achieve sustainable development at the global level.

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The New Urban Agenda commits to adopting a smart city approach, considering the opportunities offered by digitalization, clean energy and advanced transport technologies. In addition, the goal is to provide alternatives that allow inhabitants to make more sustainable choices for the environment, thus boosting economic growth in a sustainable way, and improving the provision of services in cities [13] Thus, Agenda 2030 incorporates the smart city into the SDGs, allowing new technologies to create an innovative and sustainable urban environment aimed at improving the quality of life to citizens.

3 Materials and Methods The research was supported by a bibliographic review and the development of case studies in an experimental way, in the shape of Geodesign workshops. It was proposed as a way to encourage participants to get in touch with the principles of the SDGs and Smart Cities in their proposals, while learning about the co-creation of ideas for the future of a territory. Steinitz [14] points out a definition presented by the economist and political scientist Herbert Simon [15], as the most appropriate concept to define the expectations of planning: “every project that elaborates courses of action had the objective of replacing existing situations with situations envisioned”. Based on this principle, he was one of the authors who proposed Geodesign as a tool and method for the elaboration of projects for the city, satisfying the expectations and needs of the participants in shared planning. Thus, Geodesign is a project (design) and a planning method that can facilitate the joint work of citizens and the government, for decision-making, allowing a more democratic urban planning process. GISColab, a Brazilian web-platform that was initially proposed by GE21 Geotechnologies, and adapted to Geodesign workshops with scripts and widgets by Moura and Freitas [16, 17]. This tool has technical support an SDI (Spatial Data Infrastructure) available on the web, such as a WebGIS and optimized tools to support the working stages. It was planned in a flexible way in order to be adapted to different approaches and different frameworks, according to the specifics of the case study. GISColab is a set of tools based on OGC (Open Geospatial Consortium), which makes it possible to create scripts. Thus, a script was created to measure the association of ideas with the SDGs, based on WPS (web processing service) it means that, for each proposed idea, the SDG principles were associated, resulting in a dynamic histogram, which is automatically updated according to changes in the proposals. The methodological approach utilized [16] establishes the following stages: a) reading enrichment, in which the participants learned about the study area and took notes as alerts in the platform; b) creation of ideas, in which the groups draw their ideas in GISColab, using points, lines or polygons; c) discussion of ideas and voting, when the participants analyze, comment, discuss and vote on the proposals (Fig. 3).

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Fig. 3. Workshop method. Source: Moura & Freitas [16].

During the development of Belo Horizonte workshop, the participants received initial information about the Sustainable Development Goals, and were divided into groups to follow the steps proposed and to arrive to ideas evaluating their positive and/or negative impact on the SDGs. In the study carried out on the island of Florianópolis, the concept of Smart Cities was also added, and they were asked to consider the concept of smart quote according to the European Commission. At the end of both workshops, questionnaires were applied to verify the level of interest and knowledge of the participants on the topics covered by the workshops. The research was based on an exploratory process of gradual inclusion of resources, both with regard to the presentation of concepts and to the use of technological and methodological resources, in order to make the participants understand and apply the principles of SGD and Smart Cities.

4 Results and Discussions The experiences were carried out in an exploratory way, through two Geodesign workshops, held in Belo Horizonte and in Florianópolis Island with almost the same participants in both. The workshops were conducted in the classroom with the objective of verifying the impact and effectiveness of the Geodesign methodology in the teaching-learning process of urban planning. 4.1 Belo Horizonte and Florianópolis Island Workshop Both workshops followed the steps determined by Geodesign. However, in Belo Horizonte, the proposals were evaluated based on the SDGs, while in Florianópolis, in addition to analyzing the SDGs, it was also included the concept and values to be achieve to be considered a Smart City – innovative, sustainable proposals. In both case studies the participants worked on the contexts of social, economic and environmental tripod of sustainability.

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To facilitate the dynamics of the workshop participants were organized into groups, each with a leader responsible for drawing, writing observations and justifications on GISColab platform. The groups were divided into A, B, C and D, with the aim of having a controlled number of participants in each one. Groups A and B were composed of undergraduate Architecture and Urbanism students, group C of graduate students in Geography, and group D of local planners and researchers from Florianópolis Island. In the first day, in the step of Reading Enrichment, participants analyzed the study area and scored the needs of the place. In the second day of the workshop, the Creation of Ideas, the groups initially discussed the notes taken during the Reading Enrichment activity, after what they elaborated proposals for interventions and changes. The groups had to work in a cycle, designing ideas to the contexts of social, environmental and economic contexts. While creating ideas, they were asked to associate them with the SDGs, defining if they could bring positive or even negative impacts about each of the 17 goals. On the third day the discussed all the ideas, registering comments and additional suggestions in the platform to each proposal. Finally, on the fourth and last day, the participating groups evaluated the proposals and conducted a Voting process. Those proposals that received the majority of votes as “like” were separated as already selected, the ones with majority of “dislike” were separated as not approved, while the ones that were not with majority of yes or no were separated to be discussed again, considering possible changes, to be voted again. Figure 4 illustrates the final design, which was the result of negotiations and voting, incorporating ideas related to specific contexts. The image displays a script for measuring the SDGs, with the vote being highlighted in red.

Fig. 4. Script measurement of compliance with the SDGs. Summary result of the workshop in Belo Horizonte. Source: the authors.

When analyzing Fig. 5, one can see a significant number of proposals with positive impacts covering practically all objectives of SDG while the SDG3, which refers to

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health and well-being, got the highest number of proposals, followed by objectives SDG 11, SDG 10, SDG 15 and SDG 13. While the negative impacts were only 4 proposals, related to objectives SDG 9, SDG 14, SDG 15 and SDG16 (Fig. 5).

Fig. 5. Widget measurement of compliance with the SDGs, separated into positive impacts and negative impacts. Summary result of the workshop in Belo Horizonte. Source: the authors.

When analyzing the results of each context (environment, social and economic ones) of Florianópolis Island case study, all the SDGs were considered in positive impacts, mainly in the SDG 8, SDG 9, SDG 10, SDG 11 and SDG 17, and the negative impacts were related the SDG 6, SDG 9, SDG 14, SDG 15 and SDG 17 (Fig. 6). Participants answered to questionnaires without identifying themselves, in anonymous registration of their opinions. In the case of Belo Horizonte, 37% declared they didn’t have robust knowledge about the SDGs before the workshop, while 20% were the opposite, they had interest and knowledge on that, while 11% said they were not sure. When questioned if the experience increased their interest, 67% declared that agreed or totally agreed. In Florianópolis experience, 39% of them declared they didn’t have robust knowledge about the SDGs before the workshop, while 39% were the opposite: they had interest and knowledge on that, and the others 22% said they were not sure. When questioned if the workshop resulted in the increasement of their interest about SDGs, 78% of them strongly agreed and 22% agreed with this statement after the workshop (Fig. 7). Questioning about Smart Cities, in Belo Horizonte case study 61% of them totally agreed or agreed that they had robust information about it before the workshop, and 6% said they were not sure. About the increasement of the interest after the workshop, they didn’t answer. In the case study of Florianópolis, 61% declared they had robust information and interest about Smart Cities, 25% said they didn’t, while 14% said they

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Fig. 6. Widget measurement of compliance with the SDGs separated into positive impacts and negative impacts. Each context of Florianópolis: (a) environment (b) economy (c) social. Source: the authors.

were not sure. It is worth highlighting that 50% of the blank answers were recorded as an option. It should be noted that the Belo Horizonte study was conducted first, and the participants were almost the same at the second workshop. In the workshop on Florianópolis Island, a total of 40% of the participants agreed or fully agreed that their interest and knowledge had increased after the experience. (Fig. 8).

5 Final Considerations It is possible to say that the inclusion of the SDGs and Smart Cities themes had a different assimilation by the participants. Belo Horizonte group declared they had interest and knowledge about SDGs before the workshop. Florianópolis group presented and equilibrium from having or not, but both expanded the interest – mainly in Florianópolis. When questioned about Smart Cities, both groups declared they had knowledge and interest about it, but just the group from Florianópolis had significantly increasement of interest, while the group from Belo Horizonte didn’t answer anything, meaning they were in a worst condition, not able even to construct a position or opinion. Although most part of the group did not have contact with Geodesign, the platform and the method itself show to be accessible for the public involved.

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Fig. 7. (a) Question: Before the workshop, I knew about the SDGs. (b) Statement: After the workshop the knowledge and interest about of the SDGs increased.

About the use of SDG as reference to construct proposals, there were a significant number of ideas with positive impacts, covering almost all SDG goals. The most mentioned SDGs were those related to health and well-being (SDG 3), followed by green cities and communities (SDG 11), reducing inequalities (SDG 10), combating climate change (SDG 13) and life on earth (SDG 13). SDG15). On the other hand, the proposals that could, somehow, bring negative impacts, were very few, but it was important to recognize they exist, to plan mitigations of possible problems. As the Development Goals are presented individually, but in fact there is a strong relationship between them, the participants, when making projects, realized that when planning considering an SDG, they could also have results in others.

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Fig. 8. (a) Question: Before the workshop, I knew about Smart City. (b) Statement: after the workshop, the knowledge and interest about Smart City increased.

The results also showed that enthusiasm for Smart Cities was lower if compared to the SDGs, indicating the need to explain more about this concept during the workshops. Other possibility that might explain such situation relies on the fact that the SDGs have more tangible measurements of indicators when compared to the Smart Cities concept. After all, these insights underscore the importance of deepening understanding and awareness of the SDGs and Smart Cities in order to promote more sustainable urban planning according to global development goals. Moreover, Geodesign showed to be an interesting teaching method, and also a possibility for planning sustainable, innovative, and collaborative alternative futures.

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References 1. UN: UN-Habitat: world population will be 68% urban by 2050. 1 July 2022. Homepage https://brasil.un.org/pt-br/188520-onu-habitat-população-mundial-será-68-urban-until2050 Last accessed 5 May 2023 2. ONU: Nova Agenda Urbana. Rio de Janeiro: ONUHabitat . Homepage (2016). http://hab itat3.org/wp-content/uploads/NUA-PortugueseBrazil.pdf. Accessed in 22 Oct 2020 3. Castells, M.: Fim de Milênio, 2nd edn. Paz e Terra, São Paulo (1999) 4. Moura, A.: Contribuições Metodológicas do Geoprocessamento à Geografia. Thesis, Ph.D. Federal University of Rio de Janeiro (2000) 5. Lemos, A.: Cidades inteligentes: de que forma as novas tecnologias — como a computação em nuvem, o Big Data e a internet das coisas — podem melhorar a condição de vida nos espaços urbanos? Executive GV, São Paulo, vol. 12, no. 2, pp. 46–49, Jul/Dec (2013) 6. Batty, M.: Inventing Future Cities. The MIT Press, Cambridge, MA (2018) 7. Goodchild, M.F.: Citizens as sensors: the world of volunteered geography. GeoJournal 69, 211–221 (2007). https://doi.org/10.1007/s10708-007-9111-y 8. Batty, M., Axhausen, K.W., Giannotti, F., et al.: Smart cities of the future. Eur. Phys. J. Spec. Top. 214, 481–518 (2012). https://doi.org/10.1140/epjst/e2012-01703-3 9. Zheng, Y. et al.: Urban Computing: Concepts, Methodologies, and Applications. ACM Transactions on Intelligent Systems and Technology, vol. 5 (2014) 10. Scientific America: The Smart City: More Than Just Tech. Homepage (2023). https://www.sci entificamerican.com/custom-media/pictet/a-smart-city-more-than-just-tech/. Last accessed 5 May 2023 11. UN: Sustainable Development Goals United Nations Department of Global Communications. Homepage (2020). https://www.un.org/sustainabledevelopment/wp-content/uploads/ 2019/01/SDG_Guidelines_AUG_2019_Final.pdf. Last accessed 5 May 2023 12. Comissão Europeia: Cidade Inteligentes. Homepage (2021). https://ec.europa.eu/info/eu-reg ional-and-urban-development/topics/cities-and-urban-development/city-initiatives/smart-cit ies_en#smart-cities-marketplace. Last accessed 5 May 2023 13. UNIC Rio: Transformando Nosso Mundo: A Agenda 2030 para o Desenvolvimento Sustentável. Translated by the United Nations Information Center for Brazil (UNIC Rio). Homepage (2015). https://sustainabledevelopment.un.org. Last accessed 15 May 2023 14. Steinitz, C.: A Framework for Geodesign. Changing Geography by Design. Redlands, California (2012) 15. Simon, H.A., Barenfeld, M.: Information-processing analysis of perceptual processes in problem solving. Psychol. Rev. 76(5), 473–483 (1969). https://doi.org/10.1037/h0028154lastacc essed2023/05/05 16. Moura, A.C.M., Freitas, C.R.: Brazilian geodesign platform: WebGis & SDI & geodesign as co-creation and geo-collaboration. In: Lecture Notes in Computer Science, 1st edn, vol. 12252, pp. 332–348. Springer International Publishing: Berlin/Heidelberg (2020) 17. Moura, A.C.M., Freitas, C.R.: Scalability in the application of geodesign in Brazil: expanding the use of the Brazilian geodesign platform to metropolitan regions in transformative -learning planning. Sustainability 13(12), 6508. https://doi.org/10.3390/su13126508

Geodesign for Open Spaces Management in Mining-Dependent Urban Settlements Luiz Glück Lima1(B) , Camila Marques Zyngier2 , Christian Freitas3 and Ana Clara Mourão Moura4

,

1 Princeton University, Princeton, NJ 08544, USA

[email protected]

2 Instituto de Educação Continuada, Pontifícia Universidade Católica de Minas Gerais,

Belo Horizonte, Brazil 3 GE21Geotecnologias, Horizonte, Brazil 4 Institut für Kontinuumsmechanik, Leibniz Universität Hannover, Hanover, Germany

Abstract. Mining-dependent urban settlements include villages, cities, and regions that are economically dependent on mining activities. In these areas, mineral extraction is the main source of income, employment, and municipal revenues. In the Iron Quadrangle a territory in the state of Minas Gerais in Brazil, considered in this study, 19 out of 34 municipalities are mining-dependent urban settlements. Although mining activity is an important source of revenue for these municipalities, the collected funds often do not translate into social and environmental improvements for their population. As a result, these settlements face territorial conflicts generated by the need to reconcile environmental quality preservation with the economic activities of mining carried out by large enterprises. In this study, the potential application of geodesign as a methodological, advisory, and decision-making process is empirically addressed. The objective of applying geodesign is to encourage the effective appropriation of open spaces by communities in mining-dependent urban settlements, considering the environmental control of these spaces for sediment retention and aquifer recharge. The study presented here is composed of two fronts of development. The first is the development of a WebGIS (Web Geographical Information System) for recording and presenting data on environmental control performance indicators of open spaces for the community. The second is the adaptation of the GISColab platform, a tool built for the application of the geodesign method, allowing different users to access a set of territorial data and information, enabling the collective and consensual construction of proposals for the use and function of urban spaces. Keywords: Geodesign · Mining-dependent urban settlements · Open space management · Environmental control

1 Introduction The mineral-dependent urban settlements comprise villages, cities, and regions that economically rely on mining activities. In other words, in these settlements, mineral extraction is the main source of income, employment for the local population, municipal © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 134–143, 2024. https://doi.org/10.1007/978-3-031-54118-6_13

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revenues from the Financial Compensation for Mineral Resources Exploration (FCMR), and taxes. The Iron Quadrangle (IQ), a region in the state of Minas Gerais located in southeastern Brazil, is considered one of the world’s largest mineral provinces, covering 12,785 km2 and encompassing 34 municipalities (Fig. 1), of which 19 are specialized in the mineral extraction sector [1]. According to IBRAM [2], 10 out of the 15 Brazilian municipalities that collected the most FCMR were in the IQ, totaling R$ 2.08 trillion in revenue in 2022. Despite mining activities being an important source of revenue for municipalities in the IQ, often the collected funds are not translated into social and environmental improvements for the population. Mineral-dependent urban settlements are characterized by territorial conflicts generated by the need to reconcile environmental preservation with mining activities conducted by large enterprises. The operations and facilities of these enterprises, such as open-pit mines, beneficiation plants, and tailings dams, are associated with significant negative environmental impacts, such as air and water pollution, noise and vibration emissions, soil erosion, and the destruction of wildlife habitats and landscapes.

Fig. 1. Location map of the Iron Quadrangle region. Fonts: Map created by author using the map from IBGE (Brazilian Institute of Geography and Statistics).

The influence of mining activities on the quality of water resources in the IQ is significant. Gomes [3] found high concentrations of heavy metals in both abiotic and biotic compartments up to 20 km from the nearest mining site. The study indicates that the highest retention of pollutants occurs in the biotic compartment (seston and zooplankton), which is considered a primary food source in the trophic chain of aquatic ecosystems, contributing to the transfer of metals and semimetals to higher trophic levels. Landscape improvement programs for mineral-dependent urban settlements are urgent and should be oriented towards the establishment of a system of open spaces. This system should be capable of minimizing pollution, protecting natural resources, and enhancing community engagement to expand understanding of the functions of open spaces as public facilities that provide ecosystem services.

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Studies carried out in the IQ indicate a rich hydrography in this territory (specific to its geophysical characteristics), with many springs and watercourses, some even without a nominal reference. This fact strengthened the idea of working with water as an aggregating element to increase perception and, consequently, awareness. Based on this context, the evaluation of the performance of the interventions proposed to contain the peak flow of surface runoff and associated sediments is centered on the geodesign as a pedagogical communication strategy. Through geodesign, communities in mining-dependent centers will be skilled to act as monitoring agents for environmental quality indicators. Thus, this study addresses the potential of geodesign as a consultative and decisionmaking methodology to encourage effective community engagement in open spaces within mining-dependent urban settlements. This application considers the environmental control function of open spaces for sediment retention and aquifer recharge.

2 Sustainability is Perceived in Open Spaces Open spaces are areas not occupied by built structures [4], inherent to urban form [5], as they shape the characteristics of the built environment [6]. Streets, sidewalks, squares, uncovered parking lots, vacant lots, beaches, and forests are examples of open spaces. We can also cite other examples such as: neighborhood/community gardens, playgrounds, parks, pocket parks, etc. They encompass environments that allow for the movement of people, the flow of fauna and flora, water, wind, and light. In other words, open spaces are a fundamental infrastructure for the permeability of the urban fabric. They are means through which basic city services are established, such as solid waste collection, transportation of people and goods, stormwater drainage systems, and community events. Open spaces are considered one of the key urban infrastructures, where a significant part of daily life takes place [5], and where the community can experience and truly perceive sustainable development. The maintenance of public open spaces contributes to the conservation of environmental, historical, and scenic resources, as well as the restoration of hydrological balance and improvement of air quality [6]. Therefore, the quality of mineral-dependent urban settlements and, on a larger scale, the integrity of ecosystems, are directly affected by the absence or the inadequacy of open spaces, which can provide effective environmental services to protect and enhance ecological functions and processes, such as the filtration and infiltration of surface runoff, as well as carbon and nitrogen sequestration and cycling. When open spaces are designed as green infrastructure complementary to gray infrastructure, the environmental function can be preserved or optimized in areas that are not yet urbanized or in the process of urbanization [7].

3 Nature-Based Solutions for Mineral-Dependent Urban Settlements Natural wetlands (e.g., swamps, marshes, mangroves, fens, and bogs) are ecosystems that play a crucial role in protecting adjacent ecosystems. Among their functions, the following stand out: (i) protecting terrestrial and aquatic ecosystems against floods;

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(ii) removing nitrogen from the ecosystem through denitrification; and (iii) retaining nutrients in sediments through the processing of organic matter. In this case, particular emphasis is placed on aquatic macrophytes and, especially, their associated microbial communities, which play a significant role in organic matter decomposition and nutrient cycling [8–10]. Vegetated detention basins and bioswales are compensatory devices inspired by or mimicking natural wetlands. Vegetated detention basins are shallow depressions that temporarily store the volume of intense rainfall and release it slowly, reducing downstream peak discharge and, consequently, the risk of flooding. In the root zone of their vegetation cover, physical and biological treatment of water contaminated by diffuse pollution occurs, favoring aquifer recharge with clean water. On the other hand, bioswales consist of open, shallow channels with a cover of herbaceous species designed to intercept, convey, treat, infiltrate, and attenuate the surface runoff from impermeable areas such as roads, small accesses, sidewalks, yards, and parking lots. The combination of these two compensatory techniques, detention basins and bioswales (Fig. 2), becomes a suitable strategy for areas with high sedimentation rates in surface runoff contributing areas. This is the specific case for urban settlements located in areas influenced by iron ore mines in the IQ region.

Fig. 2. Surface runoff treatment system in mining-dependent urban areas. Font: Developed by the author.

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When positioned along the streets and upstream of the detention basins, bioswales function as sediment forebays. This complementary device provides essential pretreatment by slowing down the flow velocity of stormwater and facilitating the sedimentation of suspended solids before entering the detention basin. This configuration helps minimize sediment loads and, consequently, improves the overall effectiveness of the system. In narrow streets, a common situation observed in unplanned settlements associated with mining operations, the bioswale can be covered with a grate to enhance pedestrian mobility and facilitate regular maintenance of the device, including sediment removal and replanting. Therefore, bioswales and detention basins are compensatory techniques aimed at reducing surface runoff on access roads and minimizing the significant amount of sediment that is transported daily by surface runoff to adjacent water bodies. It is important to note that, in addition to rainfall, contributions to surface runoff in urban areas near iron ore mines are caused by the ineffective practice of moistening the roads to control the resuspension of particulate matter. Such aspect intensifies the damage caused to water bodies. Public open spaces in mining-dependent settlements play a crucial role in enhancing environmental quality. However, according to Macedo [11], the longevity of an open space is directly related to the preservation of its morphological identity, which is achieved through the appropriation capacity offered to users. The author also emphasizes that proper maintenance facilitates acceptance and, consequently, the appropriation of these open spaces. Therefore, it is crucial for public management and the population to monitor quality indicators of open spaces in order to promote participatory management and useroriented appropriation of these spaces. This will ensure that the benefits of applied environmental services are truly perceived by the users.

4 Geodesign for Monitoring and Communicating the Quality of Open Spaces in Mining-Dependent Urban Areas Environmental quality indicators in urban environments have the main objectives of grouping and measuring information in a way that relevant characteristics become visible, understandable, and accessible to improve the communication process of data for a specific location and period for the public and public officials [12]. Therefore, performance indicators for actions promoting environmental quality in mining-dependent urban areas can be established and monitored in open spaces, as these spaces encompass a system where environmental services (sediment retention, aquifer recharge, wildlife habitats, etc.) and social activities are developed. In this scenario, geodesign emerges as a relevant methodology for participatory management of public open spaces, enabling typological evaluation (analysis of functional and morphological categories and criteria of spaces) and communication of this data and information on the qualification of open spaces with and for the population. The methodological proposal comprises four steps that will be incorporated into an online management platform (Fig. 3).

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Fig. 3. Model of Open Space Management System.

The first step involves obtaining information about the typological characteristics of the available public open spaces, using functional and morphological categories and criteria. Then, the open spaces will be evaluated based on fundamental criteria to establish environmental control functions, such as: • • • • •

Permeability rate of the contributing basin of the open space; Susceptibility to erosion; Susceptibility to flooding; Percentage of native vegetation cover; and Potential for connectivity with legally protected green areas.

The definition of priority open spaces and the recognition of existing or potential ecological functions are expected outcomes of the qualification stage. These results will be used to expand or define and implement suitable environmental services for each ecological function. In step 4 of the open space management process, the definition of indicators to assess the performance of environmental services will be carried out, as well as the establishment of maintenance and monitoring procedures. These measures will allow for tracking and improving the performance of these spaces, transforming them into a green infrastructure system that produces ecosystem services. The legitimate contribution of green infrastructure to urban sustainability essentially depends on multidisciplinary planning, addressing the needs of stakeholders, with the support of decision-makers, and furthermore, undergoing systematic short and long-term monitoring and evaluations [13]. Monitoring and management methodologies based on environmental quality indicators are more effective when they involve the participation of the local community, as they expedite decision-making processes to address current negative environmental trends at operational management levels and generate changes in attitude towards sustainable natural resource management [14]. In this scenario, the use of geodesign to monitor environmental quality indicators of open public spaces in mining-dependent urban centers becomes a strategy of great importance. In this strategic context, geodesign can promote access to the local community’s knowledge about the environmental control functions assigned to open spaces and

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allow the interaction of multiple local actors and other stakeholders in the construction of a systemic landscape planning. 4.1 Quality Indicators The environmental quality indicators of open spaces were established considering basic parameters that influence the environmental quality of services proposed to contain high sediment loads and facilitate aquifer recharge. Therefore, they will serve to monitor the performance of compensatory devices of Sustainable drainage systems - vegetated detention basins and bio-swales, as follows (Fig. 4):

Fig. 4. Indicators of quality of open spaces.

The monitoring plan for these indicators should be carried out with the participation of a field team made up of residents (users of open spaces) and a technician in charge. This technician must be qualified to guide the activities and fill out the data collection forms for each open space that includes compensatory devices. 4.2 Geodesign Platform for Co-Creation Geodesign combines proposal creation with impact simulation in a geographical context [15]. Eventually, it involves planning with and for geography to achieve consensus in a diverse environment with multiple stakeholders interested in the final outcomes [16]. Geodesign tools are applications that allow manipulation and processing of spatial information providing access to a variety of real-time geographic information, that can be used in various methods of territorial planning. The geodesign framework deals with “the potential of geoinformation technologies on shared platforms to create collective agreements”. These agreements are based on processes of co-creation of ideas for the territory. In the context presented in this paper, GISColab is suggested as a reference platform, that favors the understanding of “citizens’ ability to read about their reality, reducing external interference in the process” [20]. In Brazil, a methodology for geodesign application has been proposed, aiming not only to obtain results but also to raise awareness and identify the spatial interpretations made by stakeholders in the geographic territory. This aspect contributes to community inclusion and expands the discussions for the participatory construction of a management plan for public open spaces. This methodology consists of well-defined stages

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Fig. 5. Working framework in geodesign through Co-Creation.

that facilitate the identification of potential conflicts and agreements among participants (Fig. 5). The methodological process is highly optimized when using a web-based platform, such as GISColab, which was initially developed by the GE21 Geotechnologies group [20] and adapted for geodesign by Moura [20] and Freitas [19]. GISColab facilitates the application of a framework for shared co-creation planning. It has broad adaptability potential based on the Open Geospatial Consortium standards and can accommodate scripts to support the work stages. Different users can access the same set of data and information, and the collective construction of proposals is shared. The methodology allows for the rapid spatialization of proposals through integration and dialogue among participants and their proposals [20].

5 Final Considerations Given the economic dependency on mining activities in dozens of urban centers in the Iron Quadrangle the requalification of the drastically transformed landscapes becomes an urgent and compensatory program to achieve minimum environmental control conditions in these localities. The open spaces in these settlements constitute important public amenities and a starting point for implementing nature-based solutions aimed at minimizing impacts on water resources and enhancing the environmental comfort of the community. The proposed model represents a methodological approach designed based on the morphological and functional characterization of public open spaces, enabling their qualification, and gathering a set of data to support the definition of specific treatment

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requirements. These actions are focused on the implementation, monitoring, and protection of environmental control functions, with an emphasis on sediment retention and aquifer recharge. However, it is crucial that this planning process is outlined and executed using participatory methodologies involving the local community. It requires the development of capacities for reflection, discussion, and determination of their own priorities for sustainable development. In this regard, geodesign applied through the GISColab platform emerges as a powerful methodology capable of processing, spatially organizing information, and facilitating the construction of participatory management plans. The community can monitor environmental quality indicators to track performance, protect the functionalities of public open spaces, and consequently ensure the provision of associated ecosystem services.

