Real-Time Environmental Monitoring [2 ed.] 1032545712, 9781032545714

Written 10 years after the publication of the first edition, this updated edition of Real-Time Environmental Monitoring:

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Table of contents :
Cover
Half Title
Title Page
Copyright Page
Table of Contents
Preface to the Second Edition
Preface to the First Edition
Author
Chapter 1 Principles of Environmental Monitoring
Introduction
Why is Environmental Monitoring Necessary?
Environmental Systems, Ecosystems, and Planet Earth
Human Interactions with the Environment
Continuous Real-Time Monitoring
Data Management and the World Wide Web
Example: Global Monitoring
Statistics and Data Analysis
Random Variables: Distributions and Moments
Normal or Gaussian Distribution
Covariance and Correlation
Exploratory Data Analysis
Statistical Inference
Hypothesis Testing
Confidence Intervals
Parametric Methods
Nonparametric Methods
Simple Linear Regression
From Measuring to Knowing, Analysis, and Modeling
Scales and Resolution
Precision and Accuracy
Remote Sensing: Airborne and Spaceborne Platforms
More on Applications
Examples of Programs and Agencies
Environmental Monitoring Books
Exercises
References
Chapter 2 Programming and Single-Board Computers
Introduction
Computer Organization and Architecture
Single Board Computers
A/D and D/A Channels
Serial Communications
Universal Asynchronous Receiver Transmitter
RS-232
USB
Networks
Open Systems Interconnection (OSI) Model
TCP/IP
Ethernet
Wireless Fidelity (Wi-Fi)
Internet and World Wide Web (WWW)
Internet of Things (IoT)
SBC, System on a Chip (SoC), and MCU
SoC
ARM Architectures
SBC Example: Raspberry Pi
Microcontrollers
MCU Example
In-Circuit Serial Programming (ICSP)
MCU-Based SBC Example: Arduino
Example MCU-Based SBC
Concepts of Programming
Python
Arduino
HTML
CSS
PHP
JS
SQL
Exercises
References
Chapter 3 Sensors and Transducers: Basic Circuits
Introduction
Principles of Electrical Quantities
Circuits: Nodes and Loops
Measuring Voltages, Currents, and Resistances
Sensors
From Sensors to Transducers
Sensor Specifications: Static
Resistive Sensors
Thermistors: Temperature Response
Example: From Thermistor to Temperature Transducer
Calculating Sensitivity and Linearity Error
Reading Output Voltage with A Digital Device
Inverting the Transducer Output to Obtain Temperature
Self-Heating Effect
Example: Wider Temperature Range
Example: A Temperature Transducer for Air, Soil, and Water
Example: Thermocouples
Examples: Using Thermocouples
Exercises
References
Chapter 4 Bridge Circuits and Signal Conditioning
Introduction
Linearized Thermistor: Small Variation Analysis
Voltage Divider with Linearized Thermistor
Balanced Source Voltage Divider
One-Sensor Circuit: Quarter-Bridge
Two-Sensor Circuit: Half-Bridge
Two Sensors with Opposite Effect: Half-Bridge
Four-sensor Circuit: Full-bridge
Zero Adjust and Range Adjust
Sensor Specifications
Electrochemical Sensors
Example: Dynamic Specifications and a Potentiometer-Based Wind Direction
Dielectric Properties
Example: Piezoelectric Sensors
Example: Soil Tensiometer
Signal Conditioning
Operational Amplifiers
Linearization of the Bridge Circuit Output
Common-Mode Rejection
Instrumentation Amplifier
Spectrum
Noise
Electric Field and Electrostatic Shielding
Isolation
Cold-Junction Compensation
A/D Converter (ADC)
Current Loop: 4–20 mA
Pulse Sensors
Exercises
References
Chapter 5 Dataloggers and Sensor Networks
Introduction
DAS
Dataloggers
Applications in Environmental Monitoring