References 1. Correa, B.C.F.: Análise da governança na resiliência regional para os municípios do Iron Quadrangle em Minas Gerais (2004–2019). Dissertação de mestrado, Universidade Federal de Ouro Preto, Instituto de Ciências Sociais Aplicadas, Programa de Pós-Graduação em Economia Aplicada, Mariana, MG, p. 79 (2022) 2. IBRAM. Setor Mineral – 2022. https://ibram.org.br/publicacoes. Accessed 14 Jun 2023 3. Gomes, P.C.S.: Incorporação de poluentes em compartimentos bióticos e abióticos de ecossistemas aquáticos do Quadrilátero Ferrífero. Universidade Federal de Ouro Preto, pp. 19–32, Ouro Preto, MG (2019) 4. Magnoli, M.M.L: Ambiente, Espaço e Paisagem. Paisagem ambiente: ensaios 21, 179–204 (2006) 5. Macedo, S.S., et al.: Os sistemas de espaços livres na constituição da forma urbana contemporânea no brasil: produção e apropriação. In: Macedo, S.S., Custódio, V., Donoso V.G. (eds.) Reflexões sobre espaços livres na forma urbana. FAUUSP, pp. 12–14, São Paulo, SP (2018) 6. Meneguetti, K.S.: Cidade Jardim, cidade sustentável: a estrutura ecológica urbana de Maringá. Editora da Universidade Estadual de Maringá, pp.43–154, Maringá, PR (2007) 7. Pellegrino, P.R.M.: Conclusão. In: Pellegrino, P., Moura, N.B. (eds.) Estratégias para uma infraestrutura verde, pp. 300–316, 2017, Manole, Barueri, SP (2017) 8. U.S. EPA. Methods for Evaluating Wetland Condition: Introduction to Wetland Biological Assessment. Office of Water, U.S. Environmental Protection Agency, Washington, DC. EPA822-R-02-014 (2002) 9. Boavida, M.J.: Wetlands: most relevant structural and functional aspects. Limnetica 17, 60–61 (1999) 10. Odum, E.P.: Ecologia. Editora Guanabara, pp. 169, Rio de Janeiro (1988) 11. Macedo, S.S.: Espaços livres. Paisagem e ambiente: ensaios. FAUUSP 7, 15-56 (1995) 12. Nunes, M.F.O., Mayorga, C.T., Gullo, M.C.R., Pedone, C.E.M.: Indicadores de sustentabilidade urbana: aplicação em bairros de Caxias do Sul. Arquitetura Revista 12, 89 (2016) 13. Ahern, J.: Green infrastructure for cities: the spatial dimension. In: Novotny, V., Brown, P. (eds.) Cities of the Future Towards Integrated Sustainable, Water and Landscape Management, pp. 276–282. Published by IWA Publishing, London (2007) 14. Danielsen, F., Burgess, N.D., Jensen, P.M., Pirhofer-Walzl, K.: Environmental monitoring: the scale and speed of implementation varies according to the degree of people’s involvement. J. Appl. Ecol. 47, 1167–1168 (2010)

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15. Flaxman, M.: Geodesign: fundamental principles and routes forward. Talk at Geodesign Summit, Redlands – California (2010). http://www.geodesignsummit.com/videos/day-one. html. Accessed 27 Jan 2019 16. Steinitz, C.: A Framework for Geodesign: Changing Geography by Design. ESRI Press, Redlands (2012) 17. Moura, A.C.M., Freitas, C.R. (2021). Co-creation of Ideas in Geodesign Process to Support Opinion and Decision Making: Case Study of a Slum in Minas Gerais, Brazil. In: La Rosa, D., Privitera, R. (eds) Innovation in Urban and Regional Planning. INPUT 2021. Lecture Notes in Civil Engineering, vol 146. Springer, Cham. https://doi.org/10.1007/978-3-030-68824-0_28 18. Grupo GE21 Geotecnologias. https://ge21gt.com.br/. Accessed 14 Jun 2023 19. Freitas, C.: Tecnologias de Geoinformação no Planejamento Territorial, Novas Formas de Produção, Compartilhamento e Uso de Dados Espaciais, Tese de Doutorado – Universidade Federal de Minas Gerais, Escola de Arquitetura. 262f.:il (2020) 20. Zyngier, C.M., Casagrande, P.B., Moura, A.C.M., Ribeiro, S.R.O.: Geodesign como plataforma para co-design: Estudo de Caso Maria Tereza. In: XXI Congreso Internacional de la Sociedad Iberoamericana de Gráfica Digital, Concepción; Blucher Design Proceedings; Editora Blucher: São Paulo, Brazil, pp. 403–409 (2017)

Strategies for Democratizing Development. Application of Geodesign in a Low-Context Culture Simone Corrado(B) , Luigi Santopietro , Alfonso Annunziata , Rosanna Piro, Rachele Vanessa Gatto , Rossella Scorzelli , Shiva Rahmani , Francesco Scorza , and Beniamino Murgante Laboratory of Urban and Regional System Engineering (LISUT), School of Engineering, University of Basilicata, Potenza, Italy [email protected]

Abstract. Geodesign involves multiple stakeholders, including community members, planners, designers, and policy-makers, to collaborating in designing solutions to local development. Public involvement in the co-design process is a worthwhile means of generating consensus on choices and of raising awareness of the territorial structural issues and associated risks. In fact, during the knowledge building phase, spatial critical points can be highlighted in a readily communicative form that can be interpreted even in a low-context culture. Hence, this resilience-oriented co-design approach is part of the MITIGO project, which aims to deploy a framework for innovative and sustainable hydrogeological and seismic risk mitigation solutions targeting road connections and strategic structures in mountain areas typically located in the Basilicata region. In these areas a survey showed the demand for more constancy in the co-participation of the population in decision-making processes by fostering a democratic approach to local development and ensuring iterative planning. The learning process analyzed the territory to train and inform participants, raising awareness of territorial governance and urban transformation issues. The methodology applied in this experience shows alternative participatory approaches to sustainable, inclusive, and innovative future planning in risk scenarios. Keywords: Geodesign · PPGIS · Resilience-oriented planning · Spatial planning · Co-design

1 Introduction The field of Geodesign encompasses a collaborative and inclusive approach to urban and regional planning, involving various stakeholders such as community members, planners, designers, and policy-makers [1]. This cooperative effort aims to design solutions for local development while considering territorial structural issues and associated risks [2]. Public involvement in the co-design process holds useful value as it fosters consensus-building and enhances awareness of critical spatial concerns, even within low-context cultures [3]. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 144–154, 2024. https://doi.org/10.1007/978-3-031-54118-6_14

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Within this context, the MITIGO project emerges as a resilient-oriented co-design project that seeks to deploy innovative and sustainable solutions for hydrogeological and seismic risk mitigation. Specifically, the project focuses on road connections and strategic structures in mountainous areas situated in the Basilicata region. Through surveys conducted in these regions, it has become evident that there is a strong demand for increased public participation in decision-making processes, emphasizing the need for democratic approaches to local development and iterative planning. This research endeavors to explore alternative participatory methodologies that foster sustainable, inclusive, and innovative future planning in risk-prone scenarios. By examining the territory, training and informing participants, and raising awareness of territorial governance and urban transformation issues, this study contributes to the development of effective and responsive planning strategies. The findings of this research can inform planning practices and policy-making in order to address hydrogeological and seismic risks and promote resilient and sustainable development [4].

2 Geodesign – Designing in a Participatory System Thinking Approach Recent developments in the disciplinary debate propose Geodesign as an innovative methodological framework to support urban and regional planning in the regenerative design of public spaces. For this purpose, looking at the future challenges for spatial information technology proposed by Wolf in his article: Reproducibility, Inclusion and Common task Geodesign seems to be a fitting methodology [5]. Moreover, Jack Dangermond claims that [6]: “Geodesign enables scientist, design professionals, government and stakeholders to work together using a common visual language of maps and spatial analysis method to address global challenges at many scales”. Indeed, Geodesign proposes an integrated, collaborative, and participatory system thinking approach that initiates with project conceptualization, where stakeholders from various domains and cultural sphere actively engage to establish a shared vision for the development. Then, the shared vision is translated into a series of analytical and simulation-based processes, leveraging the advancements in spatial information systems, which enable the exploration of multiple alternatives and their potential impacts on the analyzed context. The implementation of Geodesign in spatial planning has already been tested with successful results in many case studies at different scales and worldwide [7, 8]. As pointed out earlier, in Geodesign the role of the methods and tools of geographic information systems is crucial [9]. Especially in today’s context, with the vast availability of data sharing and geo-processing services, these tools empower planners to perform dynamic cognitive frameworks that can be continuously update and adapt based even on real-time data or specific-context state of art [10, 11]. This dynamic nature ensures that decision-making is based on the most current and accurate data, enhancing the effectiveness and efficiency of the entire Geodesign process.

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On this premise, the primary objective of Geodesign is to make explicit and strengthen the intricate relationships between data, information, knowledge, and subsequent decision-making within the project context. By explicitly connecting these elements, Geodesign aims to bridge the gap between theoretical understanding and practical implementation, ensuring that planning and design choices are grounded in evidencebased knowledge and lead to tangible and sustainable outcomes [12]. This ambitious goal is achieved by comprehensively understanding the existing conditions and exploring alternative future scenarios, Geodesign facilitates informed decision-making and stakeholder collaboration, leading to sustainable and inclusive planning scenario. Thus, Geodesign is a structured approach consisting of six models that guide the assessment and intervention phases of the planning process [1]. The initial three models form the assessment phase, or knowledge building phase, and focus on understanding the current conditions of the study area and its potential natural future development. These models are the Representation Model (Inventory - data), which depicts the current state of the study area, the Process Model (Analysis - information), which analyzes the possible evolution of the territory with no interventions, and the Evaluation Model (Suitability map - knowledge), which identify areas that are more/less suitable or change-prone. While, the intervention phase covers the remaining three models, aimed at determining how the study area should be modified to enhance its current conditions. The Change Model (Scenario alternatives - data) is developed to propose alternative future states for the study area, which are then evaluated for potential environmental, economic, or social impacts through the Impact Model (Changes cause - information). Last but foremost, the Decision Model (Preferred solution - knowledge) supports a negotiation process among decision-makers and stakeholders to reach a consensus on the final development choice. Throughout the Geodesignhub platform, the results of each phase are shared with stakeholders and visualized through maps, charts, and graphs to facilitate participation [13]. Feedback received during this process allows stakeholders to refine their designs and collaborate towards finding a mutually acceptable solution. While the Geodesign process is not strictly linear, three iterations are typically undertaken to perform a comprehensive study. The first iteration involves identifying the purpose of the case study, serving as a scoping phase. The second iteration proceeds in reverse order through the six models, clearly defining the methods and tools required based on the specific planning study’s needs, acting as a meta-planning phase. Finally, the third iteration entails the full execution of the study. According to Steiniz, the third iteration of Geodesign delivers optimal outcomes. Due to its non-linear nature, the process ensures a comprehensive exploration of the study area, promotes continuous learning, and facilitates the synthesis of knowledge and collaborative decision-making [14]. In practice, by reevaluating and reiterating the models, Geodesign accommodates the evolving context, new data, and changing stakeholder needs. In this way, it promotes adaptability and flexibility, ensuring that the final design solution is robust, responsive, and aligned with the goals of sustainability, livability, and environmental compatibility. In conclusion, within the spatial planning discipline, Geodesign signifying a paradigm shift towards a holistic approach to the design and development of natural and man-made environments [15]. This approach is underpinned by a commitment to environmental compatibility and sustainable development goals SDGs.

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3 The MITIGO Project and Study Area The MITIGO project aims to explore innovative and sustainable hydrogeological and seismic risk mitigation solutions mainly for road links and strategic structures in mountainous areas typical of the inner areas of Basilicata region. For this purpose, traditional on-site measurements and laboratory tests, surveys and monitoring with terrestrial and satellite systems are carried out [16]. Moreover, innovative and sustainable mitigation strategies or safety interventions are test and alternative minimum-risk connection systems for reduction in travel time are analyzed [17]. All this data and models flow into IT platforms and expert-domain systems to support public administrations, engineers and businesses in managing, planning and designing mitigation initiatives [18]. The municipalities of Pietrapertosa, Castelmezzano, Campomaggiore, and Albano di Lucania were chosen as a suitable study area due to characteristics common to large portions of the Basilicata region territory: morphological features, presence of natural and cultural heritage, conditions of territorial marginality with respect to the main regional service poles, fragility of the infrastructure system, depopulation and weakness of production systems [19]. Similar to the other inner areas of Basilicata and also nationwide, the four municipalities face a significant challenge in the form of hydrogeological instability, which is widespread and poses a notable problem. The susceptibility to such instability can be attributed to natural factors, particularly the geological and geomorphological layout characterized by a young orography and rising relief. However, human actions play a substantial role in exacerbating the hydrogeological vulnerability of the context. Factors such as mountainous land abandonment, ongoing deforestation, environmentally unfriendly farming practices, and neglect of slope and watercourse maintenance have further deteriorated the state of affairs and highlighting the territorial fragility. In the MITIGO area this is particularly concerning as 18% of the roads are classified as landslide-prone, posing a significant challenge not only to transportation infrastructure but also to the safety of buildings, with approximately 670 inhabitants residing in areas of high hydrogeological risk [20]. Another worrisome aspect is the high percentage of residential buildings constructed before 1980, exceeding 80% in all municipalities, while the provincial and regional average remains below 70% [20]. This prevalence of older and very poorly maintained buildings represents a weakness in terms of safety. Moreover, the study area alone accounts for over 400 decaying, ruined, and dilapidated buildings, further adding to the concerns. Other recent studies carried out on the same area reveals that 59% of the total area falls into land features with severe limitations that render them unsuitable for profitable conventional agricultural activities [21]. Consequently, there is a lack of agricultural specialization in high-value production, and the municipalities do not hold recognized quality and valorization marks for any agricultural products. This represents a significant weakness in terms of agricultural potential and possibility of economic development [22]. Additionally, the increasing trend of depopulation poses another relevant issue since primary and secondary health and institutional services offered to the residents are inadequate and inefficient [23]. Additionally, the organization of the tourist offer in the region is inadequate considering the local natural and cultural heritage potential

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[24]. This poses yet another relevant weakness, as the tourism sector fails to effectively capitalize on the region’s resources and attract visitors [25]. In summary, the challenges facing the MITIGO area encompass hydrogeological instability due to both natural and human factors, the prevalence of older and deteriorating buildings, limited agricultural specialization, and an inadequate organization of the supply of institutional services. Addressing these weaknesses will require comprehensive planning and strategic interventions to ensure the safety, sustainability, and economic development of the context [26]. Furthermore, the spatial distance from economic and political centers of power can also shape cultural perceptions and accentuate the discomfort experienced by residents [27]. Thus, territory that are geographically distant from these centers and have a relevant weakness on many sectors may be deemed "culturally disadvantaged" or "peripheral" in relation to areas with greater financial resources, established cultural institutions, and intellectual elites. Consequently, such regions may have limited access to the resources necessary to promote and sustain education and cultural expressions considered “high” or “sophisticated” [28]. This spatial distance can potentially result in a higher prevalence of local cultural expressions, popular traditions, and less complex or less refined forms of social and political active participation [29]. Thus, the MITIGO project’s area might be categorized as “low-context” if the specific cultural parameters mentioned above are taken into account.

4 Evaluation Maps for MITIGO Public involvement in the co-design process become also a worthwhile means of generating consensus on choices and of raising awareness of the territorial structural issues and associated risks. In fact, during the knowledge building phase, spatial critical areas can be highlighted in a readily communicative form that can be interpreted even in a “low-context” culture [30]. Hence, this resilience-oriented co-design approach is part of the MITIGO project, which aims to deploy a framework for innovative and sustainable hydrogeological and seismic risk mitigation solutions and enhancing citizen’s awareness [31]. Since Geodesign is a complex participatory framework and each policy or project has multiple consequences on different domains, 10 systems are set in the framework as the basis for the comparison of design impacts. To make the methodology comparable with other projects worldwide, nine systems are common to all project and the last one is more flexible for highlight a local priority. In this exercise, the flexible system is set up as the tourism one. In such manner, the systems are summarized as follow: • • • • • • • •

tourism (TOUR); green infrastructure (GI); water infrastructure (WI); energy infrastructure (EI); grey infrastructure (TRAN); agriculture (AG); industry (IND); housing lower density (LDH);

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• institutional (INST). Therefore, the preliminary analysis was to disaggregate the territory into these ten systems and conduct an on-desk study through an overlay analysis and then revise the outcomes taking into account the "place-people factor." The figure below, see Fig. 1, shows the suitability maps designed for the Geodesign workshop of MITIGO project.

Fig. 1. Site evaluation for the ten systems designed for the Geodesign workshop of MITIGO project.

In particular, the tourism system and the grey infrastructure system are detailed here, and the components of each system and the functions performed are briefly described. The discussion is limited to these two because in our view the grey infrastructure is representative of the current main weakness in the area, but otherwise the tourism system gives the opportunity for local economic development. The tourism system, see Fig. 2, through the care and promotion of territory, enables the enhancement of local heritage and its ascription in a broader process oriented to the tourist enhancement of places and to create networks of relationships with high economic, social and cultural value [32]. The hospitality sector, consisting of activities and services with a multi-purpose character, is capable of encompassing in a systemic form the territorial entities, the organizations and businesses that provide tourists with assistance, directions and information useful for the enjoyment and discovery of the territory and cultural attractors [33]. The tourism vocation of the area is mainly linked to the geomorphological singularities, typical of the Lucanian Dolomite complex, and to the macro-attraction “volo dell’angelo” between the settlements of Castelmezzano and Pietrapertosa. In these municipalities, already included in the network of the Most Beautiful Villages of Italy, the main tourist flows are directed. Notwithstanding, the centers of Albano and Campomaggiore present natural landscape and cultural peculiarities scattered over the territories but not supported by a structured hospitality system. Throughout the area, the tourism supply shows a strong seasonality. Hence, the long-term impacts of the tourism ecosystem, in terms of territorial development opportunities, are currently low [25]. Additionally, the organization of the tourist offer in the region is inadequate considering the area’s potential. This issue offers an opportunity local economic development. If the tourism system represents an element of attractiveness and potential economic development, on the contrary, the transport system identifies elements of territorial vulnerability since it presents multiple issues especially within the road connections to the main arteries located in the valley that leading into regional poles, Potenza and Matera. The map, see Fig. 3, also highlights the paucity of road graph links with the primary road

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Fig. 2. The suitability map of tourism system and the macro-attraction “volo dell’angelo” between the settlements of Castelmezzano and Pietrapertosa.

system and the distance of the settlement between intermodal hubs. The twisted shape of the roads also highlights the nonlinearity of these links that are mainly caused by the Dolomite complex and slope instability. Indeed, the landslide risk is high along these routes and very often the only way to the municipality of Pietrapertosa is interrupted. This critical situation in terms of dealing with co-occurring emergencies should also make us to think about the possibility of multi-hazard civil protection plan to increase the resilience [34].

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Fig. 3. The suitability map of grey infrastructure system and the road connection between the settlements of Castelmezzano and Pietrapertosa interrupted by a landslide.

5 Conclusion In conclusion, by embracing Geodesign principles and integrating the outcomes of the evaluation maps, the MITIGO project and similar initiatives can contribute to the safety, sustainability, and economic development of the context. The participatory and system thinking approach of Geodesign allows for adaptive and flexible planning, incorporating evolving contexts, new data, and changing stakeholder needs [21]. Through continuous learning, collaboration, and evidence-based decision-making, Geodesign promotes resilient and inclusive spatial planning, aligning with the goals of environmental compatibility and sustainable development [35]. This cooperative effort aims to design solutions for local development while considering territorial infrastructural issues and associated risks. Public involvement in the co-design process holds useful value as it fosters consensus-building and enhances awareness of critical spatial concerns, even within “low-context” cultures.

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Moreover, a survey conducted in these areas showed the demand for more consistent co-participation of the population in decision-making processes and increased awareness of the risks associated with the area in which they live [36]. Although limited to the knowledge building phase, interaction with communities is being pursued to conclude the Geodesign workshop and promote a democratic and participatory approach to future local development. However, one of the major limitations in the advancement of the participatory process is the willingness of the public administration to actively interact in the workshop. As pointed out earlier, the community has understood the potential of the participatory planning tool to bring forward its instances and contribute to the local development vision. While this has been exposed in a positive sense, institutions are still not ready to expose themselves to actively discuss proposals that come from a bottom-up approach. For these reasons, efforts are being made to raise awareness and prepare institutions for the future workshop’s activity. In this way, the shared planning process (communityinstitutions) can help to perform the quality and the evolution of the planning process.

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The Urban Digital Twin: A New Dimension for the Land Planning

Applying 4.0 Technologies to Public Spaces. Exploring New Functions and Interactions in Savona University Campus Daniele Soraggi(B)

and Federico Campanini

Italian Excellence Centre for Logistics, Infrastructures and Transport, University of Genoa, 16126 Genoa, Italy [email protected]

Abstract. Cities are complex systems linked to economic, ecological and demographic conditions and changes. The industrial revolutions, each with their own innovations, have clearly modified the city and its spaces. The aim of this paper is to understand how the ongoing digital and robotic revolution is capable of changing the smart city of today and tomorrow. The introduction of new technologies, from autonomous robots to IoT, required a transdisciplinary approach. This implies the need to adapt traditionally adopted planning tools. Through the analysis of five testbed districts and the experiences of Digital Twin (DT) applications in urban environments, new spatial relationships are identified. These experiences, upstream of a Urban Digital Twin (UDT) application, highlight the potential that shared human-robot environments have for defining a digital infrastructure capable of monitoring, assessing and updating its boundary conditions in real-time based on continuous data sharing. Furthermore, they address the complexity of future urban planning by addressing participatory and collaborative processes so that human-robot coexistence is accepted and measured to the needs of citizens. The case study of this paper is the university campus of Savona, which unites different realities within it: companies, research centres, sports facilities, residences and laboratories. In such a complicated urban ecosystem, the aim is to analyse how the introduction of a fleet of small robots for logistics modifies the internal zoning. The campus area is subdivided by means of a three-factor system (from-through-to) in order to identify critical points and opportunities that arise in the spatial sharing between men and robots. Keywords: Urban Digital Twin · Testbed · Robotics and Autonomous Systems · New technologies · Urban Space · Spatial sharing

1 Introduction As a result of evolutionary progress, mankind has systematically ‘updated’ and transformed the places where people live, in response of stimuli, needs and necessities [1]. In these changes, infrastructures play an important role. Waterways, roads and databases © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 157–168, 2024. https://doi.org/10.1007/978-3-031-54118-6_15

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are more than just technical exercises [2], they show for each epoch the priorities of societies and the importance of technological progress in satisfying them. The needs of recent years and the years to come revolve around contrasting climate change, pandemics, and energy crisis. Cities are undergoing significant transformations to address these challenges, focusing not only on their physical infrastructure but, more importantly, on their capacity to influence the behaviour of their residents towards adopting more sustainable habits [3]. This is exemplified by the concept of Proximity City models, where smart technologies play a key role in optimising city processes and empowering citizens to live more sustainably [4]. With the transition to the Fourth Industrial Revolution, a process of intense development of digitalization and automation has begun, both in work [5] and in everyday life. With the publication of the Green Deal, the European Union itself identifies the digital transition as one of the pillars around which to build its strength in drawing up new development strategies [6]. Cities play a dual role as both pioneers and evaluators of innovations [7] In incorporating new technologies into urban landscapes, it could be useful to revise and update urban planning tools. The quality of urban life requires thinking about both a hardware and a software aspect, related respectively to architectural and urban design and to the design of collaborative services [8]. This contribution comes from an attempt to ask how moving Industry 4.0 innovations to the complex urban system could change the way the city is planned and designed, also considering the necessary infrastructural system for the proper functioning of these new technologies. In particular, this work proposes the deployment of robotic technologies within an urban district to achieve a double purpose: as well as to provide services, autonomous systems could help the collection of data and information with the aim of implementing an Urban Digital Twin (UDT). This hypothesis implies the need to envision new urban scenarios. Starting from the entry of a new entity in public space, new interactions would be observed to comprehend how design practice and traditional planning tools could be updated. In the next part, two fundamental 4.0 technologies for urban planning are presented: the Digital Twin (DT) and Robotics and Autonomous Systems (RAS). Then, common guidelines are identified in ten best-cases through a learning-by-cases methodology. The fourth section introduces the case study of the University Campus of Savona, Italy, which is then proposed as an ideal place to plan a testbed for the deployment of robots and autonomous vehicles within its urban space. Finally, the paper analyses the changes that the introduction of these technologies within a delimited urban space produces in terms of uses and relational criteria.

2 Background In order to better understand how urban design and planning can evolve, two technologies are investigated in this section: UDT and RAS. Conceptually, the former potentially represents a software tool in support of space governance, the ‘mind’ capable of storing, analysing and elaborating data. The latter is the hardware element, the ‘body’ capable of colonising public space and acting alongside human in everyday tasks. From this perspective, both hardware and software can facilitate and help human activities in governance, urban planning and city processes.

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2.1 Urban Digital Twin Digital Twin origins are referred to the ‘Mirrored Spaces Model’ concept proposed by Professor Micheal Grieves in 2003 [9]. In brief, the idea was to define a high fidelity model able to virtually represent an object or a process, in order to carry out evaluations and previsions and to compare different scenarios under varying conditions. This concept became reality with technological development that enabled greater computing power and real-time data sharing. Paving the way for IoT and Big Data applications [10]. DTs emerged in industry as a mean to enhance design process, for example simulating object behaviour in its future operative environment (e.g. NASA for astronaut training and space missions monitoring) [11] However, they are utilized throughout every stage of a product’s life [12]. These aspects can prove valuable in the classification of DTs [9, 12], additionally, the level of model’s maturity and the interconnection between the two entities can also serve as criteria [10]. A DT consists of three essential elements: the physical component, the virtual replica, and the data exchange space that facilitates seamless communication between these two entities [13]. This bidirectional information flow fosters continuous and autonomous interaction between the physical and digital realms. This concept is the core of DT technology since it enables real-time interaction between the physical object and its virtual counterpart, allowing the system to modify the status of the physical object without direct human intervention. DT structure could be simplified into a hardware, software and infrastructure system, which can be easily traced back to the urban structure and its processes [8]. UDTs are the application of DTs to the urban context. They are often mistakenly referred to the virtual model alone, since many municipalities intend it as a way to better visualize assets and data. Given their ability to store large amounts of data, process them and make predictions, UDTs do not only aim to digitally represent the city, but also to support decision-making in urban planning, management and services supply, with an integrated and horizontal approach between stakeholders [14]. Urban planning activities are currently supported by digital tools such as Geographic Information Systems (GIS) and Building Information Modelling (BIM). Each is applicable in specific fields: in a nutshell, GIS helps in geospatial data analysing and visualisation generating thematical maps and databases at a territorial dimension [15]. BIM mainly works at building scale, providing virtual models and representation of the city’s assets and their performances along the entire life span of the object [16]. GIS and BIM can complement each other in terms of scale and accuracy, acting as a mutual source of information, and enabling the integration of data and applications throughout the urban design lifecycle. However, challenges have been identified regarding the integration of these two systems: literature highlights issues related to coordinate systems, informatic and semantic languages and standards [17]. Furthermore, currently planning and design processes follow a sectoral approach, rather than a synchronised development between stakeholders [18]. A more integrated approach is essential to optimize urban practices. Compared to GIS and BIM, DT assumes the interaction between physical reality and the virtual model, potentially in real-time, using a physical infrastructure made of sensors and Internet of Things technologies [19]. For this reason, the UDT could serve

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as a strategic tool to overcome the interoperability problems overmentioned and enhance urban planning activities. 2.2 Robotic Actuators To make this possible, not only constant monitoring is required, UDT also demands actuators capable of performing without human intervention. This ‘body’ of the city organism could be identified in RAS. Robots have evolved since they were first used in the industrial sector in the 1950s. Today, we see robots as colleagues, thanks to the development of collaborative robotics, that is one of the main prerequisites for the transition to Industry 4.0 [20]. This concept envisages cooperation between humans and machines according to an interactive approach that relies on cognitive and perceptual capabilities, rather than physical boundaries [21]; this is why the authors see it as a prerequisite for the introduction of robots in urban spaces, safely and in appropriate coexistence with other users. Through robotic systems applied in urban contexts, it is desirable to improve sectors such as transport, logistics, spatial planning, environmental monitoring, maintenance, welfare and construction [22]. RAS are capable of perceiving their surroundings, collecting data, making autonomous decisions, and performing real-time physical interventions. These functionalities are closely integrated with the digital infrastructure of the city, spanning from the wiring network to the sensors one. Therefore, understanding how robots can be seamlessly integrated and collaborate within diverse urban environments becomes imperative [23]. A place, as it can be understood by a robot, is characterised by material and immaterial parameters. The physical component provides information about the nature of the environment, the presence of constraints on movement and the level of possible interaction. The immaterial properties concern the difference between public and private, aesthetic and formal requirements and socio-cultural factors [22]. Urban robotics identifies the need for an appropriate infrastructure to manage interactions and promote their proper development [24]. Scientific literature focuses on the dynamics of human interaction with the environment and how they can be involved in the construction of a digital city model [25]. The possible interaction that would occur in shared urban spaces between humans and other types of users, also with their own levels of autonomy, is not covered by the latest researches.

3 Best Cases Analysis Testbeds (TB) are the most effective means of evaluating the integration of RAS in public spaces. These tools serve not only for experimentation and policy evaluation, but also play a significant role in urban regeneration. Through case study analysis we’ll try to understand how they work and how they can be applied to the case of Savona. Learning-by-case methodology is based on the analysis of case studies following a qualitative descriptive and comparative process [26, 27]. This

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methodology, based on the experience already gained from recognised best practices, enables a bottom-up process towards the integrated design of the shared human-robot spaces. Ten best cases were identified: five concerning the use of RAS within a TB and five experimenting the use of UDTs (Table 1). TB cases were selected by those proposed in report published by innovation agencies, such as Nesta, Vinnova, Innovate UK and Forum Virium, selecting those concerning themes similar to the ones of interest. The scope was also to observe different approaches in designing and management of the experimentation sites. DT cases have been selected from literature papers consulted for the background chapter in order to put in evidence how different urban subjects could be enhanced by applying digital twin technology. Table 1. Testbeds and Digital Twin experiences best cases Case

Location

Start

Type

Integration

Topic

Smart Santander

Spain

2011

TB

Diffused

IoT, environment

MK:5G

England

2021

TB

Limited

IoT, RAS, 5G

Self Repairing Cities

England

2015

TB

Diffused

RAS, infrastructure

Barkarby

Sweden

2018

TB

New District

RAS,

Smart Kalasatama

Finland

2013

TB

New District

New urban life

Cambridge

England

2019

DT

Limited

Participation, administration

Helsinki

Finland

2010

DT

Diffused

Visualization, modelling

Zurich

Switzerland

2011

DT

Diffused

Simulation

Rotterdam

Netherland

2018

DT

Diffused

IoT, real-time data

Herrenberg

Germany

2018

DT

Limited

Real-time data, participation

Testbeds setup is extremely free and variable, in dimensions, technologies to be tested and level of interaction between RAS and users. Considering users’ involvement, ‘Smart Santander’ refers to a wide range of people, including both citizens and visitors, in a project about the use of IoT infrastructures for environmental monitoring, mobility and green maintenance [28]. ‘Self Repairing Cities’ [29], as well, potentially involves all citizens of Leeds, UK, even if with a low level of interaction. The project, in fact, aims to use autonomous robots to fully automate infrastructure management and maintenance works. The goal is to minimize inconveniences caused by road works, such as traffic and noise issues. The testbed is widespread, with minimal human-robot interaction, and citizens benefit indirectly, even though they are directly involved in forums and participatory decision-making.

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On the other hand, the MK:5G project [30] refers to a specific target, since it is installed in a stadium district. This could be particularly useful for companies intending to promote a specific solution. In this case, the experimentation involved the use of IoT technologies and RAS to assist users of the sport facilities, providing hospitality services, car rentals, and transport services to and from the district. At the end of the test phase, the installed infrastructure remained available, providing an incentive for investors and companies to continue using the site for further experimentation [31]. Some experiences involve the realization of a brand-new district. The city of Barkarby recovered old industrial sites to host companies for testing their technological innovations. Urban planning tools have been updated and refined with the aim of opening up the city to experimentation, assigning specific functions and uses to each zone [32]. The construction of a new district is also common in the case of Smart Kalasatama [33] which involves co-designing neighbourhoods and homes to test new ways of living. Innovative transport, delivery and waste management systems are also being tested on the streets. Citizens and companies based in Kalasatama offer themselves as first evaluators of RAS technologies in a participatory experimentation process. In respect with UDTs, it is common to refer them to high fidelity models representing a city, but this is incorrect, since, as we said, UDT presents precise characteristics. The DT developed by the City of Cambridge [14], for example, consist in a decision-making tool for coordinating objectives and policies in different sectors. The proposed system was tested with the active participation of citizens on the issue of transport electrification and the evaluation of spillovers to other urban processes. The model allowed a crosssectoral and horizontal approach to the different processes involved, comparing public and private interests [18]. Frequent updating of the model, or part of it, is essential to ensure its accuracy and reliability. Helsinki [34] and Zurich [35] have been working for years on the realization of virtual representation of their assets that became the basis for the creation of DTs that today can be consulted and integrated into the different city services, through open data platforms. Both cities use information from sensors and data to plan interventions and compare scenarios related to climate change mitigation. The UDT developed in Rotterdam [36] aims to use sensors that can share real-time informations to facilitate waste management and public and private traffic management for both vehicles and boats. Also the port uses its own DT for real-time monitoring, using ‘digital dolphins’ and smart containers to control changes in weather and sea conditions. Data acquisition is a key factor in DTs management and should be more researched in applications to the urban context. The UDT for Herrenberg, Germany, evaluated data collection and processing platforms to assess the impact of new possible mobility habits in order to reduce air pollution. This has been done by directly involving people in the data collection process through citizen science experiences and public forums [37]. Most of the robotics applications in urban areas concern delivery services, waste collection, mobility, maintenance of transport infrastructure and management of customer and health services. Furthermore, the tendency has been to adopt discrete and punctual applications and not to equip the city with an autonomous and automated superstructure [38]. Also, due to the practical and economic challenges associated with developing a comprehensive model, UDTs applications are typically focused on critical

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issues for which administrations are willing to invest in technological upgrades. These issues often include climate change mitigation, mobility and pollution. Consequently, UDTs are highly context-dependent.

4 University Campus of Savona, Italy The case study is the Savona University Campus, one of the teaching and research centres of the University of Genoa, Italy. The area was originally used as military barracks and has been redeveloped and transformed into a campus since the 1990s. In an extension of more than 50,000 square metres, diverse groups of users are accommodated, including students – both residents and non-residents – university staff, employees from external companies, as well as personnel from various activities, such as catering and delivery services [39]. The campus district is made up of eight main buildings containing lecture halls, offices for professors, technicians and external staff, student residences, a canteen and a library. There are also areas for sports activities and laboratories. The Municipal Urban Plan acknowledges the district as an emerging hub and a catalyst for transforming the surrounding areas. This aligns with the role of TBs which aim to support the scalability of proven experiments and solutions [40]. The primary focus of the campus’ educational activities regard energy engineering and the development and evaluation of cutting-edge technologies. Ideally, the campus is already a product of the Fourth Industrial Revolution, since modern energy and technological infrastructures have already been installed for scientific research purposes [41]. As a result, it is considered an ideal case study for the implementation of RAS within an urban testbed. 4.1 New Scenario Testbeds are useful to gradually deploy RAS technologies and evaluate how people interact with them. They provide a valuable platform to assess the real-world impact of these new entities and gauge user experiences. This would be particularly noticeable in the case of the campus, where many potential users share the public space and social dynamics are one of the driving forces of the place. Traditionally, only pedestrians and eventually vehicles coexist in the public space. In comparison to a purely vehicle-pedestrian concept, the robot variable must be considered. The introduction of the new user on the campus modifies the current state and offers the potential for a transformed space, which may not be fully comprehended at first glance. This introduction leads to the assignment of new functions to different areas, alters the flow of movement, and fosters a multitude of new possible interactions. It is therefore important to focus on the management and zoning aspects of urban spaces, considering these new entities with different behavioural habits. The new scenario for the campus foresees the installation of two elements: an automated last-mile logistics hub and a testbed for evaluating robotic applications in the urban environment. This will be achieved through the adaptation and installation of warehouse robots in a dedicated room and the use of delivery robots across the district.

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Fig. 1. Comparison of user and flow maps. Left: the current state, right: the new scenario. Robot deployment modifies spaces function and interactions.

Robots are capable of navigating through the area and accessing buildings via specifically designated secondary entrances provided with automatic opening systems, so human intervention is not needed. These have been selected to minimize confusion, especially during crowded occasions. Each building accessible to robots is equipped with an atrium dedicated to handling delivery operations, while classrooms and auditoriums remain inaccessible to avoid any disruption to their respective activities. The TB also involves the construction of a new building that will house the spaces required for the construction of the machines, their maintenance and shelters. Additionally, the facility will provide areas for experimentation and for organizing events, presentations, and demonstrations. The new building will also house offices to oversee DT production and monitoring. Three Factor System. Deployment of robots on campus, along with the aforementioned interventions, will significantly alter the utilization of outdoor areas and the movement flows of various users. Apart from the existing activities on the campus, it is imperative to consider the events associated within the TB, which hold greater public significance. Four zones have been identified based on the level of human-machine interaction (Fig. 1). Zone A is designated for pedestrian use only, encompassing primarily green areas and sports facilities. The presence of robots in this zone is not allowed due to intended use and to ensure that the area remains machine-free for individuals who may not be comfortable interacting with them. Zone B designates areas that are shared by pedestrians and vehicles. Within this category, they can be further classified as B1 and B2, depending on whether the vehicle the user interacts with is a private vehicle or a service vehicle designated for the campus area. This distinction is necessary because it entails different navigation behaviours that need to be taken into account.

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Zone C comprises high-use areas – such as offices, classrooms, and the library. Here, promoting human-robot interaction is essential to optimize research outcomes. These areas remain pedestrian in the new layout, but are redefined to hosts the majority of the TB’s activities and for RAS deployment, in particular for those unsuitable for interaction with vehicles, those at a less advanced stage of development, or dedicated to specific activities and simulations. Zone D is for areas where robots and vehicles coexist. As well as Zone B, it consists of two levels, depending on the nature of vehicle flow: D1 and D2. The analysis of flows (Fig. 1) also illustrates their transformation with the introduction of robots, which has a direct impact on public space, particularly on the areas between buildings, where activities merge seamlessly, centred around a central axis. By visualising the flows, we can identify the regions most affected by human-robot interactions. In order to best encode the urban space of the campus, by combining both interaction zones and flows, it is possible to identify a three-factor system that can accurately describe the human-robot dynamics that are generated. This system can be called ‘from-through-to’ and depends on both, the intended use of the buildings and the actions that robots and humans perform in the different zones. Depending on the action performed within the space, interactions can originate from either a human or a robot (from), generating a series of interactions (through) that conclude with the completion of the action on a robot – either the same robot or a different one – or on a human (to). As illustrated in Fig. 2, this system enables to comprehend the interactions that influence a location where humans and robots coexist, whether these interactions occur directly or through other robots or humans. Hypothetically, in an urban system shared by humans and robots, only in four out of twelve cases an interaction occurs exclusively between humans or solely between robots. In most cases, we encounter mixed interactions.

Fig. 2. Schematic view of the ‘Three Factor System’ for the determination of spatial interaction between humans and robots inside the Savona University Campus TB. H = Human, R = Robot.

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5 Discussion and Conclusion Moving 4.0 technologies into the public space, such as RAS, requires careful consideration of how cities will adapt to accommodate these new entities, which will inevitably interact with city processes and its inhabitants. The Savona district has been chosen as the starting point in which to test and then from which to scale up this transformation. The presence of ongoing innovation and sustainability projects on campus, with a particular focus on smart city initiatives, provides a stimulating environment for exploring advancements in urban development. Moreover, being a specialized and protected space, it attracts a specific type of user or ‘target audience,’ which minimizes the risk of undesirable consequences and facilitates the setup of a testbed. From an administrative perspective, this controlled setting proves beneficial in developing and refining policies and regulations, ensuring a secure and efficient deployment of technological innovations. Deploying RAS in the campus area and being able to decode spatial dynamics through a ‘three-factor system’ describing the type of interaction, allows to feed a DT system with a high frequency of updates, ensuring that the virtual model instantaneously represents the current state of reality. Such a feature stands as one of the essential characteristics of a UDT. The environment that humans share in urban space is not restricted to what is purely human, but must also consider other, technological intermediaries. The concept of public space cannot be ascribed exclusively to the set of interactions between humans alone, but must necessarily consider the technological, material and infrastructural elements that constitute it [42]. This should be read as an opportunity to make the environment more interactive and inclusive for both, people and machines, without compromising spaces’ liveability. Robots possess their unique way of perceiving the world, and it is crucial for us to comprehend this perspective to better design the cities of the future [43] and grasp their relational dynamics. Regarding at space planning and design, it could be assumed an approach that involves simplifying the environment to make it more easily comprehensible to robots. However, we must ensure that this simplification does not undermine the overall spatial quality. To achieve this, we can focus on the ‘software part’ by expanding connections to enhance robot prediction and response capabilities. In this regard, the development of a UDT proves to be a valuable tool [44]. Indeed, further research is required to tackle challenges related to scaling up of technologies beyond the experimental phase and investigate the evolution of conventional urban planning tools. It will be essential to disseminate TBs benefits, to make this case study experience replicable for other visionary institutions, in order to foster urban transformation and ensure a secure and well-regulated deployment of technology.

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Urban Built Environment Visual Features Modeling for 3D GeoSimulation Using USD Standard Specifications Igor Agbossou(B) Laboratoire ThéMA, UMR 6049, IUT NFC, Université de Franche-Comté, Belfort, France [email protected]

Abstract. Standards and approaches for simulating 3D geographic environments are gaining prominence in city research. Urban built environments, complex systems of interconnected visual features, serve as vital resources for urban planners, architects, and engineers, necessitating accurate modeling. Visual features play a crucial role in the digital twin process, enabling the creation of realistic representations of the built environment. Achieving visually realistic and precise urban 3D models requires effective modeling of visual features, encompassing materials, textures, and lighting. To accomplish this, accurate and up-to-date data is paramount, obtainable through various sources such as photography, satellite imagery, or LiDAR data. The Universal Scene Description (USD) emerges as a potent tool for urban simulation, owing to its capability to represent large-scale 3D models with high geometric and visual fidelity. Developed by Pixar Animation Studios, USD is an open-source technology that offers a standardized approach for representing and exchanging scalable 3D data. This paper explores the motivation of adoption and application of the USD framework for urban 3D simulation, highlighting its advantages and key considerations. It also elucidates the points of convergence between 3D geosimulation and virtual geographic environments, shedding light on the challenges associated with integrating USD with other geospatial data formats. Additionally, the article provides recommendations for optimizing USD workflows in the modeling process of urban 3D simulation. Overall, this article emphasizes the transformative potential of USD in revolutionizing urban digital twin processing. It offers valuable insights for researchers and practitioners interested in harnessing this technology for their own applications. Keywords: 3D Geosimulation · Visual Feature · Urban Built Environment · Universal Scene Description · Virtual Geographic Environment · Urban Digital Twin

1 Introduction Visual features play a crucial role in capturing and describing the distinctive characteristics of urban built environments. These visual features serve as vital input for various applications, including photogrammetry, 3D reconstruction, navigation, object recognition, object tracking and urban augmented reality [1, 2]. The significance of adequately © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 169–182, 2024. https://doi.org/10.1007/978-3-031-54118-6_16

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describing visual features was recognized as early as the 1920s within the field of visual perception, leading to the establishment of fundamental concepts that have since influenced numerous approaches for feature extraction [2]. The rapid growth of urbanization and the increasing need for urban planning and analysis [3] have driven the development of advanced 3D geosimulation techniques [4–6]. Accurate modeling and representation of the urban built environment are crucial for realistic simulations and effective decisionmaking processes. In recent years, Pixar’s Universal Scene Description (USD) standard specifications have emerged as a powerful framework for modeling and managing complex 3D scenes, offering significant advantages in terms of interoperability, scalability, and extensibility [7, 8], which is appropriate for modern approaches in urban prospective simulation and analysis. Combined with the third version of CityGML (City Geography Markup Language) in development [9, 10], the use of USD in the context of urban visual features modeling brings several advantages. First, the hierarchical and layer-based structure of USD allows for the modular composition and referencing of different visual elements, providing flexibility and ease of scene organization. This enables efficient updates and modifications to the models, enhancing the workflow and facilitating collaboration among researchers and stakeholders. Second, USD supports a wide range of data formats and can integrate diverse data sources, including aerial imagery, LiDAR data, GIS layers, and simulation outputs. This integration allows for a comprehensive representation of the urban built environment, incorporating both geometric and semantic information. The ability to merge and manage such heterogeneous data sources within a unified framework greatly enhances the realism and accuracy of the 3D geosimulation for different urban prospective and analysis. Third, USD’s robust schema and specification enable the precise definition of visual features, such as material properties, texture mapping, and lighting models. The physically-based rendering [11, 12] capabilities of USD ensure accurate and realistic rendering of urban elements, enhancing the visual quality and realism of the geosimulation results. To the question “How to reconcile 3D geometry, time and the different semantics of spatial objects/agents for a truer representation of reality?”, the aim of this paper is to present a comprehensive approach to modeling visual features in the urban built environment using USD standard specifications. After surveying keys existing standards and approaches for representing urban environments, we identified the challenges faced by digital twins and geosimulation and introduce the USD standard as a suitable solution in Sect. 2. Section 3 discusses the fundamentals and requirements of USD for urban 3D modeling. In Sect. 4, a series of experiments are presented, including experimental settings and result analysis, to showcase the advantages of the proposed USD approach compared to current methods and standards. The paper concludes in Sect. 5, summarizing the results and outlining future research directions.

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2 Urban 3D Modeling and Motivation of USD Advocacy 2.1 Background and Related Works The field of 3D data collection, storage, and management has matured, leading to increased utilization of 3D data [13, 14]. However, in urban contexts, there is a need for a comprehensive review to compare different 3D modeling methods and standards. This review would assess the efficacy, efficiency, and suitability of various approaches, provide valuable insights into advancements, and address evolving challenges. It would also guide future research and facilitate the adoption of standardized and effective 3D modeling techniques in urban domains. Contemporary 3D modeling approaches can be categorized into topological and geometric methods. Topological modeling methods focus on preserving relationships between geometries, while geometric modeling methods directly capture geographical coordinates [15]. Integration of multiple modeling methods has gained popularity to address limitations and enhance efficiencies. Examples include combining B-rep and CSG (Constructive Solid Geometry) techniques [16, 17], as well as BIM (Building Information Modeling) and CityGML approaches, resulting in improved outcomes [18]. Integration of diverse techniques overcomes limitations, enhances accuracy, facilitates interoperability, and optimizes efficiencies [19–21]. The combination of methods represents a promising avenue for advancing 3D modeling and comprehensive representation of urban environments [22]. CityGML, developed by the Open Geospatial Consortium (OGC) [9], is widely adopted for comprehensive 3D representations [23]. The Unified Modeling Language (UML) is commonly used to define relationships in CityGML. Zlatanova et al. [24] conducted a comprehensive review of topological modeling methods in the context of urban environments. Geometric modeling methods provide fast and efficient operations through direct access to object locations based on coordinates. However, they lack the ability to maintain adjacent topological relations, leading to data consistency issues. Geometric modeling methods can be categorized into points cloud, wireframe, mesh and voxel approaches. Points cloud modeling uses unstructured sets of points obtained from LiDAR data to create high-resolution and accurate 3D representations [11, 17, 24–26]. Wireframe modeling connects nodes to define the outer shapes of 3D objects [11], often utilizing point cloud data as input [17]. Mesh modeling, also known as 2.5D modeling, uses 2D data with height information to create 3D models. Procedural modeling methods, such as rule-based modeling, extrude 3D blocks based on 2D geoinformation and apply rules/algorithms for texture and facades [27–31]. Voxel and boundary representation (B-rep) employ vertices, edges, and faces to define geometric components. Voxel modeling utilizes regularly shaped grid points in 3D space, offering flexibility in adjusting scale for representation precision [16, 32]. BIM [25, 31] is parametric and integrates with 3D databases, following the Industry Foundation Classes (IFC) standard [33], for building-related information. BIM employs an object-oriented and standardized data definition language, like CityGML [34]. These various geometric modeling methods have their strengths and applications in 3D modeling, with BIM and CityGML representing significant advancements in the field [35].

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2.2 From 3D City Modeling issues to Scientific Advocacy for USD There is a wide array of geospatial software and tools available to support 3D data models and perform various functions, including viewing, generating, editing, converting, storing, parsing, and providing API (Application Programming Interface) for programmers. These software and tools are extensively utilized in certain exchange formats categorized as organizational standards such as CityGML, CityJSON, and IFC, while their usage is partial or limited in de facto standards like KML, SHP, DXF, COLLADA, and 3D PDF. Consequently, the presence of an open standardized data format holds crucial importance in the context of 3D models for geosimulation [14, 15, 20–22]. However, when it comes to developing effective visual analytics systems for 3D geosimulation, these existing standards and tools quickly reveal their limitations (Table 1). Table 1. A comparative view of usual international 3D format standards. Comparison criteria

DXF

SHP

VRML

X3D

KML

Collada

IFC

CityGML

CityJSON

USD

3D Geometry

++

+

++

+

+

++

++

++

++

++

Topology

-

-

0

0

-

+

+

+

++

++

Texture

-

0

++

++

0

++

-

+

-

++

Semantics

+

+

0

0

0

0

++

++

++

++

Attributes

-

+

0

0

0

-

+

+

++

++

Augmented reality

-

-

0

0

-

0

0

0

+

++

LoD

-

-

+

+

-

-

-

+

+

++

JSON

-

-

-

-

-

-

-

0

++

++

Georeferencing

+

+

-

+

+

-

-

+

++

++

Legend: Unsupported (-), Basic support (0), Supported (+), Extended support (+ +)

Although 3D modeling has significant potential for spatial analysis in complex urban areas, it remains a time-consuming and labor-intensive process. The existence of an internationally accepted data standard could address format harmonization issues [35–39]. Furthermore, there is a need for abundant fine-scale data, especially in areas like ventilation animation and emergency management [3, 10, 11]. Researchers in urban visual analytics must address questions regarding suitable visualization techniques, computational methods, and effective integration of visualization and computational models. Without answers to these questions, designing visual analytics solutions for urban problems becomes challenging. USD has been designed to overcome these challenges and enhance urban visual analytics by providing capabilities documented in Table 2. Leveraging USD can lead to more efficient and effective solutions in urban visual analytics.

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Table 2. Challenges related to the limitations of current urban visual simulation standards. Challenge

Description

Selected works in progress

Lack of Standardization

The lack of standardization in data formats and visualization methods across cities and organizations hinders the integration and comparison of urban data, limiting interoperability and exchange. This poses challenges for effective visual analytics on a larger scale

[8–10, 13, 19, 21, 36, 37–39]

Limited Semantic Enrichment

The incorporation of [8–10, 15, 22, 37–39] contextual information through semantic enrichment is essential in urban visual analytics. However, existing standards face limitations in describing complex urban features, impeding the comprehensive capture and analysis of urban phenomena, and hindering the progress of urban visual analytics

Scalability and Performance

As urban datasets grow in size [8, 27, 29, 40, 41] and complexity, efficient data processing and visualization techniques are essential for optimal performance. Existing standards may not meet scalability requirements, leading to slower analysis and rendering speeds. This limitation can impact real-time and interactive urban visual analytics, especially for large-scale datasets (continued)

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Challenge

Description

Selected works in progress

Integration of Heterogeneous Integrating diverse data sources [8–10, 13, 22, 37–39] Data Sources is crucial for comprehensive urban visual analytics, as urban environments generate data from multiple sources. However, current standards face challenges in effectively integrating and harmonizing these heterogeneous data types, leading to data silos and incomplete urban representations User-Centric Design

While standards provide a [8, 10, 22, 41–43] framework for data representation and visualization, they may not adequately cater to the needs and preferences of diverse user groups, including urban planners, policymakers, and researchers. Customization and adaptability of visual analytics tools to specific user requirements are essential for analysis and decision-making

3 USD Fundamentals for Urban 3D Visual Features Modeling 3.1 Concepts and Requirements of Universal Scene Description Standard In the context of modeling urban built environment visual features for 3D geosimulation, USD standard schema presents a robust and adaptable framework for representing 3D scenes and assets. Its layered composition and referencing capabilities facilitate the organization and management of intricate urban scenes. The schema provides a flexible and scalable framework for describing the geometry, attributes, relationships, and behaviors of objects within a scene. Employing a combination of JSON and binary formats, the schema ensures efficient storage and transmission of 3D data. By encompassing geometry, attributes, and metadata, it enables precise and detailed descriptions of visual features in files. Essentially, USD files contain data that dictates the appearance of a scene, which rendering applications interpret to generate images on the screen. There are several types of USD files. Readable ASCII text files have the.usda extension, offering human-readable representations. For more compact and efficient binary representations, the.usdc extension format is utilized. Additionally, USD supports a packaging format, denoted by the.usdz extension, which combines multiple USD files

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and associated auxiliary files (e.g., textures) within an uncompressed zip archive. The understanding and utilization of USD in urban visual modeling rely on key concepts. Geometry representation involves primitives like polygons, NURBS, curves, and points, enabling accurate depictions of urban elements. Instancing supports efficient rendering of repetitive objects. A stage serves as a hierarchical structure that organizes graphical information, comprising layers containing scene elements. Prims, the primary container objects, establish a hierarchy within the stage. Schemas define the interpretation of prim types using structured data. JSON and binary formats define schemas for efficient storage and transmission. Prims have attributes with types and values, allowing for default values and metadata. Attributes, prims, and stages can contain metadata for additional information. This flexibility enables the specification of material properties, environmental conditions, and other annotations for urban visual features. 3.2 Materials and Methods for Urban 3D Visual Features Modeling This section elucidates the procedures and methodologies employed for acquiring, processing, modeling, and simulating visual features in the urban environment (Fig. 1).

Fig. 1. Urban scene materials acquisition and visual features modeling workflow.

This workflow outlines the sequential steps and methodologies employed for acquiring, processing, modeling, and simulating urban visual features. It encompasses data collection, pre-processing, geometry modeling, visual features modeling, utilization of USD standard specifications for organization, and the application of geosimulation techniques integrated into the USD framework. This comprehensive approach ensures the creation of accurate and realistic urban 3D models suitable for geosimulation purposes.

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4 Experiments and Results Analysis 4.1 Experimental Settings To evaluate the effectiveness of the proposed approach for urban built environment visual features modeling using USD standard specifications, a series of experiments were conducted to design the digital twin of a housing estate [1]. These experiments utilized a representative dataset of the urban environment as depicted in Fig. 2. The dataset comprised of geospatial data, including aerial imagery, LiDAR data, and GIS data containing information about buildings, roads, terrain, and vegetation. The four categories of experiments conducted are described in Table 3. Table 3. USD-Based urban visual feature modeling process experimental phases. Experiments

Description

1- Layered Composition and Referencing Evaluation

Assessing the effectiveness of layered composition and referencing in urban visual feature modeling. A simplified urban scene was created with multiple layers for buildings, roads, vegetation, and terrain. Layer referencing and overrides were used to establish dependencies and customize the model. The experiment evaluated the efficiency, flexibility, and user-friendliness of the layered composition and referencing features

2- Geometry Modeling and Material Assignment

Focus on assessing the accuracy and visual quality of geometry modeling and material assignment. Detailed 3D models of buildings, roads, and vegetation were created using USD-supported geometric representations. Material properties like color, reflectivity, and texture mapping were assigned to enhance visual realism. The experiment involved visual inspections and comparisons with reference data to evaluate the fidelity of the models

3- Integration and Simulation

Integration of urban visual feature models into a 3D geosimulation framework. Testing with different simulation scenarios, including urban planning, traffic simulation, and environmental analysis. The goal was to evaluate the performance, accuracy, and interactivity of the model in simulating and analyzing the urban environment (continued)

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Table 3. (continued) Experiments

Description

4- Validation and Comparison

The final experiment involved validating the proposed approach by comparing the results with existing methods for urban built environment visual feature modeling. A comparative analysis was performed on various metrics, including computational efficiency, model accuracy, and ease of use. The experiment aimed to demonstrate the advantages and improvements offered by the proposed approach using USD standard specifications

Fig. 2. A captured parts of urban visual features modeling workflow using USD approach.