Analog Channels
RTC
Pull-Up Resistors
Serial Communication, Dataloggers, and Sensor Networks
RS-232
RS-485
SPI
I2C
SDI-12
MCUs as DAS
Conditions and Enclosures
A Datalogger Example: The CR1000
Remote Telemetry Unit or Remote Terminal Unit (RTU) and Supervisory Control and Data Acquisition (SCADA)
Exercises
References
Chapter 6 Wireless Technologies: Telemetry and Wireless Sensor Networks
Introduction
Radio Wave Concepts
Electromagnetic Waves
Radio Waves
Propagation
Propagation Models
Free-space Propagation Model
Two-Ray Propagation Model
Fresnel Zones
Antennas and Cables
Fade Margin
Polarization
Radio Links: Communication Channel
Modulation: Digital Signals
Channel Performance
Multiplexing
Spread Spectrum
Wi-Fi
Cellular Phone Network and Satellite Links
Wireless Sensor Networks (WSNs)
WSN Standards and Technologies
IoT
WSN Nodes
Examples of Devices for WSN Nodes and IoT
Moteino
ESP8266 and ESP32
Xbee
LoRa
Network Protocols
Media Access Control (MAC)
Multi-Hop Wireless Communication
LoRa-Based Protocols
Network Protocol for Environmental Monitoring
MQTT Protocol
WSN and Environmental Monitoring: Practical Considerations and Examples
Radio Propagation and WSN
Radio Propagation Experiments for WSN
Example: WSN for Soil Moisture in a Hardwood Bottomland Forest
Example: WSN for Soil Moisture using Moteino
Example: Soil Monitoring Using ESP8266 and MQTT
Exercises
References
Chapter 7 Environmental Monitoring and Electric Power
Introduction
PV Panels
PV Cells
PV-Cell Model and I-V Characteristics
From Cell to Module
Load and Power
Charging a Battery from a Solar Panel
Using a Voltage Regulator
Using a Buck Converter
Using a Buck-Boost Converter: MPP Tracking (MPPT)
Tilting the Panel
Atmospheric Effects
Sun Path
Impact of Temperature on Solar Panel
Power Budget and Power System Sizing
Powering WSN Nodes
Environmental Monitoring of Renewable Power Systems
Solar Radiation
Wind Speed
Hydroelectric
Exercises
References
Chapter 8 Remote Monitoring of the Environment
Introduction
Remote Sensing of the Environment
Optical Remote Sensing
Pixel, Raster, and Image
Imagery Specifications: Resolution and Quality
Spaceborne Remote Sensing: Types of Orbits
Platforms and Imagery
Geodetic Datum or System
World Reference System (WRS)
UTM Coordinate System
Bands and Image Display
Analysis Using Indices
Reclassification
Multivariate Analysis and Machine Learning
Reducing Dimensionality
PCA
SVD and Biplots
PCA Applied to Remote Sensing Images
Unsupervised Classification: Cluster Analysis
Hierarchical Cluster Analysis
K-Means
Unsupervised Classification of Remote Sensing Images Using K-Means
Exercises
References
Chapter 9 Probability, Statistics, and Machine Learning
Introduction
Probability
Algebra of Events
Combinations
Probability Trees
Conditional Probability
Binary (2-Class) Classification
Confusion Matrix
Bayes’ Theorem and Classification
Generalization of Bayes’ Rule to Many Events
Biosensing of Water Quality
Bayes’ Rule and ML
Naïve Bayes Classifier
Decision Trees
Discrete RVs
Probability Mass Function (PMF)
Cumulative Mass Function (CMF)
First Moment or Mean
Second Central Moment or Variance
Binomial Distribution
Bivariate Discrete Random Variables
Information Theory
Counts and Proportions
χ[sup(2)] (Chi-Square) Test
Contingency Tables and Cross-Tabulation
Supervised Classification: Confusion Matrix
Multiple Linear Regression
Matrix Approach
Evaluation and Diagnostics
Variable Selection
CART
Classification Trees
Regression Trees
Model Complexity
Cross-Validation