4.2 Experimental Results Analysis The analysis conducted aimed to evaluate the effectiveness, accuracy, and efficiency of the modeling process for urban visual features, while also comparing the results with existing methods used for urban simulation and analysis. In the first experiment, we demonstrated the hierarchical organization provided by USD facilitated modular development and management of the urban environment and the ability to establish layer dependencies. This experiment highlighted the flexibility and user-friendliness of layered composition and referencing, enabling to create complex and realistic urban scenes effortlessly. The second experiment aimed to evaluate the accuracy and visual quality of the geometry modeling and material assignment process. The findings indicated that USD offered a robust framework for creating detailed and realistic 3D models of urban features. The supported geometric representations, such as polygons, NURBS curves, and surfaces, enabled precise shape and structure representation. The assignment of materials and textures enhanced the visual realism of the models. Overall, this experiment confirmed that the proposed approach utilizing USD standard specifications resulted in high-fidelity urban visual feature models. The third experiment focused on integrating the urban visual feature models into a 3D geosimulation framework and

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assessing the simulation results. The integrated model successfully simulated various scenarios, including urban planning, traffic simulation, and environmental analysis. The performance of the model was evaluated in terms of computational efficiency and accuracy. The results demonstrated that the model exhibited real-time interactivity, enabling researchers to dynamically explore and analyze the urban environment. This experiment showcased the suitability of the proposed approach for comprehensive 3D geosimulation applications. In the fourth experiment, the proposed approach was validated and compared with existing methods for urban built environment visual feature modeling. The comparison considered metrics such as computational efficiency, model accuracy, and ease of use. The results indicated that the proposed approach using USD standard specifications outperformed traditional methods in terms of efficiency and flexibility. The ability to iteratively refine the model through layer referencing and overrides reduced manual rework and enhanced productivity. Table 4 provides a summary of the performance and improvements offered by the USD approach compared to current approaches. Table 4. USD’s metrics compared to current standards for urban visual features modeling. Metric

X3D

IFC

CityGML/CityJSON

USD

Computational efficiency

Low

Moderate

Moderate

Higher

Model accuracy

Comparable

Comparable

Comparable

Comparable

Ease of use

Moderate

Moderate

Moderate

User-friendly

Manual rework

Higher

Moderate

Higher

Reduced

Productivity

Low

Moderate

Moderate

Improved

Flexibility

Low

Moderate

Low

Higher

Here is the meaning of each metric value Low: Processing times are notably slow, hindering real-time operations. Workflow efficiency is hindered, requiring extensive time for tasks. Moderate: Processing times are acceptable but may slow down for complex scenes. Usability requires some familiarity with the system. Manual adjustments are occasionally necessary. Workflow efficiency is reasonable but may be time-consuming. Comparable: Processing times are on par with industry standards. Model accuracy is like industry-standard expectations. Higher: Processing times are notably fast, supporting real-time interactions. Substantial manual adjustments are often needed. User-friendly: The system is intuitive and easy to use for various skill levels. Reduced: Manual adjustments are infrequent due to system efficiency. Improved: Workflow efficiency is noticeably enhanced, reducing task time

5 Conclusion and Future Work Urban computing has achieved significant success in addressing various urban problems [40], and urban visual analytics plays a crucial role in empowering urban experts by combining intuitive data visualization and fast computational methods [41]. The research

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results demonstrated that the USD approach outperformed traditional methods in terms of computational efficiency, model accuracy, ease of use, and productivity, thanks to its iterative refinement capabilities. For future work, several key objectives were identified. Firstly, continual validation and benchmarking of the proposed approach against other emerging urban visual analytics standards would provide further insights and opportunities for improvement. Secondly, integrating USD with data acquisition techniques such as LiDAR, photogrammetry, and IoT sensors could enhance the accuracy and realism of urban models. Thirdly, exploring semantic enrichment and metadata standardization in USD would improve interoperability and enable advanced analysis and simulation capabilities. Fourthly, investigating mechanisms for collaborative urban modeling and data sharing using USD would enable multiple stakeholders to contribute to comprehensive urban models. Lastly, exploring real-time visualization and simulation capabilities using USD would facilitate dynamic interaction and analysis of urban models in various geosimulation scenarios. By addressing these future research directions, the capabilities and applicability of USD for urban built environment visual feature modeling can be further enhanced [37–39], contributing to advancements in geosimulation and urban planning. The four journals: IEEE TVCG, CGF, IEEE TITS and ACM TIST, and four conferences: IEEE VIS [42], EuroVis [43], PacificVis [43] and ACM CHI [40], between 2007 and 2022 offer a panorama of very inspiring work in this regard. An interactive tool to explore these articles is available at https://urban-va-survey.github.io.

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Digital Twin for Urban Development Angela Martone(B) and Monica Buonocore Università degli Studi del Sannio, BN 82100 Benevento, Italy [email protected]

Abstract. The metaverse is deemed to be the future of society, specifically in our social interaction as well as in the sectors of gaming, finance, and entertainment. There are also active efforts underway to harness the metaverse positively in one key sector that can prove beneficial: urban development. The metaverse within urban development consists on replicating the city itself, to a painstakingly accurate degree, using its digitized version to visualise and facilitate infrastructure and development, test new ideas, technologies and capabilities, and identify improvements for all aspects of urban living. By making this technology accessible to citizens and not just the corporations and agencies responsible for making these changes, any city is enabling its citizens to see the impact of changes and to feel included in the urban planning process (which has typically taken place at the municipal and government levels). Whether we are talking about a metropolis or a small town in terms of both population and land mass, its efforts with using the metaverse and digital twins to visualise, plan and facilitate urban planning, present an interesting opportunity to leverage emerging digital technologies in a similar manner. We will zoom in on a few examples of countries deploying the metaverse in varying stages to facilitate urban planning processes. Keywords: Metaverse · Urban development · Accessibility · Citizens · Inclusion

1 Introduction A growing number of cities are testing ways that immersive experiences via virtual reality and simulated cities known as “digital twins” can engage residents in new ways. What the pioneers are finding is that virtual worlds can have very real-world implications for how they lead their cities, solve problems, and serve residents [1]. Potential uses of Twin Cities include: • Virtual experimentation, for example visualisation of 3G/4G network coverage areas. • Virtual test-bedding, for example modelling and simulating crowd dispersion to establish evacuation procedures during an emergency. • Planning and decision-making, for example to analyse transport flows and pedestrian movement platforms. • Research and development of new technologies or capabilities.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 183–191, 2024. https://doi.org/10.1007/978-3-031-54118-6_17

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The research started by developing key concepts based on a narrative literature review in Google Scholar and searched for papers that included Digital Twin or Digital Twins in the title. Articles were selected from research articles and research reports. We reviewed the documents to find answers to the following questions: What is a Digital Twin and what technologies are used? Can the combination of digital twin cities and virtual reality offer a powerful tool for urban planning and design? Which digital twin project for urban development has already been implemented using citizen participation? What is the social impact that this participatory process can have? We selected research papers that defined the concept, reviewed its related technologies, and highlighted its opportunities. Section 2 provides the main perspectives and definitions of Digital Twins and technologies such as BIM, augmented reality, virtual reality and metaverse. Section 3 studies Digital Twin applications and use cases. Section 4 highlights the challenges and opportunities. Finally, Sect. 5 provides conclusions. Section 7 provides references.

2 Definitions and Technologies In 2003 Professor Grieves of the University of Michigan introduced the concept of Digital Twins in a total product lifecycle management course. It is also known as a digital mirror and digital mapping. Since then, its definition has continued to evolve as several scholars have provided varied definitions of this technology [2, 4]. Encyclopedia of Production Engineering states that “The Digital Twin is a representation of an active unique “product” which can be a real device, object, machine, service, intangible asset, or a system consisting of a product and its related services” [3]. In general, the Digital Twin is defined as virtual representations of physical objects across the lifecycle that can be understood, learned, and reasoned with real-time data or a simulation model that acquires data from the field and triggers the operation of physical devices [5, 6]. Digital Twins have moved from idea to reality much faster in recent years and can be combined with more technologies such as BIM, augmented reality, virtual reality and metaverse. Building Information Modeling (BIM) is a digital tool that can be used in urban development to create information-rich, 3D models of buildings, infrastructure, and public spaces [7]. BIM can help improve collaboration and communication among stakeholders involved in urban development projects. Overall, BIM has the potential to improve the efficiency, sustainability, and inclusivity of urban development projects. By providing a digital platform for collaboration, analysis, and management, BIM can help create more livable and sustainable cities for all [8]. Augmented reality (AR) can be used in conjunction with digital twin cities to provide a more immersive and interactive experience for users. In the context of digital twin cities, AR can be used to provide real-time information about urban planning and designers can visualize proposed developments in the context of the real world, allowing them to better understand how new buildings and infrastructure will fit into the existing urban fabric. Virtual reality (VR) is a powerful tool for urban planning that allows us to visualize and test different scenarios before they are implemented in the real world. VR can be used to include citizens in the urban design process by providing an immersive experience that

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allows them to interact with proposed designs and provide feedback, to visualize how a proposed development will look and feel in real life, which can be particularly useful for people who may have difficulty understanding traditional 2D plans and drawings [9]. This can help us to identify potential problems and opportunities, and to make more informed decisions about how to design and develop our cities. The Metaverse is a term used to describe a collective virtual shared space that is created by the convergence of physical and virtual reality. It is a new frontier for urban development that has the potential to revolutionize the way we design, build, and interact with cities. It has the potential to revolutionize the way we work, learn, and socialize. The construction of the Metaverse employs Digital Twins to completely twin the real world into a virtual space. Through real-time communication between Digital Twins and their analogues in the real world, the Metaverse realizes a virtual space in the same state as the real world, thereby constructing a digital space that combines reality with the virtual [10].

3 Use Cases The Metaverse represents an exciting new frontier for urban development that has the potential to transform the way we design, build, and interact with our cities. By prioritizing accessibility, inclusion, and citizen engagement, we can create virtual environments that are more sustainable, equitable, and empowering. Promoting accessibility and inclusion in the urban design process is essential for creating cities that are livable, equitable, and sustainable. By using digital tools, universal design principles, and community engagement strategies, urban planners and designers can help to ensure that the needs and preferences of all members of the community are taken into account in the planning and design of urban spaces. In this section we illustrate how citizen participation in urban design can be implemented by the systems of the digital twin allowing citizens to explore proposed developments in a virtual environment and provide feedback on everything from building designs to transportation options. 3.1 Virtual Singapore The first example is the “Virtual Singapore” project, which uses VR to create a digital twin of the city that can be used for urban planning and citizen engagement. Virtual Singapore is a dynamic 3D city model and collaborative data platform and acts as a digital twin of the city. It enables urban planners to test solutions without taking too many risks – especially relevant in the case of Singapore given that land scarcity does not leave any space for risky experiments. Citizens can use the platform to explore different development scenarios and provide feedback on how they would like to see the city grow and change. Singapore Land Authority (SLA), the national mapping agency of Singapore, embarked on a 3D national mapping project in 2014 to develop a Singapore Advanced Map that would represent the complex urban environment in high detail and aid in the creation of unlimited space from limited land. The reliable high-resolution, open-source

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Fig. 1. 3D digital platform to be used to run simulations using realistic large-scale scenarios of Singapore.

map data collected as part of the project would provide a digital framework for the smart nation. It would also help in the transition to a 3D-empowered Smart Nation where the data is used in applications related to national security, urban development, climate change adaptation (Fig. 2), etc. The functionality of the platform (Fig. 1) is expected to vary for different user segments, and will be rolled out in a phased manner considering the data confidentiality and privacy protocols for different segments. The Virtual Singapore platform has been made available to government agencies to enable decision-making with respect to various whole-of-government initiatives but they are still at an early stage of adoption and hence 3D city models have not been adopted at the enterprise level yet. On rolling out the 3D city model to other stakeholders, the following possible benefits with great potential for improving general quality of life can be accrued: • Citizens: To connect and create awareness and services to enrich their community. • Businesses: Utilize the 3D data for business analytics, resource planning and management, and specialized services. • Academia and Research: To research in 3D semantic modelling and create new innovations and technologies for public private collaborations [12]. Overall, VR can be a powerful tool for including citizens in the urban design process. By providing an immersive and interactive experience, VR can help ensure that citizens are engaged and informed throughout the development process, and that their voices are heard in shaping the future of their communities.

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Fig. 2. Virtual Singapore is based on Dassault Systèmes’ 3DEXPERIENCity, a scalable, single unified hub that can address architecture, infrastructure, planning, resources and inhabitants through virtualisation, simulation and collaboration capabilities.

3.2 Chattanooga Chattanooga, a city of roughly 180,000 people, is nestled in foothills of the Appalachian Mountains, situated almost equidistant from the larger cities of Atlanta, Georgia, to the south and Nashville, Tennessee to the north. While larger urban areas typically get the most attention for their digital twin projects, Chattanooga is a strong test case for the US because its smaller size allows it to be more agile, says Kevin Comstock, consultant with KCI Technologies and former Smart City director for Chattanooga. The city of Chattanooga and its various collaborators, including Oak Ridge National Laboratory and the University of Tennessee at Chattanooga, have tackled individual issues and areas by creating digital twin projects. The first project, called “CTwin,” focused on one of the city’s major roadways to examine mobility-related energy use by building a digital representation of traffic signal infrastructure, says Comstock. Another ongoing project uses sensors and laser imaging at intersections to monitor pedestrian movements and compare it to vehicle traffic, in the interest of safety (Fig. 3). Lehtola is a former city councilor in Espoo, Finland, just outside of Helsinki. He says when a new metro line was proposed, Espoo first digitized the planning of the operations and construction (Fig. 4). The digital twin can reveal what the finished job will look like, Lehtola says, “so you could show (the public) for example, if there’s some construction work or land development taking place, what is the outcome, how it will look, and then also get more precision on the estimates on the benefits and useability and added value of different projects.” [11].

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Fig. 3. This digital twin of a city block in Gothenburg, Sweden, shows simulated noise levels from street traffic, visualized by a heat map on the surrounding street and building surfaces.

Fig. 4. How digital twins are used for urban planning.

4 Challenges and Opportunities It is important to remain mindful of the ethical and social implications of this new technology. One of the most exciting aspects is the opportunity for citizens to become cocreators of their own virtual environments. This means that individuals and communities can actively participate in the design and development of the \, shaping it to meet their needs and aspirations.

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By empowering citizens to become co-creators, we can create a more democratic and participatory urban planning process that is truly responsive to the needs of the people. Involving citizens in the urban development and design process is important to ensure that their needs and perspectives are taken into account. BIM can be used to facilitate citizen involvement by creating 3D models that can be easily visualized and understood by non-experts. These models can be used to solicit feedback from citizens and to help them understand how proposed developments will impact their communities. One way to involve citizens in the BIM process is to use interactive tools that allow them to explore and manipulate the models themselves. For example, some cities have developed online platforms that allow citizens to view and comment on proposed developments in real-time. These platforms can be used to gather feedback on everything from building designs to traffic patterns, and can help ensure that citizens are engaged and informed throughout the development process. Another way to involve citizens in the BIM process is to use virtual reality (VR) and augmented reality (AR) technologies. This can be particularly useful for people with disabilities or mobility issues, who may have difficulty visiting physical locations in person. Accessibility is a key consideration in the development of the Metaverse. As virtual environments become more complex and immersive, it is important to ensure that they are designed in a way that is inclusive and accessible to all. This involves taking into account factors such as visual impairments, hearing impairments, and mobility issues. By prioritizing accessibility, we can create a Metaverse that is welcoming and empowering for everyone. Accessibility and inclusion of citizens in the urban design process is essential for creating cities that are livable, equitable, and sustainable. Citizen participation in the design and planning of urban spaces can help to ensure that the needs and preferences of all members of the community are taken into account, particularly those who have traditionally been marginalized or excluded from the planning process [12]. Inclusion is a key theme that runs through all of these areas. It involves creating environments and systems that are welcoming and accessible to everyone, regardless of their background or abilities. By prioritizing inclusion, we can create more equitable and sustainable communities that benefit everyone. The Metaverse has the potential to be a powerful tool for fostering inclusion and diversity. By creating virtual environments that are accessible and welcoming to all, we can break down barriers and promote greater understanding and empathy. This can have a transformative impact on urban development, as it opens up new possibilities for social interaction, cultural exchange, and community building across geographic and cultural divides. One way to promote accessibility and inclusion in the urban design process is to use digital tools and platforms. Digital tools can help to engage citizens in the planning process by providing them with real-time information about proposed developments and allowing them to provide feedback and suggestions. For example, online surveys, interactive maps, and virtual reality simulations can be used to gather input from a wide range of stakeholders, including those who may have difficulty attending in-person meetings.

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Another way to promote accessibility and inclusion is to use universal design principles in the planning and design of urban spaces. Universal design is an approach to design that aims to create environments that are accessible and usable by all people, regardless of their abilities or disabilities. This includes designing buildings, public spaces, and transportation systems that are accessible to people with disabilities, as well as those who are elderly, pregnant, or traveling with young children. Finally, it is important to ensure that the voices of marginalized communities are heard and taken into account in the planning and design process. This can be done by engaging community organizations and advocacy groups, and by providing opportunities for residents to participate in decision-making processes [13]. It is also important to ensure that the benefits of urban development are distributed equitably, so that all members of the community can benefit from improvements to the built environment.

5 Conclusion Urban development can have a significant impact on our communities. It involves the planning and design of cities and towns, with the goal of creating livable and sustainable environments. By providing a more immersive and interactive experience, AR can help to engage citizens and decision-makers in the urban development process, and to promote more sustainable and efficient urban systems. Furthermore, virtual reality can enhance citizen engagement by allowing residents to explore and provide feedback on proposed changes to their neighborhoods and communities. This can help to build trust and collaboration between citizens and urban planners. This opens up new possibilities for urban planning, such as creating more sustainable and accessible cities, improving transportation systems, and enhancing citizen engagement. By providing a more immersive and interactive experience, VR can help to engage citizens and decision-makers in the urban development process. As the technology continues to evolve, it is likely that we will see more cities adopting digital twin models with VR to help them address the complex challenges of urbanization. The development of digital twin cities, combined with the use of virtual reality (VR), offers tremendous potential for the future of urban planning and design. Digital twin cities are virtual replicas of physical cities that can be used to simulate and test different scenarios for urban development and management. By using real-time data and artificial intelligence, digital twins become virtual, living mirrors of their physical counterparts, providing opportunities to simulate everything from infrastructure to public services [12]. We define community engagement as any process that involves the input of community members in city problem-solving or decision-making. We believe that meaningful community engagement is an open, two-way dialogue that uses public input to make sustainable decisions. The growing demand for automation in various industries are the anticipated factors to trigger the high demand for the Digital Twin platform over the forecast period. As we recover from the pandemic, Digital Twin solutions are poised to play an increasingly important role in different industries. The benefits of creating a Digital Twin solution are too vast and still not fully explored. While there are challenges to addressing data

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quality and security, increased demand for power and storage, and integration with existing infrastructures, Digital Twin solutions are thriving to provide a highly advanced digital revolution to make the world a better place for humankind. In the future, Digital Twins will expand to more use cases and industries. The solutions will combine with more technologies, such AR, for an immersive experience and AI capabilities for better connections, insights, and analytics. In addition, more technologies enable us to use Digital Twin solutions, removing the need to check the ‘real’ thing. These exponentially higher insights and analytics, in turn, lead to even more possibilities for applications of Digital Twin solutions in complex operations.

References 1. Bloombergcities. https://bloombergcities.jhu.edu/news/virtual-realities-how-cities-are-mov ing-metaverse-and-beyond. Accessed 13 May 2022 2. Jones, D., Snider, C., Nassehi, A., Yon, J., Hicks, B.: Characterizing the digital twin: a systematic literature review. CIRP J. Manuf. Sci. Technol. 29 (Part A), 36–52 (2020) 3. Stark, R., Damerau, T.: Digital twin. the international academy for production engineering. In: Chatti, S., Tolio, T. (eds.) CIRP Encyclopedia of Production Engineering, pp. 1–8. Springer, Berlin Heidelberg (2019) 4. Tao, F., Zhang, H., Liu, A., Nee, A.Y.C.: Digital twin in industry: state-of-the-art. IEEE Trans. Ind. Inf. 15(4), 2405–2415 (2018) 5. Bolton, R.N., Mccoll-Kennedy, J.R., Cheung, L.: Customer experience challenges: bringing together digital, physical and social realms. J. Serv. Manag. 29(5), 776–808 (2018) 6. Negri, N., Berardi, S., Fumagalli, S.: MES-integrated digital twin frameworks. J. Manuf. Syst. 56, 58–71 (2020) 7. NOVATR. https://www.novatr.com/blog/benefits-of-bim-in-urban-planning. Accessed 10 May 2022 8. GEOSPATIAL WORLD. https://www.geospatialworld.net/blogs/role-of-bim-in-urban-con struction/. Accessed 10 May 2022 9. ResearchGate. https://www.researchgate.net/publication/352802317_Citizen-Cetered_D esign_in_Urban_Planning_How_Augmented_Reality_can_be_used_in_Citizen_Participa tion_Processes. Accessed 10 May 2022 10. Dionisio, J.D.N., Iii, W.G.B., Gilbert, R.: 3D Virtual worlds and the metaverse. ACM Comput. Surv. 45(3), 1–38 (2013). https://doi.org/10.1145/2480741.2480751 11. GEOSPATIAL WORLD. https://www.geospatialworld.net/prime/case-study/national-map ping/virtual-singapore-building-a-3d-empowered-smart-nation/. Accessed 12 May 2022 12. CNN. https://edition.cnn.com/2023/01/31/world/digital-twin-cities-tnf-spc-intl/index.html. Accessed 13 May 2022 13. CityLab. https://www.bloomberg.com/citylab. Accessed 13 May 2022

Digital Twins of Cities vs. Digital Twins for Cities Maria Rosaria Stufano Melone1(B) , Stefano Borgo2 , and Domenico Camarda1 1 Polytechnic University of Bari, Bari, Italy

[email protected] 2 Laboratory for Applied Ontology, CNR-ISTC, Trento, Italy

Abstract. The notion of Digital Twin (DT) gained attention about 15 years ago when sufficient computational capacities became available allowing to develop and run so-called virtual copies of a given physical product. As the evolution of so-called smart cities led to the integration of data-driven decision systems in the traditional urban infrastructure, DTs may become an important element for decision-making in urban contexts but, given the specificities of the latter, here DTs cannot be passively adopted. Information devices and artificial intelligence made their way into city management, but the city cannot be reduced to a digital computer nor an automatised factory indeed. As argued in literature, a city can show a number of structural components such as place, agents, knowledge, and their diverse interaction can make each city special, the urban environment a category on its own. We propose to analyse DTs in the light of these characteristics of cities to understand what role they could play. Keywords: Urban planning · Decision support · Digital twin models · Applied ontology · Ontological Analysis · City component

1 Introduction Artificial Intelligence (AI) has evolved considerably in the last ten years and its recent applications are being increasingly successful. This has determined an increasing interest in the opportunity and possibility of the management and representation of knowledge for complex systems like the city and, more generally, the planning and management of the territory and the environment. We work in this line of research with the aim to enrich AI methodologies with techniques coming from another successful research area, namely, Applied Ontology [3]. An ontology is a conceptual artifact [2] which provides a common disambiguated vocabulary for the experts and the practitioners who need to share information in a domain. It is particularly suitable for disambiguation and knowledge sharing between heterogeneous (human and non-human) agents beyond the subtleties of natural and technical languages. It is particularly suitable for man/machine interaction, useful for defining objects, attributes, relationships, even dynamic ones, that populate (and animate/activate) a system. In this work, we refer to a specific foundational ontology called DOLCE [4]. In line with the above characteristics, the aim of this research line is to investigate and eventually develop an effective decision support system for the city. A city, and © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 192–203, 2024. https://doi.org/10.1007/978-3-031-54118-6_18

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more so a smart city, is a complex system where data and knowledge are collected and exchanged in many ways. Recently, to cope with the complexity problem, it has been proposed to adopt a concept developed in manufacturing, namely that of DT [10], to model the city. We believe that this proposal requires to reflect on what a DT for the city could be given the challenges of collecting, representing and sharing knowledge of the city, and the particular flexibility in interacting with Socio-Technical Systems (STS) that this approach can offer. A DT of the city, to be meaningful, must be able to model important components of the city [19], among which the population and the in-city artificial world, as well as to allow to interpret and evaluate the intentions, needs, strategies and visions that characterize the city itself. The paper is structured as follows. In the next section we describe what is a city from an ontological viewpoint according to our previous research. In Sect. 3 we reflect on the DT vision and actuality, as well as on criticalities in using DT to model cities. The fourth section deals with the roles of inclusive participation and spatial cognition to challenge the limits of city models, whereas Sect. 5 explores the case study of an urban square. Final remarks are discussed in the concluding section.

2 Cities from an Ontological Viewpoint This section reports reflections on what a city is, with a particular focus on the smart city from an ontological point of view. Applied ontology is investigated in the literature as a useful approach for a coherent, comprehensive and clear modelling of the inherent variety of living environments, particularly urban ones [1, 4]. There is no definitive definition of a city, but many of them are close to describing its different aspects. Cities are dynamic and often polycentric systems [5], and the smart feature is supposed to increase the city ability to structure and manage relations, services and connections. Data are typically collected by distributed sensors and by the people who provide (intentionally or else) information and impressions, with all the known risks of data aggregation and meaning extraction. With the smart city, knowledge has acquired a new status in the history of the city, and the potential to be the key component in the modern city evolution [1]. The new technologies help to interpret environmental and cognitive complexities by monitoring characteristics and relationships and thus identifying and managing emerging properties [8, 9]. In this framework, agents are endowed with new characteristics and needs identifiable in these emergent properties whose integration into the city as a whole leads to multiple and differentiated behaviours [6, 7, p.53]. Hence, the smart-city concept indicates a new way for the city to exist, perdure, and progress as both a multi-agent entity and a whole. Carrying out an ontological analysis for eliciting the fundamental components of the city, we elicited three principal components: (i) the place as distributed materiality, (ii) the community as multi-layered agentivity, and (iii) the knowledge as a whole made of data, models and meanings. According to this analysis the city can result from an interaction between these ontologically distinct components. Interactions and their nature are as necessary as the qualification of the components themselves: this means that the mere presence of components is not sufficient for the existence of a city [1]. Therefore, we are conducting an analysis to elicit how the components of the city interact and how they are inherently entangled. The city-place component is the physical manifestation

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of the city elaborated by the continuous large and small changes that happen in the city which can have varying degrees of coordination and intentionality, or even lacking those. The city-agentive component explains the dynamic evolution of the city with the interplay between the individuals, organizations and communities. The city-knowledge component takes into account the information world that a city produces and enriches the city with the capacity to represent itself and reason about its parts, to modify the relationships among its parts as well as to lead the evolution of the whole [1]. In this conceptual framework we imagine that the process of ‘smartification’ of the city can help the development of communities with new self-awareness and conscious intentionality. This would renew systems and networks and likely produce important transformations in the social fabric of the city itself. It is a sort of new emerging ‘substance’ made of interactions and decisions based on shared knowledge, which is co-created but which at the same time may be largely unknown to single individuals. How can we represent this ‘substance’ (or layer) that emerges from the knowledge of the city? It might be that the DT technology could be an important support in the representation and sharing (ideally in real time) of emerging intentions, emotions, decisions, both at the individual and at the collective levels. For example, if the knowledge component could be suitably represented in the DT, the latter can act as a tool for modelling the agency component of smart cities (in the form of collective agents, administrators or individuals) in deciding which actions to take, how to intervene (modify or preserve) in a physical place or with respect to some events. This decision would bring about a change which, in turn, will feedback the DT model, changing the knowledge component and generating new data and new interpretations by individuals and by the community. This experiment could be carried out in (portions of) a smart city harvesting the approaches in STS and the availability of sensors (as data-creators).

3 Vision, Actuality, and Failing Cases of City DTs The notion of Digital Twin emerged several times in the second half of the XX century as a natural application of the developing computational capabilities and the increasing interest in digitalization, and eventually became a driver for research in the early 2000s in the context of manufacturing where DTs were seen as a virtual companion during the product life-cycle [10]. The core of the notion of DT is easily said: since engineers use structural, processual, and functional models of products, and these are developed using different assumptions and methodologies, if we succeed in integrating these models with models of physical reality and materials, it becomes possible to reliably simulate the state and behavior of the whole product in real time and even to use this simulation to anticipate possible undesired events, like failures, and to optimize the product’s behavior. This goal requires to keep the evolution of the physical product and the evolution of the DT aligned. Due to the different nature of the two entities, their states most likely diverge over time. This mismatch can be minimized by a (possibly continuous) exchange of data from the product to update the DT. In turn, the DT allows to fast forward the simulation of the product’s behavior anticipating possible problems before their actual occurrence. In this way, the product manager can preventively modify the working parameters or schedule just-in-time maintenance activities to reduce the risk of failure.

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From the previous description, the interest on DT is due to its capacity to (wholly) describe, control from afar, and anticipate at will the changes in the structure and behaviors of a physical object. By physical we mean an object that has a spatial location and is composed of material and, possibly, non-material parts. Non-material parts are located entities like holes, cavities and voids that may be necessary for an object like, e.g., an engine, a building or a pipeline. These holes can be temporarily or constantly filled (by air, water, material etc.). In practice, these capacities of a DT are obtained at the cost of relatively inexpensive computational systems (the costs of the simulation might still be considerable due to the need of advanced and dedicated hardware and software, it may even require a continuous monitoring by humans) compared to the costs of repairing the physical object and the indirect costs of interrupting functioning and related activities. After all, reliability has been a key feature in engineering from the 1950s and a series of methodologies have been developed to ensure it (scheduled maintenance, regular inspection, material and structural tests etc.) [11]. These methodologies are themselves costly (scheduled maintenance is often overabundant) and can prevent only some types of failure (like those due to worn components). If the use of DT is clearly an innovative approach to reliability, the development of DT requires solving old problems while raising new ones. Some product models are static (like structural models) while others are dynamic (like processual models); some are discrete (like the Bill of Materials, BOM) while others are continuous (like operational models of, e.g., welding); some are linear (like the input-output models of a fluid container) while others are intrinsically non-linear (like the flow turbulence in a fluid container). The diversity of the models relevant in engineering to describe and control a product is a major difficulty to achieve a global and integrated view of the product itself. This integration is part of the vision behind the DT and the important differences across the models are clearly an obstacle. Even though one may aim to align models without pushing for a full integration, that is, one may aim to share the data of one model with another without merging them into a single comprehensive system, there remain important difficulties due to differences on aspects like granularity, theoretical assumptions, needed core data, and so on. Finally, applied ontology has pointed out that even implicit assumptions in building models (e.g., how to model properties and how to identify those that are essential) can prevent the integration of models that at first sight might seem quite similar. On top of this, the concept of DT requires to develop a strong mutual dependence between the physical and the digital worlds which are, by their nature, different even when we restrict ourselves to the information they use and manage [12–14]. From the previous observations, most DT efforts aim to build very limited versions of the ideal DT, practically in many cases they are better seen as data integration efforts. Nonetheless, the goal of integrating large datasets containing heterogeneous information already pushes for the development of improved and possibly innovative approaches to optimize services. Coming back to the study of cities, the DT vision allows to introduce new optimization methodologies for infrastructures (e.g., water and electricity distribution) and to reduce availability issues in services (e.g., traffic congestion and recharging stations monitoring as in the Snap4City initiative)1 . 1 https://www.snap4city.org.

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Aside the theoretical and technical difficulties to build suitable DTs, there are already experiences of the application of DT inspired approaches. It follows from our discussion that these experiences tend to focus on some aspects of the city environment, in particular those that are easily measurable by today’s inexpensive and broadly available sensors and that have an important social impact. Typical examples are the enrichment of closedcircuit television systems (CCTV) to control crime in urban environments. The message is that video recording and automatic analysis of video data can start a virtuous cycle to deter the occurrence of criminal scenarios. This view has been largely supported by police and political authorities over the years suggesting that criminality could be reduced by AI control techniques and is relevant to our discussion since it embraces the same data collection approach behind the development of DTs. Today there are many cases of large cities with impressive CCTV systems where the increased presence of video surveillance does not correlate with a decrease in criminality rates. Quite the opposite.2 On the contrary, the reliance on digital models can cause new problems at a scale that was not foreseen before. An example is given by the case of Toronto where the development of a digital layer suitable to monitor city services at large (from autonomous garbage collection to street crossing to park bench usage) created a new type of problem linked to “the idea of the city as something to be quantified and controlled”3 . Therefore, the mechanistic interpretation of the city that underlying these modelling methods and devices is actually raising new kinds of risks. Where one sees messiness, others see compelling and serendipitous interactions; where someone sees confusing and unregulated situations, others feel a sense of enriching diversity and proximity. This, and the sensibility towards privacy of data and behaviors (like in the case of the city of Marseille4 ), lead to a series of concerns that shattered some technological programs devised for the urban environment.

4 Managing City-Modeling Limits: The Key Roles of Participatory Technology and Spatial Cognition There is a long, difficult history of community inclusion processes in spatial planning. The overwhelming diffusion of smartphones and the progressive economic liberalization of data lines today largely reduced problems, allowing to fine-tune cognitive interaction processes and build real-time dynamic databases [15]. However, some problems remain, like the difficulty of interaction by digital non-natives. And these cognitive agents are essential in the cognitive arena of weak voices, expressions of needs and capable of visions structurally useful for a planning process [16]. Starting from this framework, an inclusive DT construction process is technologically structured and demanding. On the one side, it requires specific skills and greater availability of technological resources. On the other side, it requires a granularity of cognitive tessellation, as detailed as the geminal compliance goals to be achieved. In this context the very interpretation of the concept of ‘twin’ is a relevant criterion for the 2 For a discussion, see the reports in https://restofworld.org/2023/cctv-crime-surveillance-india/. 3 https://www.technologyreview.com/2022/06/29/1054005/toronto-kill-the-smart-city/. 4 https://www.technologyreview.com/2022/06/13/1053650/marseille-fight-surveillance-state/.

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definition of those goals and for shaping the entire construction process of the urban DT model, hereafter called UDT. Hence, the still growing debate around the levels of adherence of the model to the real context is critical per se. From an exclusively physical level up to social and behavioral levels, the choice of one degree of adherence over another is not indifferent. In this context, ontological analysis of individual levels of complexity may be relevant, also for application purposes, as suggested by some recent studies [17]. The cognitively participated construction phase is followed by a subsequent stage of use of the model for inclusive decision support. In addition to aspects of participation complexity, there are important aspects relating to the forms and contents of knowledge, involved as a substantive part of decision-making processes. As in classic applications of the DT, an UDT model should allow the definition, simulation, control and possible correction of urban and environmental decisions, in a more informed, aware, situational and dynamic way [18]. However, a mechanical digital model already shows problems of consistency with the physical, tangible or sensorially perceivable elements. This virtual model allows, for example, to simulate mechanical actions capable of returning comparisons and parallels and of verifying possible impacts in relation to the real mechanical product. It is therefore clear that the context of participation must include relevant agents for those actions performed on the virtual model, each of which is an expression of cognitive contents suitable for supporting operational decisions. We can think of agents from some well-known domain of knowledge, like an expert (formalized or experiential) type [19]. Modes of cognitive interaction by these agents are codified in a DT in a direct way. The debate about the UDT initially focused on this perceivable configuration determining what was represented of the city or of parts of the city. Models of three-dimensional representation of urban geographic areas through GIS, for instance, are among the first proto-examples of DTs in the literature [20]. A subsequent integration with BIM (Building Information Model) models explored a possible extension towards more explicit functional characteristics of the built areas [21]. However, if real urban contexts are a complex expression of differentiated ontological levels, as mentioned above, clearly these models can capture only a partial urban DT, failing from the start to comply with the DT vision. In this framework, the participation process oriented to support decisions through that typology of UDT, has some characteristics that are however interesting. First, it is used as a support for the simulation of scenarios and spatial impacts, for example of urban transformations, at an eminently physical but also - more indirectly - socio-economic level. In this mode of simulation there is a field of research about the concept of geodesign, originally developed on the inclusive potential of the so-called public participation GIS (PPGIS) [22]. In a knowledge elicitation process, the model in this case can represent a basis for the cognitive interaction between different agents. They enrich the geodesign model through the collected individual knowledge contents, towards the realization of decision support scenarios. However, contents with low formal structuring, high complexity, as well as with dynamically variable contents have typically shown poor integrability into these processes so far [23, p.140]. Then there were other lines of research developed in limited and circumscribed contexts, especially physically confined such as halls and museums. In them, technology-based models of virtual reproduction of spaces have instead explored spatial decision processes in dynamic situations. However, even if built through multiagent

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cognitive interaction processes, these models still orient the use of DT-inspired technologies towards the support of single-agent activities [24]. The extensive use of applied ontologies for the representation and management of spatial complexities remains interesting, especially in the latter cases [25]. They seem able to offer perspectives of complex representation, useful in paths towards the possible creation of UDTs. Yet managing complexity remains a hard point in public decision-making and planning. In the twentieth century dominated by world wars, planning is increasingly filled with needs of public interest, also depending on the emerging need for demand support. Rational models of urban decisions are undermined by an increasingly evident complexity of agents with a relevant voice in the decision-making arenas of cities. The structural limits of a rational approach emerge when dealing with multiple communities, full of social, political and economic distortions compared to a simple metrically predetermined organizational model. And the principle of environmental sustainability further enhances the complexity of the urban system. Together with attempts of planning renewal, the traditional orthogonal model still persists [32, p.22], due to its easeness of realization – but there is an important misalignment with the complex reality that it should model. The evolution of GIS-based models is also moving in this direction. They are increasingly used as fine representation models, even in 3D renderings, of the city and of its physical territories. This results in a typical exclusion of models of relationships, behaviors, cognitive interactions that are difficult to formalize geographically through metric parameters and dimensions. GIS are also used as simulators of dynamics but these applications are always physically-based, as in the case of climate forecasting models [26]. In this framework, the representative GIS-based metric system seems to be necessary but not sufficient to define such a model as UDT. In fact, following its own definition and application origin, a DT should allow complete simulations, verify behaviors, cognitions, understand relationships, verify the systemic effects of impacts, etc. It should include aspects intrinsic to the represented system (for example intangible characters such as cognitive aspects or individual needs, etc.) as necessary parts for the mechanics of the system, just as expected by the concept of DT [18]. In this framework, a UDT should aim to mirror the complexity of the system it represents, not to reduce or simplify it to achieve (apparent) manageability. Indeed, the comprehensiveness of a socio-spatial decision support model has been a debate area in decision theory for a long time [6]. The final awareness of its intrinsic limits has led to a season of growing methodological renewal which today guides the search for decision support architectures. The potential offered by improved technological and IT capabilities allows to deal with complexity through equally complex descriptive and interpretative models – such as applied ontologies [25]. In this context, recent research has proposed the evolution of BIM models towards BIM-DT as an example of partialized models of urban DTs. However, it is difficult to expunge from the organism to model its non-physical characteristics without undermining the representation. Case studies on the behavior of residential agents in housing units have reported, for example, the relevance of different energy behaviors in increasing the phenomenon of the so-called urban heat island [27]. Also, the partial essence of BIM undervalues the dynamics of behavioral relationships beyond the building installation.

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Hence, relational links with the system should be maintained, to preserve its inherent complexity. Applied ontologies show useful methodological support also in this area. Ultimately, it can be said that the development of a DT model that can be considered suitable for the city should be geared towards structurally and operationally managing this complexity.

5 A Use Case: A City Square Following the previous observations, a city-place component, a city-agency component, and a city-knowledge component should coexist, integrate and interact in the ‘translation’ of the DT model. What forms of knowledge should be present in a DT of a city? It should involve the city in its complex entirety, but a smaller system exemplification could be useful – without necessarily meaning that a DT should entail just detached parts. Let’s focus on a more ‘measurable’, highly significant, and symbolic element: the urban square, narrating the habits and social customs of city people. It refers to a precise ‘type’, made up of primitives (such as geometric shapes to be managed) and needs (such as functions to be performed). Both primitives and needs are dynamic generators relating to more complex concepts, and the shapes of the square derive from the same primitives and the same needs. Palladio in 1570 distinguishes public urban types into full (buildings) and empty, and among the latter he includes squares. Similarly, two centuries later Durand includes the squares in a more articulated list of urban typologies. Therefore, by extension, we can apply the ontological analysis previously developed for the architectural type to the square. The DT of a square should include the dimensions for the analysis of types: the objective constraints (shape, surrounding environment, functionality, affordances, living style/social level), subjective constraints (abstraction and structure interpretation; memory; intentionality; creativity; sense of a liveable space), both collective and individual [28]. This ontological analysis allows to clarify and manage some of the complexity of references, constraints, functional goals and establish the relationships between expert and non-expert knowledge. This is necessary for the construction of a UDT that also contemplates the relationships between the components (place-agency-knowledge) and the reciprocal modifications and evolutions. This is the background informing and populating the UDT. The UDT of a square should include the information relating to the agency component of the city. Already in the construction phase, the UDT should integrate aspects of use, habits, customs, which alternate in the space of the square within the cyclical nature of day/night, of the days of the week, of the annual recurrences. It should also integrate different groups of agents, who alternate in the square or who coexist, sharing the use of the square itself as described by Calafiore et al. [29]. And it should include the observation of events that change habits, enriching or diminishing them or confirming them: a new installation, a new gradient, new benches, old flower beds. This is possible with a work of analysis and observation, also sociological/anthropological, of interaction with space, integrated by conscious participation. To this one has to add, like a second layer, the knowledge component referred to the square. It emerges from the known use of the square as well as from the translation and integration of what is elicited (or collected) from sensor devices, from sharing platforms, and possibly from ad hoc

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approaches. The flow of data from sensors participates in this component of knowledge: both the sensors ‘following’ the agents, and the sensors ‘following’ the STS.

Fig. 1. Example of a relational map of the ‘literary’ square (bold = nouns, locutions; italic = adjectives; other = verbs) [30].

The latter takes care of following and recording the environmental conditions affecting the square: a sensor system that records the sunrise (light/shade trend), or the direction and intensity of the winds, or even the presence of pollen, or pollution in pm10 or carbon dioxide, humidity, temperature and other possible dynamic events useful to monitor. But the knowledge that can be gathered and integrated into a UDT relating to an urban square does not end there. The collection of knowledge, even in its more nuanced and delicate, or dramatic meanings, can be carried out by searching, for example, within literary productions, whether they are essays, or novels or even poems. In this context, we have previously analyzed the square (“piazza”) according to the integration of knowledge deriving from a literary work such as Italian poems through applied ontology [30]. An excerpt of this work is in Fig. 1 (Italian is maintained for consistency of meaning and syntactic links, yet translatable if needed). The representation of a square as a UDT could appear as a 3D model of itself, populated/animated by agents, by fluxes which, for example, identify the passing of the wind, or heat islands, or emotional intensity that gathers in the square, or simply the density of crowding and information. It should be inclusive for non-humans, for example with sensors that detect the presence of bees or bird species or swallows. It might include pop-up text boxes like ads or information exchanges knowingly or not. From this brief examination it can be seen that a UDT of an urban square is effective only if it is complex and inclusive. The UDT should reproduce the square system in its complex entirety, including the components that we have identified as making up the city as a whole, albeit characterized by a cross-border passage between the three identified components which is incredibly nuanced - but structural.

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6 Conclusions “A city is more than a place in space, it is a drama in time” [31]. The paper tried to address the issue of DTs applied in the urban context, framing it within the broader chapter of model-making for urban decision and planning. Problems of various types and genesis have emerged. First, there is the question of urban modeling, a harbinger of good potential for decision-making and operational support, but also of simplifications that reduce the intrinsic complexities - and with them its very usefulness, increasing the risks. Simplifications do affect typical aspects of a system, such as, for example, the manifestation of new and emerging elements and properties, or the role of evolutionary and behavioral dynamics. An UDT, but before it an urban model, should allow the consideration of these elements in order to usefully fulfil their prerogatives. Second, the animated, or hybrid animated/non-animated matrix of a UDT differs fundamentally from the original concept of a DT. In fact, it was born as a gem copy of a non-human artefact, typically mechanical and/or electronic, bringing with it cloning refinements, and related operational utilities, consistent with those finely codified and controllable contexts. There is no trace of this in the city, beyond the pervasive physicalities that are sufficient at most to describe its envelope. Much more representative of the functioning of a city are its different components, physical and immaterial, biotic and abiotic, behavioral and relational, static and dynamic, perduring and enduring. Today the conceptualization of urban DT, even before its actual construction, must deal with this multifaceted complexity. The research on which this work is based follows the possible role of applied ontologies for modeling the city. Again, this is not an easy exercise, although a conceptualization exercise arguably includes less immediately operational aspects than a UDT artifact. In this context, the present work has proposed an operational approach that divides the complexity of an urban twin into a more controllable and, within certain limits, codifiable context. The construction of an ontology of the urban square is presented here as a perspective of controlled exploration of an urban DT, which can include multiform and multilayer features and relations. The common thread of this ontological exercise is the structured management of knowledge, both formalized and codified through data such as sensors, and common-sense-based through cognitive interaction with living agents actually using the analysed context. Building a UDT of a square can help to better understand a comprehensive digital urban twin, its limits and potentials even before actually building it. To this aim the analytical and modeling efforts of our research group will be directed in the future.

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Beyond the Smart City. The Urban Digital Twin for the Augmented City: The Vox Hortus Project Romano Fistola1 and Ida Zingariello2(B) 1 University of Naples Federico II, Naples, Italy 2 University of Sannio, Benevento, Italy

[email protected]

Abstract. The Urban Digital Twin (UDT) represents an innovative new dimension for urban planning capable, not only, to replay the corresponding physical twin in all its properties but also and specially, to implement the interaction with our cities through the addition of any type of information content. Thanks to the tools of City Information Modeling and Augmented Reality technologies, the information content of the UDT can be interrogated, updated and shared among planners and political decision makers, and with citizens. Based on the type of information content, the UDT makes various planning actions possible and allows to start of different perceptive experiences, such as the prefiguration of urban transformations; the virtual recombination of historical heritage; the augmented use of the city with a new way to polarize tourist flows as well. With regard to this capability of the UDT, the present work intends to describe how it is possible to regenerate an urban context by using augmented reality. The case study is focused on one of the most iconic spaces inside the city of Benevento: the Hortus Conclusus. This little open-air space, inside the inner city, contains the artworks of the famous modern artist Mimmo Paladino that are been geolocated inside a project called Vox Hortus which allow the visitors to listen to the voice of the masterpieces through an augmented reality audio application. Keywords: Smart City · Urban Digital Twin · City Information Modeling · Augmented Reality

1 Introduction Technology assumes a central role in supporting informed knowledge and decisionmaking processes, which are indispensable to orient the urban system towards a sustainable evolution compatible with the available resources. It is necessary to consider new paradigms for understanding urban dynamics and to adopt technological innovation in the knowledge processes, interpretation, modelling, planning and management of the city. In this sense, it appears useful to note that, from a theoretical-methodological point of view, it is necessary to overcome the rhetoric on the smart city and develop a new reflection on the technological paradigm applied to urban planning. The main element © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 204–210, 2024. https://doi.org/10.1007/978-3-031-54118-6_19

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of incongruence of the smart city lay in urban planning practices that saw technologies “added” to the city and not “adopted” by the processes of governance of territorial transformations. Technology should not be instrumentally added, but introjected for the redefinition of urban planning methods and procedures [1]. From this awareness it is necessary to start a new reflection for a disciplinary redefinition that adopts technological innovation in all phases of the urban planning process in order to govern the evolution of the complex urban system in a sustainable way.

2 The Urban Digital Twin, Beyond the Smart City The discourse surrounding the concept of urban digital twin has reached a mature stage in research, marked by numerous global experiments. Major cities worldwide are currently constructing their digital twins based on models that accurately replicate the functioning of urban systems. Similar to historical trends, where urban scientists analyzed city transformations to develop theories describing past urban developments (such as the emergence of smart cities), we are now at a juncture where we can propose a methodological approach to comprehend the phenomenon of urban digital twins. A digital twin is commonly defined as a virtual representation of a physical system, including its environment and processes, which is continually updated through information exchange between the physical and virtual realms [2]. In the context of a city model, this implies the creation of a digital environment that mirrors the city’s physical space. Furthermore, adhering to a systemic approach to city interpretation, it is evident that cities can be conceptualized and depicted as complex dynamic systems [3]. The concept of urban digital twins builds upon previous research in urban modeling, spanning from the works of Christaller to Wilson, extending beyond the scope of the smart city model. As recently stated, “Urban digital twins have the potential to revolutionize the smart city concept and propel urban models to new heights” [3]. The digital modeling of urban space can occur through both the virtual reconstruction of the urban system in an electronic simulation and, in a sense, by incorporating digitalization within the physical urban space. In other words, it is possible to envision another dimension of digital twin modeling, built within the spatial context and through the creation of a network of hybrid digital spaces [4]. This reflection leads to proposing two distinct types of urban digital twins: – UDT exogenus – UDT endogenus Both typologies are based on the reference to the urban system and owe their effectiveness to the speed of digital information processing. The first type is the UDT which is currently being defined or already developed in many international urban contexts. This model is essentially built through a computer programming structure that connects data from urban sensors with expert system modules capable of formalizing the state of the system and suggesting potential governance actions, either autonomously or with human intervention [5]. As previously emphasized, a significant number of “classic” UDTs have been developed, either as prototypes or are currently under development. Among these, we can

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mention the UDTs of cities such as New York, Tokyo, Vienna, Helsinki, and so on (see Fig. 1).

Fig. 1. The urban digital twin referred to specific features of the urban system (source: FerreBigorra et al., 2022).

The second type of UDT is one that incorporates digital spaces within the physical context of the city. This second typology does not strictly represent a model of the city, but it can be useful for testing localized modifications of the urban space where such changes are anticipated. In this sense, the endogenous UDT is configured as a Digital Twin Instance (DTI) understood as a digital instance connected and federated to its physical twin. The DTI is identified as a digital content that can be activated live and on demand in the urban context to which it refers by means of augmented reality tools and envisages the direct involvement of the urban community in decisions concerning the transformation of the city. The endogenous UDT can be implemented in various ways in the spatial contexts of the city and can become an innovative tool for the enhancement of the territory capable of satisfying the needs of a new multi-sensorial urban tourism. The endogenous UDT, thanks to AR tools, has the potential to significantly increase the use of urban spaces for tourism [6]. The advantages of AR in the field of tourism enhancement are multiple: a greater emotional involvement of the visitor, a greater and differentiated fruition of space, a multi-level knowledge. On the basis of these considerations, it is possible to affirm that endogenous UDT can serve as a functional catalyst triggering new processes of interactive tourist fruition as illustrated in the case of the Vox Hortus project described below.

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3 The Vox Hortus Project The Vox Hortus project, with the support of the Municipality of Benevento and the supervision of the well-known artist Mimmo Paladino, aims to ‘give voice’ to the artworks through the realization of an audio augmented reality application for the urban space of the Hortus Conclusus in Benevento, which houses the works of the Samnite artist, one of the leading exponents of the Italian Transavantgarde. Paladino’s Hortus Conclusus, designed in 1992, is located within one of the gardens of the Convent of San Domenico, and evokes, in its urban conformation, the classic medieval garden of small dimensions, surrounded by high walls, a protected and silent place within the chaos of the city. In this place, which takes the form of an open-air museum, are the numerous works of the master Paladino, among which the Bronze Horse and the enormous Shield stand out (see Fig. 2).

Fig. 2. Photo of the urban space of the Hortus Conclusus taken from a drone (source: Aurus Research Group - www.aurusricerca.it).

Starting out from this urban context, the Vox Hortus project aims to make the sculptures “speak” by creating a sound path through which the visitor can walk through the space of the Hortus Conclusus, grasping, in an integrated perception, not only the spatial values of the works, but also the audio-emotional stimuli linked to the individual artwork. The audio does not provide an explanation of the work to which it is connected, but proposes a short sound (voice and music) that the visitor can listen to, with incremental volume, as he approaches the artwork itself, so as to define a path, not necessarily guided, between the artworks. In other words, each work is associated with an informative content in the form of sound input that can be enjoyed, in full autonomy, by each individual visitor thanks to their smartphone. Once the Vox Hortus app has been installed and the marker has been framed with the smartphone, each visitor is offered the possibility of listening to

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the audio content associated with each work, the volume of which becomes louder and louder as one approaches the work and lower and lower as one moves away from it. Moving within the urban space of the Hortus, it is possible to move from one sound content to another simply by approaching the individual works, deciding independently which itinerary to follow (see Fig. 3).

Fig. 3. Vox Hortus project mockup (source: Aurus Research Group - www.aurusricerca.it).

The realization of the Vox Hortus project involved four consecutive phases: 1. The relief of the urban space of the Hortus Conclusus. The exact position of each work within the garden was identified, as well as the reciprocal distance between the individual works; the point where the marker capable of activating the geolocation of the works within the app was also chosen. 2. The design of the AR app in Unity using the ARCore and AR Foundation platforms. A scene was created in the Unity environment to simulate the space of the Hortus. Each artwork in real space was associated with a 3D object in Unity’s virtual space to which an audio track was added with a linear roll off and a maximum distance beyond which the audio will not be heard. The app takes advantage of AR Foundation’s image tracking, so once a tracking image was chosen to work as a marker, individual 3D objects were associated with it. Finally, the app was built in APK format for Android devices that support AR Core (see Fig. 4). 3. The choice of sound information content to be associated with each artwork. Currently, in order to test the app, generic music tracks have been associated with the works. The objective is to produce texts or musical contents, which are representative of the artwork, but not, explanatory or descriptive of it. 5. The ‘augmented’ use of the urban space of the Hortus Conclusus. The app has been tested but is not yet usable by Benevento citizens and tourists. Once the audio content has been chosen, also under the supervision of the master Mimmo

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Fig. 4. Vox Hortus project mockup (source: Aurus Research Group - www.aurusricerca.it).

Paladino, the AR app Vox Hortus will be available to every citizen with an android device. Every visitor will be able to enjoy the ‘augmented’ space of the Hortus Conclusus; that is, to enjoy both the physical space with its artworks and the audio content. The Vox Hortus project aims to further increase the already high artistic and cultural value of the Hortus Conclusus, enhancing its touristic value through a further attractive dimension in “augmented” form, by triggering an innovative process of urban requalification.

4 Conclusions The UDT will soon become one of the new backgrounds in urban planning and, more broadly, in the governance of urban transformations. What is important to underline is that the UDT must be a system capable of addressing the needs of the city [7], particularly the functional and socio-anthropological requirements of the urban system. Furthermore, as briefly demonstrated in the overall exploration of the topic, it is possible to envision different types of UDTs. These include not only the ones created for benchmark modeling of the city without involving urban actors but also those that emphasize the interaction that citizens can have with a virtual urban space. Thanks to studies on Embodied Cognition [8], it has come to be understood how the individual’s knowledge is generated by the subject’s interaction with the surrounding environment and the elements that structure it. In other words, it is the interaction with an object that enables its perception by the individual regardless of the nature of the object itself. On the basis of these reflections, it is possible to state that if a digital instance is inserted into a physical space of the city with which an individual can interact through appropriate extended reality devices, the individual will perceive the entire context as real without distinguishing between physical objects and virtual objects. The space generated by the interaction between real and digital entities is called ‘hybrid digital space’ (HDS). It is the DTI’s own information content that appropriately associated with real entities is able to digitally hybridise the physical space. The insertion of a DTI within a physical

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space is capable of triggering a series of interactions between the real and the immaterial in which HDS is substantiated. In other words, an HDS is only possible if different digital contents are included in the physical space; it is through this grafting that the real space is configured as HDS [9]. Through this process, by the Vox Hortus app, the space of the Hortus Conclusus takes on the new configuration of a HDS, an environment in which the user, being able to establish an indistinct interaction with the real entities (the artworks) and the virtual ones (the sound content), triggers a new augmented cognitive process [10]. As a result of the above, it is evident how the adoption of technological innovation in the redefinition and re-functionalisation of urban contexts now allows the development of new dimensions of anthropised space that can be activated by extended reality tools.