CART Applied to Supervised Classification for Remote Sensing
Exercises
References
Chapter 10 Databases and Geographic Information Systems
Introduction
Databases
Server Client: Datalogging and DB
Relational databases
Data Models and Entity Relation Diagrams
SQL
DDL
DML
XML
GIS
GIS Software
GIS Layers
Raster Layers
Raster Analysis: Entry-Wise Calculations
Raster Analysis: Neighborhood and Zonal Calculations
Vector Layers
Vector Analysis
Backup
Web Services
Metadata, Standards, Interoperability, Preservation
Example: Data Collected from Distributed Sensor Systems
Exercises
References
Chapter 11 Atmospheric Monitoring
Introduction
Earth’s Atmosphere
Composition and Vertical Structure
Direct and Diffuse Solar Radiation
Greenhouse Effect
Increasing Atmospheric CO[sub(2)] Concentration
Doubly Exponential
Nonlinear Regression
Global Temperature: Increasing Trend
Atmosphere – Near-Surface Air Quality
Standards
Air Monitoring Stations
Optical Devices
Linear Photodiode Array (PDA) and Charged Coupled Devices (CCD)
Dispersive Spectrometers
Photomultiplier Tubes
Beam Splitter
Fourier Transform Interferometer
Fiber Optics
Measurement Methods Using Samples in Closed Path
OAS
Chemiluminescent Analyzer
Fluorescence Instruments
Non-Dispersive Infrared
Measurement Methods Using Open Path
Total Column Estimation from the Ground
Example: Measuring UV and Total Column Ozone Concentration by OAS and DOAS
Atmospheric Gases and Air Quality from Remote Sensing
Atmosphere – Weather
Air Temperature
Precipitation
Relative Humidity
Solar Radiation
Wind Velocity and Direction: Sonic Anemometers
Next-Generation Weather Radar (NEXRAD)
Weather Satellites
Exercises
References
Chapter 12 Water Monitoring
Introduction
Water
Water Level and Depth
Water Velocity and Flow
Water Quality Parameters
Temperature
Electrical Conductivity
TDS and Salinity
pH and ORP
Dissolved Oxygen
Turbidity
Fluorometer
Multiple Parameter Probes
Importance of Ionic Profile of Water Quality
Light as a Function of Depth
Productivity and Respiration
Automated Real-Time Biomonitoring
Modeling and Monitoring of Surface Water
Hydrodynamic Models
Water Quality Models
Hydrological Models
Remote Sensing of Water Quality
Ocean Monitoring
Groundwater Monitoring
Autoregressive Analysis of Time Series
Exercises
References
Chapter 13 Terrestrial Ecosystems Monitoring
Introduction
Soil Moisture
TDR
Capacitance Probes
Soil Tension: Tensiometer
Infiltrometers
Soil EC
Evapotranspiration
Sap Flow
Lysimeters
Productivity
Gas Exchange
Chlorophyll Fluorescence Combined with Gas Exchange
Canopy Gas Exchange
Micrometeorological Flux Measurements
Covariance: A Review of Basic Concepts
Eddy Covariance
Tree Growth, Dendrometers
Leaf Area
Leaf Level
Canopy Analyzer
Solar Radiation and Spectral Measurements
IR Thermometer
Ground Penetrating Radar
Remote Sensing of Terrestrial Ecosystems
Exercises
References
Chapter 14 Wildlife Monitoring
Introduction
Radio Monitoring
Terrestrial
Aquatic
Acoustic Monitoring
Terrestrial
Aquatic
Satellite
Global Positioning System
Pop-Up Satellite Archival Tags
Proximity Sensors
Data Storage Tags
Camera and Video
Autonomous Vehicles
Habitat Monitoring
Habitat Suitability Index
Habitat Fragmentation Analysis
Vertical Structure
Spatial Analysis
Testing Spatial Patterns: Cell Count Methods
Nearest Neighbor Analysis
Geostatistics
Population and Community Modeling
Exercises
References
Index

Real-Time Environmental Monitoring [2 ed.]
 1032545712, 9781032545714

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