References 1. Fistola, R., Zingariello, I.: Dalla percezione all’enazione urbana: gli spazi ibridi digitali. In: Fistola, R., Fregolent, L., Rossetti, S., La Greca, P. (eds.) Innovazioni tecnologiche e qualità urbana, Atti della XXIV Conferenza Nazionale SIU Dare valore ai valori in urbanistica, Brescia, 23–24 giugno 2022, vol. 01. Planum Publisher e Società Italiana degli Urbanisti, Roma, Milano 2023 (2022). http://www.planum.bedita.net/atti-della-xxiv-conferenza-nazion ale-siu-brescia 2. VanDerHorn, E., Mahadevan, S.: Digital twin: generalization, characterization and implementation. Decis. Support Syst. 145, 113524 (2021). https://doi.org/10.1016/j.dss.2021. 113524 3. Fistola, R.: La città come sistema. In: Beguinot, C., Cardarelli, U. (eds.) Per il XXI Secolo Una Enciclopedia. Città Cablata e Nuova Architettura, Università degli Studi di Napoli “Federico II” (Di.Pi.S.T.), Consiglio Nazionale delle Ricerche (I.Pi.Ge.T.), Napoli, Italy, vol. II, Chapter 2 (1992) 4. Fistola, R., Fabbri, F., Zingariello, I.: La rifunzionalizzazione “aumentata” della smart city: spazi e contenuti ibridi digitali. In: Atti della XXV Conferenza Nazionale SIU Transitions, Spatial Justice and Territorial Planninga, Cagliari, 15–16 giugno 2023 (2023) 5. Ferré-Bigorra, J., Casals, M., Gangolells, M.: The adoption of urban digital twins. Cities 131, 103905 (2022). https://doi.org/10.1016/j.cities.2022.103905 6. Ronaghi, M.H., Ronaghi, M.: A contextualized study of the usage of the augmented reality technology in the tourism industry. Decis. Anal. J. 5, 100136 (2022). https://doi.org/10.1016/ j.dajour.2022.100136 7. Lehtola, V.V., et al.: Digital twin of a city: review of technology serving city needs. Int. J. Appl. Earth Obs. Geoinf. 114 (2022). ISSN 1569-8432 8. Shapiro, L.: Embodied Cognition, 2nd edn. Routledge, London (2019) 9. Zingariello, I., Gaglione, F., Fistola, R.: Urban digital twin e realtà aumentata: una nuova dimensione di pianificazione bottom-up. In: Beyond the Future: Emergencies, Risks, Challenges, Transitions, and Opportunities. 13th International INU Study Day, Napoli, 16 December 2022 (2022) 10. Pagano, G.: Il marchio enattivo della Realtà Virtuale. Applicazione della teoria enattiva della cognizione nella spiegazione della conoscenza umana dei mondi virtuali, NOEMA (2021)

The Applicability of the Urban Digital Twin in the Detailed Choices of the Urban Plan Federica Cicalese(B) , Michele Grimaldi, and Isidoro Fasolino Department of Civil Engineer, University of Salerno, Fisciano, SA, Italy [email protected]

Abstract. In recent years, the idea of building urban digital twins (UDT) representing entire cities has increasingly attracted the attention of various disciplinary sectors. The UDT turns out to be the inevitable consequence of the digital transformation, configuring itself as the most innovative tool in the panorama of city studies, capable of providing decision-makers with simulation analyzes based on the monitoring of considerable quantities of data, allowing for a better allocation of public resources and helping to tackle problems such as noise, air pollution and traffic congestion. However, UDT use only a limited number of variables and rarely include the processes that determine the functioning of a city in terms of social and economic functions. Following a framework of the UDT concept and after having contextualized this tool within the scientific debate, the present contribution aims to evaluate whether the UDT is a suitable tool, as well than to guide urban policies, even to accept the forecasts of urban planning tools at a detailed scale. We wonder about its possible applications, in the decision-making phase, for the control of territorial surfaces of urban transformation and/or regeneration, both from a physical point of view, for example by supporting decision-makers on where to build buildings, plants and infrastructures, thus pursuing long-term actions, both from a functional point of view, making medium and short-term decisions based on a constantly updated vision of the city. Keywords: Detailed urban planning · Urban digital twin · Choices of urban scenarios

1 About the Concept of Digital Twin Various and divergent definitions emerge from the literature regarding the notion of the digital twin, first coined in the early 2000s by Michael Grieves [1]. It is a dynamic and evolving concept to meet the needs of the many sectors to which it is applied [2]. The digital twin was originally created in the aerospace field, so much so that one of its first definitions was formulated by NASA. Its purpose was to study the history of the vehicle by predicting failures and requirements. Later, used in the manufacturing sector, it aimed to simulate the behaviour of production systems by taking into account external factors such as human presence and technical constraints [3]. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 211–220, 2024. https://doi.org/10.1007/978-3-031-54118-6_20

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To date, its use has expanded and is being used to characterize a variety of digital simulation models, capturing real-time changes in different physical systems [4]. This growth has been largely driven by advances in data processing and management such as the Internet of Things (IoT), big data, real-time sensors, multiphysics simulation, and Industry 4.0 [2]. So, the digital twin can be defined as a mirror image of a physical system, that is, a dynamic, constantly updated representation that evolves and interacts with the different configurations that the system assumes [5]. Applied in the field of urban planning, the Urban Digital Twin (UDT), makes it possible to obtain, from heterogeneous urban data, a spatiotemporal picture of the city, useful to support decision-making processes that will shape the future of cities and the quality of life of their citizens. From this comes the possibility of testing the impacts of changes in order to be able to carry out maintenance operations, with a view to long-term planning policy [6]. Therefore, UDT are digital representations, or ‘virtual replicas’ of cities that can be used as simulation and management environments to develop scenarios in response to policy problems [7]. The first urban models aimed at assisting planning and policy making were developed in the 1950s. Later, in the 2000s, 3D city models began to be used, which were refined with the advent of Building Information Modeling (BIM) [7]. Placed in the context of the Digital Twin, BIM aims to twin a building, using a data connection between physical and virtual, so as to measure and realize the change in the current state of the physical building. Currently, representative models of digital cities are based on geospatial data derived from a Geographic Information System (GIS), which can be considered an indispensable tool for land development and land governance in general [8]. Technological advances and the widespread use of Global Positioning System (GPS) technology at the individual and infrastructural levels, with the resulting access to highresolution spatiotemporal data, allow for more complex urban models and simulations, in which dynamic interactions and interdependencies can be captured in space and time [9]. The knowledge of a territory, its representation, can therefore be carried out in various ways. Demonstrating the importance of the interdependencies between city infrastructure and its collective impact on urban sustainability, it should be noted that several goals of the 2030 Agenda (SDGs 3, 6, 7, 9 and 11) are influenced precisely by urban infrastructure [9]. Aiming to contribute to the conceptualization of the digital twin in urban management, this paper, through a literature review, selects some existing initiatives by schematizing them in terms of applications, purposes and users, identifying benefits, open issues and possible perspectives.

2 Review of Urban Digital Twin Practices The city is to be read as a complex set of relationships and interactions between inhabitants and its infrastructure.

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Digital twins open up important opportunities to support better decision-making and city management towards sustainability. In order to understand the dynamics of the city, it is necessary to acquire a vast knowledge of the events that occur in it. Having a large amount of heterogeneous data at one’s disposal that can be analyzed and interpreted makes it possible to identify interventions to be implemented that not only improve the sustainable functioning of the infrastructure but also take into account the needs of its citizens [9]. The interactivity resulting from this data exchange allows for the most accurate representation of the real city and its systems, and has the potential to bring important benefits in the management and operation of the city. By using new technologies, efforts are made to make the city more efficient, safe, inclusive and democratic, including by increasing cooperation between administration and inhabitants [10]. Currently, digital twins are used to model different systems, such as urban transport or infrastructure management, depending on the needs and requirements of the city. In general, a UDT is used to modify physical space, making choices over the long term; to make everyday decisions, which can be implemented by either a human or a machine; to assess the effects that certain actions may have on the territory, allowing, through these predictions, to support planners’ decisions [6]. Depending on the objective pursued, there will be different users: policy makers, urban planners, citizens, etc.. Focusing on urban planning, this paper has excluded the other possible uses of digital twins by concentrating on the various facets and levels of scale to which UDT has been applied. Eleven episodes of UDT creation have been selected, directly referred to the urban planning. Among them, we mention the DUET initiative and the case of Zurich, which, when considering urban planning, represent significant European experiences. The project of the Athens metropolitan area, together with the case of the city of Pilsen and the Belgian Flanders region, is part of the Digital Urban European Twins (DUET) pilot projects. Through a 2D and 3D interface, policy makers, city administrators and stakeholders were able to simulate, model and explore the expected impact of different policy options in the real world before making final decisions. The functionalities and objectives of the digital twin of the Greek city are manifold. Measures to combat pollution within the city are pursued in order to adopt new strategies and policies for healthy mobility, promoting efficient routes and green spaces. By combining environmental data, the city’s historical data on mobility, parking and environmental measures, as well as real-time data, strategic plans to reduce traffic problems are to be defined, enhancing the existing controlled parking system and promoting the use of public transport [11]. For example, from the point of view of a policy maker and urban planner it is possible to evaluate the decision making in adding benches in a central square of Athens and have an overview of the trees shadow coverage at different seasons (Fig. 1). In this way we obtain an optimized monitoring of the shade coverage and exploitation of the shaded places.

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Fig. 1. Athens Green Squares and planning (source: DUET website).

Among the various objectives is the involvement of citizens in the decision-making process, so that they are actively participate in the city’s initiatives, express their interest in a better and greener way of life, and their voice is a resource in the definition of the policies to be undertaken. By exploiting the outputs of the decision-making process and the predictive capabilities of the digital twin, the aim is to assess the usefulness and effectiveness of existing policies in order to update them. The digital twin can also provide the city with a tool to visualize current sources of pollution, points of interest and green routes, and to check the environmental impact of different strategic plans. Moving to Pilsen, a medium-sized city in Czechia, the aim is to help predict and understand the impacts of regional mobility so that policy can be implemented in a way that minimizes stress on both the environment and human health. The UDT of the city of Pilsen, like the one developed for the Flanders region, is used for urban planning, to model and assess the expected impact of new buildings on the local area, and to better understand the evolution of traffic noise and air quality in the city. In the case of Zurich, on the other hand, the construction of the UDT is primarily aimed at increasing the city’s level of sustainability, becoming a tool to address a number of urban challenges due to the expected increase in the number of inhabitants, the resulting employment, urban densification and competition in land uses [12]. The objective of the UDT for the city of Zurich is to realize a digital representation of the city to simulate possible solutions to issues to be overcome in the context of sustainable urban planning, making it optimally usable for a variety of applications. To this end, the components of the digital twin are to be updated at different intervals and, if necessary, enriched with real-time data. The developments, managed by the City of Zurich GIS, enabled a thorough analysis of various issues: environment; noise; air pollution; flood and inundation simulations; energy, such as the analysis of solar potential and the calculation of mobile network coverage; urban planning, for the visualization of construction projects, the calculation of

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Fig. 2. Virtual Zurich (source: City of Zurich).

air flows, shadow and visibility analysis [12]. The results support the planning decisionmaking process. In addition, within the navigation area (Fig. 2) users can interact by making changes and submitting them to the municipal administration. Below, two summary tables are given: the first (Table 1) schematizes the different cases of UDTs examined, locating them and identifying their objective; the second (Table 2), highlights the main characteristics of the tool analyzed, in terms of application size, user, usage stage and theme modeled. Table 1. Identification of case studies and the objective pursued. N.

Reference

Case Study

Keywords

Purpose

1

Charitonidou (2022)

Hervanta (FIN)

Traffic; Automated vehicles; Sensors

Test methods related to autonomous driving studies

2

Charitonidou (2022)

Kalasatama district (FIN)

3D city; Interaction; Visualization

Participation and interaction with residents

3

DUET

Athens (GR)

Pollution reduction; City planning; Healthy mobility

Data analysis in order to design policies focusing on small areas of the city

4

DUET

Pilsen (CZ)

Environment; Urban Achieve a higher planning; Engagement quality of public and cocreation space by using tools to better simulate, plan in scenarios and regulate the future development of the city (continued)

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N.

Reference

Case Study

Keywords

Purpose

5

DUET

Flanders region (BEL)

Public safety; Spatial planning; Mobility

Create a dynamic and usable database for evidence-based decision making

6

Virtual Singapore Singapore (SGP)

3D modeling; Decision-making; Collaboration

Use of the information and system capabilities for policy and business analysis, decision making, test-bedding of ideas, community collaboration and other activities

7

Schrotter and Hürzeler (2020)

Zurich (CH)

Urban climate; Participation; Densification

New and more efficient solutions for the users of urban infrastructures as well as for their operators

8

White et al. (2021)

Dublin Docklands (IE)

SmartCities; IoT; Urban planning; Urban policy

Involve citizens and obtain valuable feedback on policy and planning decisions in the city

9

Wan et al. (2019)

Cambridge sub-region (UK)

Transport; Housing; Environment and energy

Aims to quantify some of the interdependencies among transport, air quality, housing and energy infrastructure

10

Dembski et al. (2020)

Herrenberg (DE)

Collaborative planning; 3D modeling; Simulation

Gain a better understanding of potential solutions for urban challenges involving public decision-making to reach consensus (continued)

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Table 1. (continued) N.

Reference

Case Study

Keywords

Purpose

11

Adreani et al (2022)

Florence (IT)

3D city model; Smart visualization; Open-source platform

To offer a method for creating effective integrated visualizations of 3D city entities combined with a wide variety of data

* Note: DUET = Digital Urban European Twins

Table 2. Characterization of the UDT.

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3 Summary Assessments and Future Prospects This contribution presented a literature review in an attempt to characterize the digital twin and map its current state of development in order to highlight distinctive features and identify future challenges. From the study conducted, several applications of UDT emerged, essentially distinguishable by scale, purpose, techniques, simulation tools contemplated, users and time of use (see Table 1 and Table 2). As a result of the research, it is possible to affirm that UDT is an urban planning tool with great potential, capable of providing decision makers with new ways, such as simulative and predictive analyses to make changes to specific components of the city and direct design choices on the basis of monitoring and historical data sets. In addition, it was emphasized that UDT provides a better understanding of potential solutions to urban challenges, predicting impacts and supporting decision-making. It has the merit of: being able to create optimal designs, obtaining feedback through efficient processes aimed at the broader political ambitions of sustainability, accessibility, liveability; predicting how resources will change over time; and making real-time updates so that decision-making can be better supported. Among the most frequently used applications is traffic simulation, which is present 8 out of 10 times, enabling the calculation of traffic density in cities based on added events or changes in the road network. What generally emerges from all experiences is the possibility for the private sector and inhabitants to open up in a dialogue with the administration to share visions for improving local conditions for better liveability. UDT allows for greater community acceptance through the use of sensors and applications that directly involve them in the planning process, strengthening the contact between the population and the administration. The obstacle to active participation is therefore lower than in traditional participation procedures, where participation in an event organized by the municipal administration is generally required at a given time. Moreover, the health emergency has forced many cities to recognize that the adoption of new technologies and data to provide alternative approaches to city service delivery is no longer a luxury but a necessity. However, the scientific production examined shows that current approaches, only consider a limited set of fields of application [7]. Such systems, in fact, rarely include those processes that determine the functioning of the city in terms of social and economic functions. The 3D virtual models, even if they have incorporated within them real-time processes such as traffic and energy flow, are only representations that function over short periods of time [4]. In order to truly reach a tipping point and take the concept of smart cities and urban models to the next level, it is necessary to integrate physical information with sociocultural aspects, enabling digital twins to be successful in the long run so as to better support the creation of meaningful urban experiences [19, 20]. Therefore, having the potential to enable sustainable urban development at all scales, research needs to focus on methodological advances that can lead to integrating social and economic functions to include the human dimension [21].

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To date, therefore, the tool is not ready to go into the details of the plan choices. In addition, a clear dividing line should be defined between digital twins on the one hand and 3D models and BIM on the other, considering that a general confusion emerged after the survey. In BIM, the model includes the geometric and temporal information of the physical entity, however it requires manual data input for updates due to the lack of connection between the model and the physical entity, whereas the use of a digital twin can provide mutual interaction between the two counterparts in real time [23]. For example, the use of sensors and IoT technologies can provide information transfer, which updates the virtual model based on real-time updates from the physical counterpart. Furthermore, due to the potential of running simulations on the virtual model, future predictions and performance optimization of the physical entity’s performance can be achieved [24]. The investigation carried out, although not exhaustive, invites a general reflection on the issues and objectives entrusted to this tool. In conclusion, the digital twin’s ability to conceptualize, compare and collaborate frees us from the ‘physical realm’ and allows us to move into a ‘virtual realm’ where physical location is irrelevant and people can have a common visualization, grasp the difference between what is and what should be and collaborate together [23]. This significant result can only be achieved if the physical product can be matched with the virtual product.

References 1. Grieves, M.: Digital Twin: manufacturing excellence through virtual factory replication. White Pap. 1, 1–7 (2014) 2. Jones, D., Snider, C., Nassehi, A., Yon, J., Hicks, B.: Characterising the digital twin: a systematic literature review. CIRP J. Manuf. Sci. Technol. 29, 36–52 (2020) 3. Macchi, M., Roda, I., Negri, E., Fumagalli, L.: Exploring the role of digital twin for asset lifecycle management. IFAC-PapersOnLine 51(11), 790–795 (2018) 4. Batty, M.: Digital twins. Environ. Plan. B Urban Anal. City Sci. 45(5), 817–820 (2018) 5. VanDerHorn, E., Mahadevan, S.: Digital twin: generalization, characterization and implementation. Decis. Support Syst. 145, 113524 (2021) 6. Coenen, T., et al.: Open urban digital twins -insights in the current state of play (2021) 7. Ferré-Bigorra, J., Casals, M., Gangolells, M.: The adoption of urban digital twins. Cities 131, 103905 (2022) 8. Grimaldi, M., Giordano, C., Graziuso, G., Barba, S., Fasolino, I.: A GIS-BIM approach for the evaluation of urban transformations. a methodological proposal. WSEAS Trans. Environ. Dev. 18, 247–254 (2022) 9. Mohammadi, N., Taylor, J.E.: Knowledge discovery in smart city digital twins. In: Hawaii International Conference on System Sciences, pp.1656–1664 (2020) 10. Arroub, A., Zahi, B., Sabir, E., Sadik, M.: A literature review on smart cities: paradigms, opportunities and open problems. In: 2016 International Conference on Wireless Networks and Mobile Communications (WINCOM), Fez, Morocco, pp. 180–186 (2016) 11. DUET City of Athens. https://www.digitalurbantwins.com/athens-twin. Accessed 31 May 2023 12. Schrotter, G., Hürzeler, C.: The digital twin of the city of Zurich for urban planning. PFG 88, 99–112 (2020)

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13. Charitonidou, M.: Urban scale digital twins in data-driven society: challenging digital universalism in urban planning decision-making. Int. J. Archit. Comput. 20(2), 238–253 (2022) 14. DUET City of Pilsen. https://www.digitalurbantwins.com/pilsen-twin. Accessed 31 May 2023 15. DUET Flanders region. https://www.digitalurbantwins.com/flanderstwin. Accessed 31 May 2023 16. Virtual Singapore. https://www.nrf.gov.sg/programmes/virtual-singapore. Accessed 31 May 2023 17. White, G., Zink, A., Codecà, L., Clarke, S.: A digital twin smart city for citizen feedback. Cities 110, 1–12 (2021) 18. Wan, L., Nochta, T., Schooling, J.M.: Developing a city-level digital twin –propositions and a case study. In: International Conference on Smart Infrastructure and Construction (ICSIC), pp. 187–194 (2019) 19. Esposito, D., Abbattista, I., Camarda, D.: A conceptual framework for agent-based modeling of human behavior in spatial design. In: Jezic, G., Chen-Burger, J., Kusek, M., Sperka, R., Howlett, R., Jain, L. (eds.) Agents and Multi-Agent Systems: Technologies and Applications 2020. SIST, vol. 186, pp. 187–198. Springer, Singapore (2020). https://doi.org/10.1007/978981-15-5764-4_17 20. Esposito, D., Ruggiero, M.: Advancing urban science with multi-agent systems: prospects for innovation and sustainability in spatial planning and urban governance. In: Gervasi, O., et al. (eds.) ICCSA 2023. LNCS, vol. 14109, pp. 368–384. Springer, Cham (2023). https://doi.org/ 10.1007/978-3-031-37120-2_24 21. Dembski, F., Wössner, U., Letzgus, M., Ruddat, M., Yamu, C.: Urban digital twins for smart cities and citizens: the case study of Herrenberg, Germany. Sustainability 12(6), 2307 (2020) 22. Adreani, L., et al.: Digital twin framework for smart city solutions. In 28th International DMS Conference on Visualization and Visual Languages, KSIR Virtual Conference Center, Pittsburgh, USA, 29–30 June (2022) 23. Mezzour, G., Benhadou, S., Medromi, H.: Digital twins development architectures and deployment technologies: Moroccan use case. Int. J. Adv. Comput. Sci. Appl. (IJACSA) 11(2), 468–478 (2020) 24. Shahat, E., Hyun, C.T., Yeom, C.: City digital twin potentials: a review and research agenda. Sustainability 13(6), 3386 (2021)

Urban and Spatial Planning Through the Support Tool of the Regional Digital Twin Sara Sacco(B) , Federico Eugeni, and Donato Di Ludovico DICEAA - Department of Civil, Construction-Architectural and Environmental Engineering, University of L’Aquila, L’Aquila, Italy [email protected]

Abstract. The gradual transposition of physical and intangible reality into the digital environment interfaces with a multiplicity of areas, although still being stabilized. Creating connections between data streams and information from physical and digital space provides the ability to test and analyze the behavior of systems, depending on different needs and objectives, with the ability to be able to create simulations and generate real-time information useful for a more current concept of planning. In this sense, a study at the University of L’Aquila is defining a prototype Urban and Regional Digital Twin (Urban and Regional Twin) as an innovative tool for representing and analyzing reality at different scales of intervention. The main objective is thus to support planning and programmatic choices by providing a cross-cutting and detailed representation of reality, linking to the paradigms of Knowledge Systems and Digital Information Platforms. Another goal will be to reconsider current planning paradigms regarding the potential of DT. The article will describe the methodology that the research, to date in its early stages, is following to structure such a system by identifying its sources, processes, and possible fields of application of which some elaborations already carried out are presented. Several case studies (one Italian and one international) were outlined to test their capabilities and applicability in different territorial contexts. Keywords: Digital Twin · Risks · Planning Models

1 Introduction The concept of the digital twin has been widely addressed in the scientific literature for a long time and even more so in recent years thanks to the digital evolution that allows a holistic approach in different fields of application. The prototype was born from simulations in the space domain thanks to Micheal Vickers in 1970, later in 2002 it was proposed by Michael Grieves for the life-cycle management of an industrial product [1] until today, where it is being tried to be used in a wide variety of contexts such as climate adaptation, smart cities, infrastructure adaptation, health care, security and more. Conceptually, DT makes use of a real physical element, its virtual interactive reproduction, and the two-way relationship between the two parts that is achieved through © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 221–229, 2024. https://doi.org/10.1007/978-3-031-54118-6_21

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the exchange and transmission of data, seeking to achieve an automated system. This is made possible by the advancing technological development at hand; what makes it possible to define the digital model, and especially usable in increasingly different contexts, are its technological components such as big data and the cloud, AI artificial intelligence, Internet of Thing IoT, and High-Performance Computing HPC [2]. An example of the approach is the basis of the CNR’s strategic project on smart cities, “Urban Intelligence,” represented by new digital technologies in terms of analysis (data science) and prediction (artificial intelligence and machine learning), simulation (high-performance computing), optimization and decision support, IoT (connected sensors and objects that collect data) and 5G (the latest generation of mobile connectivity to transmit data [3]. Thus composed, the digital twin is characterized by the ability to be multiphysical, since it simulates multiple physical phenomena; multiscale, depending on the detail required; modellable, thanks to the possibility of modifying its constituent components; multidisciplinary, with the possibility of including information from different fields; probabilistic, through statistical methods, algorithms, machine learning for simulations, predictive scenarios of the real world can be generated; and dynamic, because of the continuous interaction with the physical model it turns out to be always updated and consequently generates simulations and predictions of the real system also updated. By its very nature, the digital twin can optimize a system’s performance through adaptive models, shared data, and advanced visualization, enhancing the speed at which a process runs and reducing the risk associated with complex projects [4]. In the urban planning context, the digital twin can provide significant support in tracking the behavior of the real city and monitoring its evolution; planning and developing projects, observing in advance the effects of their implementation on its “twin”; anticipating possible problems and executing corrective actions, thus preventing the occurrence of critical issues [5] or predicting extreme weather events, climate change and hazards [6]. The opportunity to have a synchronous dataset can contribute to more updateable urban and regional planning. The study proposed in this paper concerns an initial result of research at the University of L’Aquila on the potential of the Digital Twin (DT) for disaster risk knowledge and planning, to define a prototype digital twin, at the urban and territorial scale intended as a tool to support possible new models of truly flexible and dynamic planning and programming, with particular reference to the issue of hazards and pre-disaster planning [7] at the regional level. The research methodology is essentially composed of three parts. The first concerns the study of existing Digital Twin (DT) models, delving into those that are best able to support urban and spatial planning processes; it also covers the definition of the synchronous (real-time) and asynchronous knowledge sets needed to populate the DT, with a particular focus on risk issues. The second phase concerns the identification of the most appropriate technologies for the establishment of an urban digital twin and a regional digital twin, the collection of the “static” basic data, and the identification of the necessary “dynamic” data (phase in collaboration with the Civil Protection Regional Agency of Abruzzo Region - Agenzia Regionale di Protezione Civile della Regione Abruzzo), and finally the definition of the regional planning model oriented to pre-disaster planning that makes the best use of the potential of DT. The third phase will concern testing

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Regional DT and pre-disaster planning prototypes, on national and international spatial level case studies. This paper will describe the main results of the first phase of the methodology, the first studies on DT, and the identification of related baseline data.

2 Literature Review The concept of the digital twin is gaining more and more space in the scientific literature. In the specific urban context, today’s most in-depth cases are mainly associated with the smart city concept, probably because of the available technological tools. CIM (City Information Modeling) is certainly the most studied model in this regard. As Salles et al. [8] refer, this type of technology integrates BIM data (Building Information Modeling) with GIS (geographic information system) and IoT sensors as a synthesis of a three-dimensional urban spatial model and urban information. It also investigates the possibilities of integrating GIS and BIM to compose an open, accessible, and interactive platform for all users, whether urban planners or citizens, useful for assessing the multiple scales of the city; emphasized that it should be a design and planning tool, where urban planners and designers could share properties, characteristics, and relationships of urban elements. Although different approaches exist, some common elements characterize a CIM platform: interactivity, collaboration, interoperability, and shared information among stakeholders [8]. In the case of projects and planning at the regional level, the complexity is evident from the difficulty of data processing, in fact in these cases the BIM software would have to discard a large amount of data to achieve efficient management, due to the limited potential of technological tools as mentioned by Xia H et al. [9]. As Park J et al. [10] reminds us, the concept is that initial data are digitized through processing and are displayed in the virtual model. In this virtual space, new spatial data are generated through analysis and simulation. The new data are managed to support decision-making, and the decisions are ultimately reflected in the physical space. It can be seen how complex it still is to extrapolate information according to the scale dimension, and how obvious the difficulty of bridging the different dimensions of detail of information between the different levels concerning the hierarchy that makes up the DT. In addition, the integration between the various levels of information and detail themselves is also complex. Considering the urban context, according to Tao F et al. (2022), an individual urban building is considered an individual unit; the building complex, such as a neighborhood, is assimilated at the system level; finally, the whole city is at the SoS (System of Systems) level [11]. A useful example of being able to analyze a spatial scale digital model application process is shown by Park J et al. [10] about the city of Jeonju. The case of Jeonju City is a pilot project in South Korea in terms of digital twins and territory. Of interest are the specific information used for model development, such as collecting and updating data; establishing the city of Jeonju in virtual space; and operating and managing models for simulation and analysis.

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Specifically, to define the city of physics in virtual space, the territorial data collected, by national and local governments, are about 20 types and can be grouped into four subcategories according to the level of detail (LoD). The subdivided data are, for example, cartographies, digital elevation models, and building information modeling. Again, critical issues emerge that limit the development of a large-scale model, for example as Barricelli B et al. expose [12], the huge costs for elements such as software, hardware, and cloud/physical interconnection in terms of challenges. Or data for many facilities are not managed in computer systems, which leads to limitations in terms of data renewal. In addition, the data update cycle is so slow that data are underutilized, and it is difficult to maintain consistent standards. The security of personal information must also be considered. Through an ‘ecosystem’ of technologies (including digital twins, big data, and ICT), cities become archipelagos of self-sufficient and connected neighborhoods. Technology can play a decisive role in the design and implementation of smart habitats, for the well-being, ecosystem quality, and adaptivity of the built environment [13]. Net of the information and critical issues that have emerged in analyses of the scientific literature, the challenge is not to be limited to the urban context but to try to achieve a digital spatial model (RDT).

3 Methodology As mentioned above, the research topic is still at a preliminary stage so a summary of the first study steps is proposed regarding the knowledge of the DT tool and how it can contribute to land use planning, specifically risk planning in the pre-disaster phase [7]. The University of L’Aquila’s research, “Potential of a digital twin for disaster risk knowledge and planning”, frames this issue in the territorial context through collaboration with the Civil Protection Regional Agency of Abruzzo Region (CPRA). 3.1 DT Definition to Support Planning As shown in Fig. 1, the search path follows two parallel approaches. The first in which they are deepened by three typological successions of DTs have been investigated in depth concerning their size scale, their constituent features, and the information they return. The same multi-scalar approach is applied to the in-depth study of the topic of predisaster planning, which aims to reduce risks as much as possible and prepare the territorial structure for a response, and post-disaster planning, for emergency management and the subsequent physical and social recovery of the territorial context. This information allows identifying the DT useful to pre-disaster planning. Once the specific digital model is recognized, its definition is defined as construction tools; among these are the informatics tools, the data obtained from Civil Protection of phenomena and risks that affect the territory, and finally urban tools such as multi-scale analysis and simulations. The goal is to understand how to generate a DT through a risk dataset, and simultaneously, a tool that can provide output information useful for planning.

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The second approach is concerned with the study of pre-disaster planning, its levels, and its components. This approach will be explored in more detail in Sect. 3.2. At the present stage of the research, we are in the first phase (top, Fig. 1), which concerns the analysis of Digital Twin (DT) models described in the literature. The classification of DT derived from the analysis of the scientific literature on urban and regional planning issues, as the first result of the research, can essentially be defined on three levels, differing in scale and detail of information (type and level of detail of information change about scale, also due to the dimensional aspects of the information itself), as shown in Table 1 below. The research project, at present, is deepening and developing the Regional Digital Twin (RDT) model, which will be populated with static and real-time knowledge, aimed at simulating risk scenarios and defining flexible and dynamic pre-disaster planning strategies. This aspect will involve establishing new modes of urban and regional planning that use the features of DT and go beyond the current long-term plan model. As stated by Wideman, “Risk management in the project should be viewed as advanced preparation for possible future negative events, rather than reacting as they occur. With this advanced planning, it should be possible to select an alternative plan of action that will successfully achieve the project objectives” [15]. 3.2 The Baseline Data for the Regional Digital Twin In parallel with the study on Digital Twin forms and models, research is also deepening the topic of data for RDT, which, specifically in pre-disaster planning and therefore Risk Assessment, particularly concerns the Multi-Hazards (M-H), Multi-Vulnerability (M-V) and Multi-Exposure (M-E) components [16], but also other interacting layers useful to carry out simulations and define risk scenarios as a dynamic and continuous activity. Such deepening also concerns the nature of information, which can be divided into “static,” such as data extracted from the regions’ open-data platforms, and “real-time,” such as data produced in the context of the Internet of Things (IoT) or satellite data (remote sensing). The first step in defining the above information comes from a study by the University of L’Aquila and the Abruzzo Region to establish the Knowledge System of the CPRA Plan dedicated to multi-hazard analysis, prevention, and risk mitigation/reduction. It is a study geared toward the preparation of the Regional Risk Management Plan (RMRP) that responds to the prevention and mitigation demand typical of “structural” civil protection activities [16] and contains a substantial part of the definition of the knowledge system. The study was also used to compose the knowledge base for the regional CPRA report “Cognitive Elements of the Territory of the Abruzzo Region and Civil Protection Organization”. This specific report describes a dynamic and updatable structure of the Knowledge System and was prepared on the assumption that knowledge of the territory is the essential requirement for proper Civil Protection planning [17, 18]. The Knowledge System consists of four elements. (1) The Basic Spatial Knowledge Framework (orographic, hydrographic, meteoclimatic, administrative, sociodemographic, economic-productive, regional cultural and environmental heritage framework); (2) the Cognitive Framework of the main civil protection risks; (3) the technicaloperational description of the organization of the regional Civil Protection system, the

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Fig. 1. Conceptual research map for DT definition to support Planning.

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Table 1. Classification of the DT. Classification of the Digital Twin Neighborhood Digital Twin NDT “Neighborhood Digital Twin,” concerns urban neighborhoods or districts whose level of detail is very similar to that of BIM - Building Information Modeling, so much so that it can be likened to CIM - City Information Modeling [14]. A review of the scientific literature shows that there are no studied and tested models at this scale Urban Digital Twin

The UDT “Urban Digital Twin,” concerns the extended urban level, sets of neighborhoods, i.e., the city, is a concept generally associated with that of a Smart City. The UDT generally focuses on the replication of mobility and sub-services. A review of the scientific literature shows that this model is the one most referred to

Regional Digital Twin

The RDT “Regional Digital Twin,” which relates to the digital twin at the regional scale, refers to the replication of spatial, environmental, and landscape systems aimed at, for example, risk management and thus the simulation of scenarios useful for land management and its planning in peacetime. A review of the scientific literature shows that there are no studied and tested models at this scale

composition and intervention model of the Regional Mobile Column; (4) the Civil Protection operational models. Among the information collected for the aforementioned Knowledge Frameworks, the data collected during the reconstruction phase of the 2009 Abruzzo post-earthquake reconstruction were crucial, as they enabled the production of entirely new knowledge bases and represent innovative elements to support the analysis of risk components. These are often autonomous GIS or Databases, which in the Knowledge System have been integrated, addressing issues of thematic, temporal, and scale consistency. The goal of such information, which strongly characterizes the types of RDTs to which our research refers, is to constitute an “autonomous,” continuously implementable information base [19], capable of generating and evaluating models and frameworks of territories and cities, understanding and representing their processes, supporting their debate and addressing their conflicts. The Knowledge System and these frameworks, integrated into an RDT, can show current events, those that took place in the past that will take place in the future, through two-dimensional techniques, scenarios, diagrams, ideograms, etc. [20]. The definition of the Regional Digital Twin understood as a virtual and computerized model of the territory, will be integrated with planning and knowledge tools to reach a dynamic and flexible planning model. Once the toolset is obtained, it will be applied to a case study of the Abruzzo Region, at a regional scale, and the results will be compared with a further international case, finally arriving at a possible knowledge structure useful both to institutions and to the population itself.

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4 Conclusions The gradual integration of tangible and intangible reality into the digital domain interfaces with different domains even though it is still being stabilized. The ability to test and analyze the behavior of systems according to different needs and goals is made possible by the connections made between data and information flows of physical and digital space. This allows the creation of simulations and the production of valuable real-time information for a more up-to-date conception of planning. In this regard, this paper describes the research of the University of L’Aquila, in its initial stage, concerning the role of Digital Twin at its different scales, from urban to territorial, as a tool to support a new multi-scalar planning model that is truly flexible and dynamic as the DT itself, concerning pre-disaster planning. The article briefly describes the three phases of the proposed methodology and in particular some outcomes of the first phase that relate to the definition of the DT model, differentiated into three scales (neighborhood, urban, regional) and the underlying knowledge system that can also be derived from other research by the same working group. The next step in our research will be to define the information needed for the construction of the RDT and to identify the appropriate informatics tools to develop it. In a very concise way, the ultimate goal will be to understand the potential of digital information, through the Digital Twin, to structure a new model of urban and territorial planning that uses the characteristics of flexibility and dynamism, overcoming the longterm approach of current planning systems.

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8. Salles, A., et al.: Analyzing the feasibility of integrating urban sustainability assessment indicators with city information modelling (CIM). Appl. Syst. Innov. 6(2), 45 (2023). https:// doi.org/10.3390/asi6020045 9. Xia, H., et al.: Study on city digital twin technologies for sustainable smart city design: a review and bibliometric analysis of geographic information system and building information modeling integration. Sustain. Cities Soc. 84, 104009 (2022). https://doi.org/10.1016/j.scs. 2022.104009 10. Park, J., et al.: Digital twins and land management in South Korea. Land Policy 124, 106442 (2023). https://doi.org/10.1016/j.landusepol.2022.106442 11. Tao, F., et al.: Digital twin modeling. J. Manuf. Syst. 64, 372–389 (2022). https://doi.org/10. 1016/j.jmsy.2022.06.015 12. Barricelli, B., et al.: A survey on digital twin: definitions, characteristics, applications, and design implications. IEEE Access 7, 167653–167671 (2019). https://doi.org/10.1109/ACC ESS.2019.2953499 13. Thiébat, F.: Habitat intelligenti e auto-sufficienti: il ruolo della tecnologia per il futuro dell’architettura. Thecne 25 (2023). https://doi.org/10.36253/techne-14765 14. Xu, X., et al.: From building information modeling to city information modeling. J. Inf. Technol. Constr. (ITCon) 19, 292–307 (2014). https://www.itcon.org/2014/17 15. Wideman, R.M.: Project and Program Risk Management: A Guide to Managing Project Risks and Opportunities. Project Management Institute; Preliminary Ed. for Trial Use edition (1992) 16. Di Ludovico, D., Di Lodovico, L.: The regional management risk plan. Knowledge, scenarios and prevention projects in a regional context. Int. J. Disaster Risk Reduct. 45, 1–13 (2020). https://doi.org/10.1016/j.ijdrr.2019.101465 17. Di Ludovico, D., Di Lodovico, L., Basi, M.: Prevenzione e mitigazione dei rischi territoriali. Conoscenze e orientamenti per la protezione civile della Regione Abruzzo. In: Francini, M., Palermo, A., Viapiana, M.F. (eds.) Il Piano di Emergenza nell’uso e nella gestione del territorio. FrancoAngeli, Milano (2020). (a cura di) 18. Di Lodovico, L., Di Ludovico, D.: Territori fragili. Integrare le conoscenze per una reale mitigazione dei rischi. In: Urbanistica e/è azione pubblica. La responsabilità della proposta, vol. 1, pp. 161–167. Planum Publisher, Roma, Milano (2017) 19. Di Ludovico, D.: Il Progetto Urbanistico. Prove di innovazione per il futuro della città, Canterano. Aracne Editrice, Roma (2017). ISBN: 978-88-255-0181-0 20. Hanzl, M.: Information technology as a tool for public participation in urban planning: a review of experiments and potentials. Des. Stud. 28–3, 289–307 (2007). https://doi.org/10. 1016/j.destud.2007.02.003

Towards Sustainable Urban Development: Matera’s Urban Digital Twin and Challenges in Data Integration Simone Corrado(B)

and Francesco Scorza

Laboratory of Urban and Regional System Engineering (LISUT), School of Engineering, University of Basilicata, Potenza, Italy [email protected]

Abstract. This work is part of the project CTEMT “House of Emerging Technologies of Matera” aims to develop an ICT platform, i.e., “Alpha model”, connecting sensor networks with advanced simulation and monitoring services for the creation of the urban digital twin of the city of Matera. The ambition is to build a set of digital models for city systems to analyze the complex dynamics of the urban environment. The first phase required a detailed context analysis to explain the role and function of the “model Alpha” in the city of Matera, identifying the main thematic structures territorial of the city and their connections and effects on the area. For this purpose, the urban context is analyzed by splitting it into three different spatial information layers: Point Of Interest, road graph and public space. The implementation of an operational urban digital twin was found to be a complex process involving several technical and logistical challenges even before the mapping phase began. Beyond data collection and integration to provide accurate representations of the urban environment to the model, another challenge was the engagement of analysts from multiple disciplines throughout the deployment process. Indeed, different semantic interpretations of information and purposes of the urban digital twin have emerged. This work aims to give an overview of the CTEMT experience and analyze the critical issues related to the development of urban digital twin. Keywords: Urban Digital Twin · Urban management · Smart city · Urban planning

1 Introduction The journey of Matera as the European Capital of Culture in 2019 highlighted how a cultural program can act as a catalyst for implicit processes of urban regeneration, transforming public spaces into areas for experimentation and the development of creative and innovative processes. Through the implementation of the European Capital program, the city positioned itself at the center of a critical reflection on the potential of technology for maintenance, governance and future development of the urban context. The focus extended beyond the well-known tourist sites and cultural heritage, such as © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 230–236, 2024. https://doi.org/10.1007/978-3-031-54118-6_22

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the Sassi, and encompass the modern neighborhoods and suburbs of the city. This focus also included the adoption of the city’s Urban Digital Twin, presenting an opportunity for Matera to re-discover its urban space and dynamics, and effectively manage future urban regeneration projects [1]. The project “The House of Emerging Technologies in Matera” (CTEMT) aims to transform Matera into an international reference center for the application of emerging technologies in the urban domain, specifically Artificial Intelligence (AI), Blockchain, Internet of Things (IoT), and 5G. Technologies to serve city government in a broader sense, for example an optimizer and simulator of scenarios related to ongoing forms of urban system management, i.e. pedestrianize a street, traffic management, maintenance of urban greenery, waste management, and strategic planning i.e. the projects and strategies for the city and assessment of future trends. Firstly, hardware interventions will establish a technological infrastructure for gathering data from various aspects of the city. Secondly, software interventions will enable the analysis, management, and processing of this data, resulting in the development of innovative models, systems, and services. The resulting data, applications, and services will be accessible, with a particular emphasis on providing opportunities for startups involved in the project’s innovation domains to develop their products and services. The concept of digital twin entails the creation of a virtual replica or simulation that mirrors physical objects, systems, or processes [2]. It serves as a dynamic model, emulating its real-world counterpart, and finds application in various domains. This discourse presents a series of ambitious yet concrete scenarios that underscore the utilization of digital twins in urban contexts [3]. Several frameworks have been released for the description and development of Digital Twins in industrial sectors [4]. Each framework is accompanied by a delineation of the context, requisite data, the most suitable technologies and addressed needs, offering comprehensive insight into the concept’s essence. Within the domain of urban development and planning, the creation of a digital twin of a city holds significant potential. Integrating diverse data sources, this twin encapsulates the entire urban environment, allowing simulations of infrastructure development, transportation optimization, and energy consumption. Urban planners can leverage this model to assess the impact of new construction projects, predict traffic patterns, and evaluate environmental factors, thereby facilitating the design of sustainable and efficient cities. However, implementing urban digital twins poses several challenges and hurdles that cities should investigate if they want to reach the levels of industrial ones. These challenges can include personal data privacy and security concerns, data integration and interoperability issues, high costs of implementation due to the technical complexities, and comprehension and use of such technologies by the institutional stakeholders.

2 Digital Twins: Lessons from Matera’s CTEMT Relevant experiences concerning the identification of specificities arising from recent research in this field can be found in the literature [5]. On one hand, authors rely on the technological response that the Digital Twin can offer as an innovative solution for

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specific urban challenges [6, 7]. On the other hand, it opens up a broader reflection based on disciplinary contributions and integrated expert knowledge to assist in defining urban development strategies. In line with [1]: “generally, a computerized model of a physical system can never be the basis for a digital twin since many elements of the real system are ignored in such an abstraction. However, there is no doubt that some models are closer to reality than others...” The reference to the complexity of the city as a system finds unique elements in the case study of Matera, not only related to the physical configuration of urban spaces characterized by the uniqueness of the “Sassi” [8], but also to the recent valorization experience associated with the process of being the European Capital of Culture. The legacy of 2019 necessitates the association of the physical dimension with the social dimension of the context through a renewed interpretive structure. This process begins with the evaluation of past experiences and projects towards new forms of modeling, simulation, and optimization of the relationship between citizens and the city, with a focus on quality of life, safety and resilience, and socio-cultural-economic opportunities [9, 10]. In addition, another strategic dimension should be considered, which regards “tourists” as temporary users of urban space and services, sometimes seen as antagonistic to residents, but at other times supporting converging instances that contribute to defining “opportunities” for development from a new perspective of the city and the territory [11]. Regarding the Matera case study, issues related to the scale and size of the urban system emerge in relation to defining optimality criteria. The demographic threshold significantly influences the search for a balance between the demand and supply of services, allowing the utilization of technological and organizational solutions developed in contexts with a high concentration of demand. This requires the consideration of intervention areas and performance improvement objectives within the urban system as a set of elements conditioned by a hierarchy of priorities, where certain components must be preferred to concentrate resources and investments at the expense of others [12]. This depends on a future vision that can be better defined through the project’s experience. In a broader representation of the disciplinary debate, it is crucial not to forget that innovation experiences referred to as “smart cities” [13–15] offer a rich heritage of experiences and models worth considering. This can enable the activation of adaptation and transfer of urban practices to the components that the project will develop, both in terms of the strictly technological and digital aspects, as well as the wider perspective of urban development sustainability.

3 Data Model A further level of insight is related to defining a representative data model of urban components essential to producing useful digital replicas useful for urban analysis. A key factor in defining the data model is that such model should maintain a close connection to the objectives of the project, should be functional for modeling within the Twin, and aimed at optimization processes consistent with the instances that at the urban scale may characterize useful application domains of the Urban Digital Twin [16].

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In the virtual space of an urban digital twin, many of city physical infrastructure elements come together to form a comprehensive and dynamic simulation. Buildings and structures populate the virtual landscape, encompassing the residential, commercial, and industrial buildings. The mobility system and transportation networks weave throughout the digital twin, mirroring the real-world roads, highways, railways, etc. Street graph could be accurately recreated, capturing the details of intersections, traffic flows, and public transportation routes [17]. Moreover, parking lots and private garages could be mapped providing insight into the availability and utilization or saturation of parking spaces. All of this information results in a massive amount of data from a variety of sources that can be defined as big-data and as such is affected by 5V’s [18]. Within the context of the “model Alpha” in the city of Matera, a diverse range of geometric spatial data serves as the foundation for mapping the city’s physical infrastructure and identifying the main urban thematic structures. Each type of data brings different spatial information and contributes to simulate the digital replica: • Point data plays a crucial role in pinpointing specific locations or Points Of Interest (POI) within the urban shape. By precisely capturing the coordinates of buildings, commercial properties, transportation facility, and utility poles, point data enables the digital twin to simulate the exact location and distribution of these elements. This simplifies visualization, analysis, and monitoring of individual infrastructure components, enhancing the overall fidelity of the virtual city and facilitating topological associations with other type of data [19]; • Line data offers a means to represent linear features that traverse the urban environment. The detailed mapping of roads, railways and utility networks provides useful insights into the connectivity and layout of transportation or utility infrastructure through road graph mapping. By incorporating line data, the urban digital twin can simulate the flow of traffic, utilities, and resources, supporting planning and decisionmaking related to infrastructure optimization, route planning, and network design [17]. • Polygon data introduces the concept of enclosed areas or public spaces within the digital twin. By delineating administrative zones, parks, green spaces, and specific districts using polygons, the virtual representation can accurately depict the boundaries and extents of these areas. Polygon data is instrumental in simulating land use patterns and spatial relationships, empowering planners to assess urban density, analyze green spaces usage, and design urban interventions more precisely. However, a city is more than its physical elements, it is a dynamic entity shaped by its inhabitants. The pursuit of understanding social infrastructure within the urban digital twin is driven by the objective of fostering more inclusive, sustainable, and resilient cities and participative citizens [20–22]. Through unraveling the social implications of urban interventions, promoting citizen engagement, and facilitating evidence-based decisionmaking, the groundwork is laid for the development of cities that thrive and cater to the diverse resident and tourists needs [23].

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The social infrastructure focuses on capturing and modeling the intricate web of human interactions and behaviors within the urban context. This encompasses factors such as social interaction, community dynamics, events, and cultural practices that constitute the social fabric of the city [9]. To get the insights embedded within this interplay, a diverse array of data sources has to be employed. These sources encompass data derived from social media platforms, mobile phone records, surveys, and municipal authorities’ statistics, especially for analyze tourist dynamics [24, 25]. This type of data needs advanced analytical techniques such as network analysis, agent-based modeling, and data visualization to unravel the intricate relationships, patterns, and dynamics that shape the social fabric of the city within the virtual environment.

4 Conclusion In conclusion, the “Alpha model” to be developed in the Matera House of Emerging Technologies (CTEMT) project is a useful laboratory for testing and implementing IoT technologies and AI models for understanding and managing the complex dynamics of the urban environment. In general terms, the spatial data upon which the Urban Digital Twin’s functionalities are built should be made and organized according to a logic that aims to generate information to address specific urban questions. This involves defining synthetic indices and attributes based on a predefined classification of the territorial components to be modeled within the digital infrastructure. While some applications such as optimization for pedestrian routes may go as far as considering point disconnections and/or dynamic criticalities on the path such as a construction site, on the other hand, understanding the most frequently used areas of a green space does not require too much detailed representation. Such a process would streamline the mapping phase and simplify the development of IT models. By integrating social infrastructure into the urban digital twin, a deeper understanding of the multifaceted interplay between the physical and social systems emerges. This enables exploration and analysis of various aspects, including the impact of transportation on social equity, the influence of public spaces on social cohesion, and the relationship between urban form and community well-being [26]. The rationality of this process depends on the integration of two disciplinary languages: urban planning and computer science. The feasibility of defining functionalities that effectively address urban challenges depends largely on how well this integration is conducted, considering the project’s high technological potential in terms of digital infrastructure, sensor networks, and computational capabilities. Thus, it is necessary to work with the available data for the city of Matera, harmonizing the information requirements of the modelers, the availability of open data or data provided by project partners, and the functional requirements for urban governance. This complex methodological action will be carried out in the coming months as a short-term activity aimed at realizing the “model Alpha” according to the project specifications and additional features defined in collaboration with the Municipal Administration and the project partnership.

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References 1. Batty, M.: Digital twins (2018) 2. Batty, M.: Big data, smart cities and city planning. Dialogues Hum. Geogr. 3, 274–279 (2013). https://doi.org/10.1177/2043820613513390 3. Ivanov, S., Nikolskaya, K., Radchenko, G., Sokolinsky, L., Zymbler, M.: Digital twin of city: concept overview. In: Proceedings - 2020 Global Smart Industry Conference, GloSIC 2020, pp. 178–186 (2020). https://doi.org/10.1109/GloSIC50886.2020.9267879 4. Liu, M., Fang, S., Dong, H., Xu, C.: Review of digital twin about concepts, technologies, and industrial applications. J. Manuf. Syst. 58, 346–361 (2021). https://doi.org/10.1016/j.jmsy. 2020.06.017 5. Deng, T., Zhang, K., Shen, Z.-J.M.: A systematic review of a digital twin city: a new pattern of urban governance toward smart cities. J. Manag. Sci. Eng. 6, 125–134 (2021) 6. Ketzler, B., Naserentin, V., Latino, F., Zangelidis, C., Thuvander, L., Logg, A.: Digital twins for cities: a state of the art review. Built Environ. 46, 547–573 (2020) 7. White, G., Zink, A., Codecá, L., Clarke, S.: A digital twin smart city for citizen feedback. Cities 110, 103064 (2021) 8. Cardinale, T., Pavia, L., Zucchi, G.: The city of Matera and the Sassi: smart places with a Dantean attraction. In: REAL CORP 2014–PLAN IT SMART! Clever Solutions for Smart Cities. Proceedings of 19th International Conference on Urban Planning, Regional Development and Information Society, pp. 665–674 (2014) 9. Ye, X., et al.: Developing human-centered urban digital twins for community infrastructure resilience: a research agenda. J. Plan. Lit. 38, 187–199 (2023) 10. Nochta, T., Wan, L., Schooling, J.M., Parlikad, A.K.: A socio-technical perspective on urban analytics: the case of city-scale digital twins. J. Urban Technol. 28, 263–287 (2021) 11. Gatto, R.V., Corrado, S., Scorza, F.: Towards a definition of tourism ecosystem. In: 18th International Forum on Knowledge Asset Dynamics (IFKAD) - Managing Knowledge for Sustainability (2023) 12. Lacerenza, A., et al.: “Back to the villages”: design sustainable development scenarios for in-land areas (2023). https://doi.org/10.1007/978-3-031-37123-3_14 13. Caragliu, A., Del Bo, C., Nijkamp, P.: Smart cities in Europe. Research Memoranda series 0048 (VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics). J. Urban Technol. 18 (2009) 14. Kitchin, R.: Making sense of smart cities: addressing present shortcomings. Camb. J. Reg. Econ. Soc. 8, 131–136 (2015) 15. O’Dwyer, E., Pan, I., Acha, S., Shah, N.: Smart energy systems for sustainable smart cities: current developments, trends and future directions. Appl. Energy 237, 581–597 (2019) 16. Silva, B.N., Khan, M., Han, K.: Towards sustainable smart cities: a review of trends, architectures, components, and open challenges in smart cities. Sustain. Cities Soc. 38, 697–713 (2018) 17. Bao, L., Wang, Q., Jiang, Y.: Review of digital twin for intelligent transportation system. In: 2021 International Conference on Information Control, Electrical Engineering and Rail Transit (ICEERT), pp. 309–315 (2021) 18. Arputhamary, B., Arockiam, L.: Data integration in Big Data environment. Bonfring Int. J. Data Min. 5, 1–5 (2015) 19. Jiang, S., Alves, A., Rodrigues, F., Ferreira, J., Pereira, F.C.: Mining point-of-interest data from social networks for urban land use classification and disaggregation. Comput. Environ. Urban Syst. 53, 36–46 (2015). https://doi.org/10.1016/j.compenvurbsys.2014.12.001 20. Corrado, S., Santopietro, L., Scorza, F.: Municipal climate adaptation plans: an assessment of the benefit of nature-based Solutions for urban local flooding mitigation (2021). https:// doi.org/10.31428/10317/10497

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21. Corrado, S., Giannini, B., Santopietro, L., Oliveto, G., Scorza, F.: Water management and municipal climate adaptation plans: a preliminary assessment for flood risks management at urban scale. In: Gervasi, O., et al. (eds.) ICCSA 2020. LNCS, vol. 12255, pp. 184–192. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-58820-5_14 22. Scorza, F., et al.: Training for territorial sustainable development design in Basilicata remote areas: GEODESIGN workshop. In: Gervasi, O., Murgante, B., Misra, S., Rocha, A.M.A.C., Garau, C. (eds.) ICCSA 2022. LNCS, Part III, vol. 13379, pp. 242–252. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-10545-6_17 23. Gatto, R.V., Scorza, F.: Tourism ecosystem domains (2023) 24. Corrado, S., Gatto, R.V., Scorza, F.: The European digital decade and the tourism ecosystem: a methodological approach to improve tourism analytics. In: 18th International Forum on Knowledge Asset Dynamics (IFKAD) - Managing Knowledge For Sustainability (2023) 25. Tang, L., Li, J., Du, H., Li, L., Wu, J., Wang, S.: Big data in forecasting research: a literature review. Big Data Res. 27, 301–323 (2022). https://doi.org/10.1016/j.bdr.2021.100289 26. Lagonigro, D., et al.: Downscaling NUA: Matera new urban structure. In: Gervasi, O., et al. (eds.) ICCSA 2023. LNCS, vol. 14110, pp. 14–24. Springer, Cham (2023). https://doi.org/ 10.1007/978-3-031-37123-3_2

City Burning: New Approaches to Measure the UHI and Its Effect on Urban Energy Balance Federica Gaglione1

, Carmela Gargiulo2

, and Floriana Zucaro2(B)

1 Department of Engineering, University of Sannio, Benevento, Italy 2 Department of Civil, Building and Environmental Engineering, University of Naples

Federico II, Naples, Italy [email protected]

Abstract. Climate change represents one of the main threats to which our planet is called to respond. IPCC highlights how to climate variability will intensify in the coming decades and extreme events related will constitute a growing risk for our cities, like the heatwaves. In particular, the urban heat island (UHI) effect further exacerbates the heat stress resulting from them by determining an increase of energy consumption. The international scientific framework shows that the energy consumption of a territory depends on the urban assets and, vice versa, the energy balance is linked to the physical and functional organization of the settlement such as the behaviour of citizens. The aim of this work is to define a methodology for measuring the weight of the urban characteristics on UHI that mainly affect the energy balance. Innovative tools are used to develop a spatial analysis by regression analysis that is combined with a second analysis on the influence of variables on the energy balance of urban areas through a hot-spot density. The experimentation is carried out on the city of Naples, which differs in its settlement, functional and demographic characteristics, showing the classification of highly or less critical urban areas. Keywords: Urban Heat Island · Urban energy balance · Urban planning · Spatial analysis · Geographical Information System

1 Introduction The higher temperatures of the urban built environment compared to the rural areas were noticed and introduced as an issue within the scientific debate during the past two centuries as a UHI [1–3]. Nowadays it is a global phenomenon, as UHI effect is interrelated to climate change due to the fact that a warming climate will increase already higher temperatures. it is projected that by 2100, global average temperatures will rise by 2.7–3.5 °C, depending on the assumptions for post-2030 emissions [4] and with the enhanced greenhouse effect and global warming, UHI is an extremely important issue to be addressed as the growing urban population could be further exposed to elevated temperatures. International studies paved the way for connecting UHI and urban development as early as the mid-20th century, even though its strength varies depending © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 237–247, 2024. https://doi.org/10.1007/978-3-031-54118-6_23

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on the city’s location and environment. In fact, different intensities and sizes of UHI depend on site specific urban asset, shape and geometry, more than meteorological conditions [5]. As investigated by [6–8], the relationship between urban features and UHI can be summarized in three key points: – localization and distribution of green and water spaces, such as trees, as they contribute to reducing temperature through evapotranspiration processes; sidewalks, and buildings are the most important drivers of regional-scale temperature variability. – building materials, such as asphalt, concrete, and metal increased storage and transmission of sensible heat energy, allowing high-intensity solar radiation to be captured; – presence of tall buildings and narrow roads increases the effectiveness of UHI by trapping warm air and reducing airflow; – direct emissions of heat generated by the combustion of all types of fuel and consumption of electricity. The scientific community has been investigating UHI phenomenon through three main lines of research. Scholars as [9, 10] have developed the field of remote sensing by identifying Land Surface Temperature as one of the most important factors that can influence the UHI phenomenon [11, 12] For instance, Chakraborty et al. [13] developed an algorithm to map UHI intensity worldwide based on LST. Within this scientific domain, the impact of land surface components on LST was tackled by using different spectral indices (e.g., the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Built-Up Index (NDBI)), as proxies for surface vegetative cover, built-up areas, and other land surface components. Remote sensing allowed scholars to relate LST and UHI to Land use and land cover (LULC) changes too, as the reduction in permeable surfaces is associated with increased absorption of solar radiation, leading to rising LST with harmful effects on climate and human life. In this perspective, researchers developed also a variety of physics-based modelling techniques like the Urban Canopy Models (UCMs) which are the well-known physicsbased approach to simulate and assess the mutual influences of LST and LULC [e.g. 14– 15]. The study of the interactions among land use changes, temperature value distribution and heat-stress conditions, fostered the study of the urban micro-climate effects on energy consumption at urban and building levels, on one side, and the study of the most effective and suitable climate change adaptation strategies to reduce UHI vulnerability of cities, on the other side. Zinzi et al. [16] and Kbilai et al. [17] developed a simulation model that can describe the relationship between summer weather conditions and building cooling energy demand in an urban environment. They found that a drop in outside temperature of more than 1 °C could reduce peak cooling power demand in Tokyo’s central business district by up to 6%. According to Kyriakopoulos et al. [18] and Salata et al. [19] in Greek cities UHI effects could double the cooling load of buildings in the city and triple the peak load of cooling flow.

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2 Methodology As previously stated, there is no single cause of UHI, as numerous physical, climatic and functional elements contribute to warm cities. According to this, we assumed the energy balance equation as a quantitative model to define the main urban characteristics that contribute to the UHI effect. Figure 1 shows the proposed methodology framework.

Fig. 1. Methodology of the study.

The urban energy balance was first proposed by Nunez et al. [20] within a city as follows: Q ∗ +QF = QH + QE + QS + QS

(1)

where Q* is the net radiation, QF represents the anthropogenic energy release, QH and QE are the fluxes of the sensible and latent heat, respectively, and QS is the storage

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heat flux and represents all energy storage mechanisms [Wm−2 ] within elements of the control volume, including air, trees, building fabrics, and soil. This equation allows to investigate and simplify the intricacy, in which the heat created by and contained in an area could be calculated and demonstrates that increasing the production of anthropogenic heat leads to raised temperatures and generates a UHI that provides warm air canopy over the city. Consequently, it causes significantly increased energy consumption to heat and cool buildings [21]. For each term in Eq. (1), the relevant variables useful for their measurement were identified, which refer to the phenomenon under consideration (UHI) and the context in which it occurs (urban characteristics). The terms on the left-hand side of the equation refer to UHI values measured from satellite image processing operations (Landsat 8). In particular, medium-resolution (30 m/pixel) raster imagery was processed to analyze the spatial variation of temperature in an urban layer (above vegetation, usually called the canopy layer) up to 2 m above the ground. The terms on the right-hand side, on the other hand, refer to the morphology of the urban fabric (average height and construction period of buildings), the density of the built up area, the presence of permeable and impermeable surfaces, and the radiative properties of the materials present in an urban area. All these eight variables allow to measure the effect of all the main factors of UHI formation and their relative contributions to heat and energy exchanges. A stepwise analysis was used to identify variables that have a significant impact on urban heat islands. This exploratory regression work system consists of evaluating all possible combinations of explanatory input variables and searching for the OLS model that best explains the dependent variable in the context of user-defined criteria. Ordinary Least Square (OLS) regression analysis is used to determine the relationship between the urban form factor and UHI. OLS refers to regressing the dependence of a dependent variable (boundary) on one or more independent variables (independent variables) and estimating and/or predicting the population mean or mean value of the dependent variable based on its values. purpose. Spatially known independent variable. The OLS approach is used because population data are collected for all variables: γ = β0 + β1 X1 + β2 X2 + · · · βn Xn

(2)

Equation (2) is OLS regression. Where γ is variable dependent (UHI value), β coefficients, X explanatory variable (independent variables related to the urban characteristics), ε is the random error. The spatial regression analysis was followed by a hot-spot analysis for the variables that were found to be statistically significant on the basis of the probability coefficient values (p-value). The Hot Spot Analysis tool calculates the Getis-Ord Gi* statistic for each feature: Gi* statistics is calculated for the group of values within a distance threshold (d) from the feature i. The observed Gi* statistics for feature i are compared with the expected Gi* statistics if the same values of the whole dataset were randomly distributed. To be a statistically significant hotspot, a feature must have a high value and be surrounded by other high-valued features. Local totals for a feature and its neighbours are compared proportionally to the total for all features. A statistically significant Z-score is obtained when the local sum differs significantly from the expected local sum, and this difference is too large to be the result of chance. This technique is used because it identifies statistically significant spatial clusters of high values (hot spots) and low values (cold spots).

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These results allow to identify the parts of the city where the values of the most influencing variables on UHI are more significant and that would require ad hoc interventions to adapt to heat stress. The statistical and spatial analysis and all the geoprocessing operations on alpha-numeric data were sequentially executed in the model builder GIS tool for building and geoprocessing workflows models, where the output of one process is the input of another process. The research results were obtained through spatial geostatistics analyzes developed with the use of cutting-edge tools in the field of urban planning such as ArcGISPro. The proposed methodology was applied to the city of Naples, Italy. Naples is classified as the Italian urban area with the highest density of inhabitants per km2: 8,000 people per km2 on a land area of 118 km2 (Fig. 2). For this reason too, Naples ranks among the Italian municipalities with the highest percentage of artificial surface area in relation to administrative boundaries, at 63%. These aspects make the municipality of Naples particularly vulnerable to the consequences of climate change impacts. In fact, the heat wave peaks, according to the RPC 4.5 scenario, exceed 50 consecutive days, while for the RPC 8.5 scenario, these exceed 90 days [22].

Fig. 2. Naples study area with 30 districts localization.

3 Results and Discussions In accordance with the previous section, the entire research work was tested on the ten municipalities of the city of Naples. The decision to examine this area is due to the profound differences both in terms of population density and morphology of urban fabrics

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combined with functional characteristics making it a significant test of experimentation with respect to the phenomenon of urban heat islands. In detail, the work examines the phenomenon of urban heat islands in relation to the equation of the energy balance of urban systems to understand the areas where it is necessary to intervene as a priority. The first spatial OLS regression analysis allowed us to identify the statistically significant variables both individually and within the model used as the independent variable the urban heat island is defined as the temperature difference between the urban center and the area rural. The significance of the individual variables is described through the coefficients of probability and consistent probability which explain the statistical incidence through a p-value of 0.01 as well as the variance inflation factor (VIF, Variance Inflation Factor) which indicates redundancy between the variables if the value is 7.5. In particular, the first analysis better identifies the significance of variables linked on the one hand to the time of construction of the buildings such as those built before 1950 (p = 0.000992) and after 1980 (p = 0.017854) as well as the height of the buildings (p = 0.017854) by significantly identifying the physical and conformation characteristics of the urban fabrics as well as the population density with an equal value (p = 0.000000). In turn, the Variance Inflation Factor estimates a high value for characteristics related to the emissivity of the materials and the permeable surface of the city with values equal to 10.19 and 7.93. Instead, Fig. 3 shows the model residuals found in the output feature class. The values appear to be high in the central part of the municipali ty of Naples precisely in the V municipality and in the part below it in the Chiaia district and under the Posillipo ridge, presenting a colour between red and orange. These areas are characterized by a high built density and largely with buildings built before 1950 and with a low presence of surfaces destined for urban greenery. Similar considerations apply to the district of San Carlo all’Arena in areas with a high density of buildings which contrast with the areas adjacent to it. Red-orange urban areas are also present in the northwestern part of the municipality in the area that goes from Fuorigrotta, Bagnoli and Pianura, but due to completely different urban dynamics. The area of Ponticelli, Barra is a predominantly industrial area linked to logistics and freight transport. These areas appear to be characterized by a high concentration of anthropogenic activities as is the area of Poggioreale which, on the other hand, is an area with a high presence of offices interspersed with urban areas of economic and social housing. Fuorigrotta area is presented as an area with a high concentration of urban services compared to the area of Bagnoli, Pianura which was built as a predominantly residential area, but with a higher concentration of permeable demonstrating the yellow-green areas (Fig. 3). Finally, in the VIII municipality, there is strong opposition between the southwest and southeast part. The southwest part has predominantly wooded areas acting as a buffer element for the phenomenon of heat islands with respect to the highly urbanized area of Piscinola and Scampia. The orange-coloured areas appear to be near the ChiaianoPiscinola underground stations, reflecting the planning logic that the stations could be places of development and concentration of activities and residences, favouring heat emissivity. Similar considerations are extended in the Scampia district also due to the creation of a building system based on affordable popular housing designed in reinforced concrete

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Fig. 3. Classification of census tracts according to OLS results.

and whose shape of the building favours the aspect ratio (H/W) and therefore the increase in the intensity of the UHI. The outputs of the second part of the research work aimed at identifying the statistically significant spatial clusters in accordance with the significance of the values obtained from the OLS. The results obtained from the hot spot maps pursue a dual objective: methodological and application. On the one hand, they spatially identify which urban characteristics favor the phenomenon of heat islands and which have the greatest impact on the energy balance of urban areas. On the other hand, they provide a first knowledge scenario for the public decision-maker of the study on where priority action needs to be taken by identifying hot and cold spots in the territory being studied. Below are the high values that were obtained from the analysis of hotspots using the Gi-Bin index (Fig. 4, 5, 6 and 7). In detail, as regards the population density, the high values prove to be throughout the central area of Naples, also in agreement with the high built density compared to the neighbouring areas (Fig. 4). Instead regarding buildings built before 1950 and after 1980 (Fig. 5, 6). The map of pre-1950 buildings identifies the hottest areas of the most consolidated urban parts of the city relating to the historic centre of Naples up to the Chiaia district and the Posillipo area as can also be seen from the map of the heights of the buildings (Fig. 7). The situation appears to be the opposite for the map of buildings built after 1980 where the hot areas appear to be those of the most recent configuration due to an uncontrolled and unplanned building expansion according to well-defined logic such as the area of the Pianura district and the VIII municipality of Naples (Fig. 6). The comparative reading of the four hot spot maps bring out some critical points of the context under study. The city of Naples is presented in the central part with an urban

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Fig. 4. Hot-spot maps of population density.

Fig. 5. Hot-spot maps of buildings pre 50’s.

fabric with a high population density, some implanted on a planning logic and others born from an uncontrolled building expansion. It is precisely in these areas that buildings

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Fig. 6. Hot-spot maps of buildings post 80’s.

Fig. 7. Hot-spot maps of average building height.

of high historical, artistic and architectural value are found with a medium/high height of the buildings compared to the physical characteristics linked to the spaces and canals of the city which strongly affect the phenomenon of urban heat islands. Instead, the

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more recently formed urban fabrics such as the eighth and ninth municipality of Naples are mostly presented with buildings built after 1980 with materials such as reinforced concrete where, however, the high emissivity of the concrete is balanced with the high presence of wooded areas.

4 Conclusions The phenomenon of urban heat islands in relation to the energy balance of urban areas has assumed a key role in the scientific debate as can be seen from the first paragraph of this work. Significant are the growing scientific contributions as well as calls in Europe. In this direction, the research work is a first step to support local decision-makers in the development of policies aimed at outlining a systemic framework for measuring adaptation and mitigation to urban heat based on the energy balance of urban areas [23– 25]. The methodological results aim to measure the significant urban characteristics through spatial analysis techniques such as the OLS and the optimized Hotspot in order to understand how much each of them affects urban systems. The operational results aim at defining scenarios to support public administrations on how and where to intervene based on the parameters that significantly influence the territory, especially in the absence of sector planning on the effects of climate change. Limitations from the current model implementation arise from the variables, that can be referred more in detail to further urban characteristics related for instance to mobility and urban form features. Furthermore, the temporal component shall also be considered for assessing the UHI intensity evolution during different years. Hence, more time series analysis of temporal-related variables related also to weather conditions (e.g., relative humidity, wind direction, etc.) could be added, depending on data and computational resources availability.

References 1. Oke, T.R.: The energetic basis of the urban heat island. J. Remote Meteorol. Soc. 108, 1–24 (1982) 2. Oke, T.R., Maxwell, G.B.: Urban heat island dynamics in Montreal and Vancouver. Atmos. Environ. 9(2), 191–200 (1975) 3. Kłysik, K., Fortuniak, K.: Temporal and spatial characteristics of the urban heat island of Łod´z, Poland. Atmos. Environ. 33, 3885–3895 (1999) 4. IPCC: Summary for policymakers. In: Masson-Delmotte, V., et al. (eds.) Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (2021). ISBN: 978-92-9169-158-6 5. Chen, Y., Shan, B., Yu, X.: Study on the spatial heterogeneity of urban heat islands and influencing factors. Build. Environ. 208, 108604 (2022) 6. Cao, C., Li, X.H., Zhang, M., Liu, S.D., Xu, J.P.: Correlation analysis of the urban heat island effect and its impact factors in China. Huan Jing Ke Xue 38(10), 3987–3997 (2017) 7. Ellena, M., et al.: Micro-scale UHI risk assessment on the heat-health nexus within cities by looking at socio-economic factors and built environment characteristics: the Turin case study (Italy). Urban Clim. 49, 101514 (2023)

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8. Chokhachian, A., Perini, K., Giulini, S., Auer, T.: Urban performance and density: generative study on interdependencies of urban form and environmental measures. Sustain. Cities Soc. 53, 101952 (2020) 9. Xu, L.Y., Xie, X.D., Li, S.: Correlation analysis of the urban heat island effect and the spatial and temporal distribution of atmospheric particulates using TM images in Beijing. Environ. Pollut. 178, 102–114 (2013) 10. Wan, Z., Zhang, Y., Zhang, Q., Li, Z.-L.: Quality assessment and validation of the MODIS global land surface temperature. Int. J. Remote Sens. 25, 261–274 (2004) 11. Hulley, G.C., Ghent, D., Göttsche, F.M., Guillevic, P.C., Mildrexler, D.J., Coll, C.: Land surface temperature. In: Hulley, G.C., Ghent, D. (eds.) Taking the Temperature of the Earth. Elsevier, Amsterdam (2019) 12. Bokaie, M., Zarkesh, M.K., Arasteh, P.D., Hosseini, A.: Assessment of urban heat island based on the relationship between land surface temperature and land use/land cover in Tehran. Sustain. Cities Soc. 23, 94–104 (2016) 13. Chakraborty, T., Hsu, A., Manya, D., Sheriff, G.: A spatially explicit surface urban heat island database for the United States: characterization, uncertainties, and possible applications. ISPRS J. Photogramm. Remote Sens. 168, 74–88 (2020) 14. Silva, R., Carvalho, A.C., Carvalho, D., Rocha, A.: Study of urban heat islands using different urban canopy models and identification methods. Atmosphere 12(4), 521 (2021) 15. He, J., Liu, J., Zhuang, D., et al.: Assessing the effect of land use/land cover change on the change of urban heat island intensity. Theor. Appl. Climatol. 90, 217–226 (2007) 16. Zinzi, M., Carnielo, E., Mattoni, B.: On the relation between urban climate and energy performance of buildings. A three-years experience in Rome, Italy. Appl. Energy 221, 148–160 (2018) 17. Kubilay, A., Allegrini, J., Strebel, D., Zhao, Y., Derome, D., Carmeliet, J.: Advancement in urban climate modelling at local scale: urban heat island mitigation and building cooling demand. Atmosphere 11(12), 1313 (2020) 18. Kyriakopoulos, P., Caouris, Y.G., Souliotis, M., Santamouris, M.: Characteristics of the urban heat island effect in the coastal Mediterranean city of Kalamata, Greece. Int. J. Sustain. Energy 41(11), 1795–1818 (2022) 19. Salata, K.D., Yiannakou, A.: Green infrastructure and climate change adaptation. TeMA J. Land Use Mobil. Environ. 9(1), 7–24 (2016) 20. Nunez, M., Oke, T.R.: The energy balance of an urban canyon. J. Appl. Meteorol. Climatol. 16(1), 11–19 (1977) 21. Magli, S., Lodi, C., Lombroso, L., Muscio, A., Teggi, S.: Analysis of the urban heat island effects on building energy consumption. Int. J. Energy Environ. Eng. 6, 91–99 (2015). https:// doi.org/10.1007/s40095-014-0154-9 22. Spano, D., Mereu, V., Bacciu V., et al.: Analisi del rischio. I cambiamenti climatici in sei città italiane (2021). https://www.cmcc.it/it/. Accessed 01 Aug 2023 23. Guida, C.: Energy saving and efficiency in urban environments: integration strategies and best practices. TeMA J. Land Use Mobil. Environ. 15(3), 517–531 (2022) 24. Ustaoglu, E., Aydınoglu, A.C.: Land suitability assessment of green infrastructure development. TeMA J. Land Use Mobil. Environ. 12(2), 165–178 (2019) 25. Papa, R., Gargiulo, C., Zucaro, F.: Towards the definition of the urban saving energy model (UrbanSEM). Smart Energy Smart City Urban Plan. Sustain. Future, 151–175 (2016)

Spreading Porosity: The Contribution of Planning Tools in Increasing Soil Permeability

A Multidimensional Assessment Model of Settlement Efficiency at the Urban Scale Federica Cicalese(B) and Isidoro Fasolino Department of Civil Engineer, University of Salerno, Fisciano, SA, Italy [email protected]

Abstract. Although the increasing ecological sensitivity has led to the diffusion of various protocols that allow for the certification of the sustainability of a building or a district, tools currently used by planners for the multidimensional evaluation of urban planning projects on an urban scale are not yet available. The physical and functional organization of settlements is called upon to confront paradigms, principles and disciplinary criteria such as: contrast to land consume, urban compactness, density and multifunctionality, improving urban soil quality, adaptation to climate change. The aim of this contribution is to propose a multidimensional evaluation methodology that allows to control the level of urban efficiency of a settlement on an urban scale, through the identification of indicators that can be controlled from an urban planning point of view and can be used in the drafting of the implementation plans. The assessment of the degree of efficiency of a settlement, with reference to the presence of certain devices, is carried out by considering three different factors: resilience, resources, urban facilities. The methodology is configured as a support tool in implementation planning choices, allowing to guide urban planning towards higher performance values of settlements in terms not only of environmental but also economic and social sustainability. Keywords: Settlement efficiency · Sustainability · Implemented urban planning

1 Towards the 2030 Agenda In recent decades, an integrated vision of the three dimensions of sustainable development has been affirmed, leading to the birth of the 2030 Agenda, which defines 17 Sustainable Development Goals to be achieved by 2030, divided into 169 Targets. Goal 11 and 15, in particular, address respectively “Sustainable cities and communities”, setting the goal of making cities and settlements inclusive, safe, long-lasting and sustainable, and “Life on land” aimed at protecting and restore terrestrial ecosystems, sustainably manage forests, combat desertification, halt and reverse land degradation, and halt biodiversity loss. This growing sensitivity has flowed into the definition of an approach that tends to bring the complexity of the problem back to a local dimension, affirming the importance of local identity and community participation [1]. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 A. Marucci et al. (Eds.): INPUT 2023, LNCE 467, pp. 251–262, 2024. https://doi.org/10.1007/978-3-031-54118-6_24

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To achieve the goal of sustainable development it is necessary to find ways of measuring the efficiency of the actions that are implemented, it is necessary to define sustainability indicators, setting precise objectives to be achieved in territorial planning. The proposed methodology provides a set of methods for evaluating and choosing between different design alternatives, in which an attempt is made to explicitly take into account the multiple dimensions of the problem under consideration. In particular, a comparison between different scenarios is envisaged: base scenario; baseline scenario; project scenario. The main results of this research concern the possibility of numerically measuring both the objective and subjective aspects that influence urban quality at the urban scale, considered the most suitable as a self-sufficient spatial unit to show the results of redevelopment. The research presented in this article will develop by presenting a set of indicators (Sect. 3), identifying threshold values for each of them (Sect. 4) and, finally, defining an index of settlement efficiency (EI) (Sect. 5), in order to formulate a synthetic judgement on the overall performance of a portion of an urban area.

2 Methodology The evaluation of the degree of efficiency of a settlement cannot be carried out without considering the various factors that determine its performance: resilience, resources, urban equipment (Fig. 1). Resilience concerns the possibility for complex systems to react to severe and instantaneous events (shock) or severe chronic conditions (stress), activating response and adaptation strategies in order to restore functioning mechanisms. Resilient systems, in the face of stress, react by renewing themselves but maintaining the functionality and recognizability of the systems themselves [2, 3]. Talking about a resilient city is equivalent to talking about an urban system that adapts, restoring its functionality through change, to devastating phenomena, above all due to the wicked sealing of the soil and the consequent hydrogeological risk with phenomena that are repeated with increased frequency, strength and unpredictability. The development of sealed surfaces is largely attributable to territorial planning strategies that have not taken into consideration the irreversible soil loss and related environmental effects [4]. In order to achieve the efficiency of the settlements it is also necessary to guarantee the presence of urban facilities, such as: pedestrian areas, cycle paths, ecological corridors, social housing, etc. The analysis of urban sustainability, fundamental for planning, is carried out through the application of methodologies which evaluate the quality objectives at an environmental, urban and building level. It should be highlighted that this theme brings with it a series of multidisciplinary aspects, think of urban green areas, mobility, energy, water management, waste management, etc., which go beyond urban planning in the strict sense. With the aim of introducing indicators capable of interpreting these different components of a territorial system, a model for evaluating the efficiency of the settlement

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has been developed that is as comprehensive as possible of the various aspects that fall within the vast concept of sustainability. The model focuses on the devices necessary to make environmental sustainability concrete in urban areas: infrastructures, interventions for adaptation to climate change, reduction of climate-altering gas emissions, reduction of soil consumption, waste management, promotion of mobility eco-friendly, energy efficiency and protection of natural resources. Within this strategy, priority importance is assigned to the permeability of urban soils. The proposed qualitative and quantitative descriptors are then aggregated to develop an index to evaluate the level of urban quality. The second step, in fact, consists in carrying out a multi-criteria evaluation procedure aimed at formulating a synthetic judgment of the global performance of a portion of the urban area with the aim of complying with environmental and resilience criteria.

Fig. 1. The indicators examined in the three spheres that define the performance of a settlement (source: elaboration by authors).

3 Identification of Indicators Sustainability indicators undoubtedly constitute a starting point to begin on the path to sustainable urban land use, being able to evaluate the best strategies to be implemented to achieve the desired objective. The model is based on the concepts of urban complexity and compactness and on shared priorities such as functional and social mixité, public space as a cornerstone of planning and public housing for social cohesion, the pre-eminence of the pedestrian

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staircase that favours soft and eco-sustainable mobility, the preservation of cultural, historical and natural resources, and the soil permeability that helps counteract the urban heat island phenomenon. Furthermore, the inability of the sealed areas to absorb some of the water by filtration means that the greatest impact is on the water flow. By significantly increasing the surface flow, the volume and speed increase, causing obvious problems in the control of surface water, in particular during particularly intense rain phenomena, and affecting the recharge capacity of the aquifers [4]. Therefore, the indicators have been selected also taking into account that the sustainable design of spaces must: adapt to climate change; ensure an adequate level of soil permeability; allow the collection of rainwater as a result of massive storms; generate spaces to manage emergencies, suitable for gathering an impressive number of people in safe conditions. In this contribution, a set of 24 indicators is proposed divided into capital: natural, i.e. inherent to the set of ecosystems, biodiversity and environmental matrices that are necessary to preserve all the natural resources that the environment makes us available; artificial, that which originates from the transformation of natural capital (houses, roads, bridges, etc.); social, which refers to the heritage of knowledge and interaction between the established communities [5–7]. The indicators were selected through the analysis of technical-scientific literature, best practices and frequently through an elaboration by the authors. Table 1. Natural Capital indicators. N. Indicator

Description

Formula RH2 O =

1

Mirrors of water

Percentage of bodies of water with respect to the total area

2

Permeable surfaces

Percentage of permeable or Rp = filtering area with respect to the total surface area

3

Ecological habitat

Percentage ratio between Rhe = the planted area with native shrubby tree species and the external surface

4

Urban gardens

Incidence of areas destined for urban gardens with respect to settleable inhabitants

5

Ecological micro-corridors Percentage of connected Rvc = green areas compared to the total area of green areas

6

Tree density

Number of tall trees to be planted per m2 of reference area

Iou =

Ialb =

Unit of measure RH 2 O St 100

Sp St 100

Sau Se 100

m2 m2

m2 m2

m2 m2

Sou Ninhab 100

m2 inhab

Svc Svt

m2 m2

Nalb St 100

alb m2

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Table 2. Artificial Capital indicators. N.

Indicator

Description

Formula

Unit of measure

meqPC (100)ab

Ipc =

m 100 inhab

7

Cycle paths

Indicator which expresses in equivalent meters (meq) the ratio between the weighted length of the different types of slopes and the number of inhabitants

8

Pedestrian spaces

Percentage of streets and Rsp = pedestrian spaces in relation to the total area of streets and roads

9

Intermodal nodes

Qualitative indicator that expresses the number of combinations of eco-sustainable modes of transport present in the node

Nim n Types of green mobility present in the node

10

Recycling and composting infrastructure

Presence of adequate waste collection points, hazardous waste and composting equipment

Irc no. Requirements (0/1/2/3) present

11

Isolated orientation

Rotation and length of the block axis: a) an axis rotated ±15° with respect to the east-west direction; b) length of the east-west axis at least equal to the north-south one

Oi =

12

Building orientation

Rotation and length of the buildings axis: a) the longest axis rotated ±15° with respect to the east-west direction; b) length of one axis equal to at least 1.5 times the length of the other

Oe =

13

Shape of the buildings

Ratio between the dispersing surface of the envelope and the volume of the building

Rf =

14

Urban compactness

Indicator that allows to evaluate settlement dispersion

CU =

n 2 i=1 pi di  n i=1 pi

m5 m3

15

Photovoltaic

Percentage of areas used for photovoltaics compared to the total area

Rfot =

Sfot St

m2 m2

16

District heating

Annual energy consumption produced by the centralized system (district heating or district cooling) compared to the total annual energy consumption

EP T =

Ssp Sv

100

m2 m2

n



I0 Itot

100

n



E0 Etot

S disp

V

100

n

/nEtot

m2 m3

100

EP T EP gl

100

kWh

m3 kWh/m3

(continued)

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F. Cicalese and I. Fasolino Table 2. (continued)

N.

Indicator

Description

Formula Rtv =

17

Green roofs

Ratio between the surface area of green roofs and 50% of the covered area

18

Sustainable urban drainage system

Quantity of surfaces SD = equipped with drainage devices compared to the total urbanized area

19

Water collection and reuse system

Volume of drinking water saved compared to the calculated basic requirement

Unit of measure

Stv 50%S c

m2 m2

100



Irra =

SD St

Vris Fstd

m2 m2

100

m3 /year m3 /year

100

Table 3. Social Capital indicators. N.

Indicator

Description

Formula

Unit of measure

20

Watersquare

WS Presence/Absence

n

21

Multifunctional square

Ppol Presence/Absence

n

22

Urban center

UC Presence/Absence

n

23

Functional mixité

Presence of a square or public space suitably designed to become a rainwater collection and storage basin in the event of heavy rains Presence of a resilient and multipurpose square that satisfies multiple needs: meeting place, market point, square for events, square for emergency management Presence of a space for the aggregation and participation of citizens It measures the degree of organization of the urban system, providing information on the diversity of uses and services Application of the Gini heterogeneity index to obtain information on the diversity of uses and services in a given territory

IG = 1 − fi2

24

Social mixité

ENT =

−

 k

j=1 P

j ln

 j  P

[−]

ln(k)

[−]

The approach is strictly urbanistic, in fact all the elements, devices and indicators are identified because they can be controlled from an urbanistic point of view (those that allow us to describe the forms and/or functions of the territory) or related to the building scale, i.e. they are project choices that can be inserted within the plans, excluding

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everything which, however, can only be controlled at an administrative-political level. Therefore, those criteria (indicators) proposed by the protocols that do not meet this criterion (that is, that cannot be controlled from an urbanistic point of view) have been excluded. Below are the indicators considered, broken down by capital, with the respective formulas.

4 Identification of Benchmarks In order to arrive at a synthetic evaluation on the performance of each individual device and to be able to verify the degree of success and effectiveness of certain design choices, it is necessary to assign performance bands (Tables 4, 5 and 6). Table 4. Benchmarks of natural capital indicators. N.

Indicator

Benchmarks

Score

Performance level

1

RH2 O

2

Rp

3

Rhe

4

Iou

5

Rvc

6

Ialb