Ebook: Progress in Geospatial Analysis

This book examines current trends and developments in the methods and applications of geospatial analysis and highlights future development prospects. It provides a comprehensive discussion of remote sensing- and geographical information system (GIS)-based data processing techniques, current practices, theories, models, and applications of geospatial analysis. Data acquisition and processing techniques such as remote sensing image selections, classifications, accuracy assessments, models of GIS data, and spatial modeling processes are the focus of the first part of the book. In the second part, theories and methods related to fuzzy sets, spatial weights and prominence, geographically weighted regression, weight of evidence, Markov-cellular automata, artificial neural network, agent-based simulation, multi-criteria evaluation, analytic hierarchy process, and a GIS network model are included. Part three presents selected best practices in geospatial analysis. The chapters, all by expert authors, are arranged so that readers who are new to the field will gain an overview and important insights. Those readers who are already practitioners will gain from the advanced and updated materials and state-of-the-art developments in geospatial analysis.

---

This book examines current trends and developments in the methods and applications of geospatial analysis and highlights future development prospects. It provides a comprehensive discussion of remote sensing- and geographical information system (GIS)-based data processing techniques, current practices, theories, models, and applications of geospatial analysis. Data acquisition and processing techniques such as remote sensing image selections, classifications, accuracy assessments, models of GIS data, and spatial modeling processes are the focus of the first part of the book. In the second part, theories and methods related to fuzzy sets, spatial weights and prominence, geographically weighted regression, weight of evidence, Markov-cellular automata, artificial neural network, agent-based simulation, multi-criteria evaluation, analytic hierarchy process, and a GIS network model are included. Part three presents selected best practices in geospatial analysis. The chapters, all by expert authors, are arranged so that readers who are new to the field will gain an overview and important insights. Those readers who are already practitioners will gain from the advanced and updated materials and state-of-the-art developments in geospatial analysis.

---

This book examines current trends and developments in the methods and applications of geospatial analysis and highlights future development prospects. It provides a comprehensive discussion of remote sensing- and geographical information system (GIS)-based data processing techniques, current practices, theories, models, and applications of geospatial analysis. Data acquisition and processing techniques such as remote sensing image selections, classifications, accuracy assessments, models of GIS data, and spatial modeling processes are the focus of the first part of the book. In the second part, theories and methods related to fuzzy sets, spatial weights and prominence, geographically weighted regression, weight of evidence, Markov-cellular automata, artificial neural network, agent-based simulation, multi-criteria evaluation, analytic hierarchy process, and a GIS network model are included. Part three presents selected best practices in geospatial analysis. The chapters, all by expert authors, are arranged so that readers who are new to the field will gain an overview and important insights. Those readers who are already practitioners will gain from the advanced and updated materials and state-of-the-art developments in geospatial analysis.
Content:
Front Matter....Pages i-xii
Introduction: Geospatial Analysis....Pages 1-9
Front Matter....Pages 11-11
Multispectral Classification of Remote Sensing Data for Geospatial Analysis....Pages 13-28
Data Collection, Processing, and Applications for Geospatial Analysis....Pages 29-48
Front Matter....Pages 49-49
Fuzzy Set Theory in Geospatial Analysis....Pages 51-71
Spatial Prominence and Spatial Weights Matrix in Geospatial Analysis....Pages 73-84
Geographically Weighted Regression in Geospatial Analysis....Pages 85-96
Weight of Evidence in Geospatial Analysis....Pages 97-106
Markov–Cellular Automata in Geospatial Analysis....Pages 107-124
Multi-layer Perceptron Neural Networks in Geospatial Analysis....Pages 125-141
Agent-Based Simulation in Geospatial Analysis....Pages 143-156
Analytic Hierarchy Process in Geospatial Analysis....Pages 157-181
GIS Network Model in Geospatial Analysis....Pages 183-194
Front Matter....Pages 195-195
Urban Growth Modeling Using the Bayesian Probability Function....Pages 197-214
Land Suitability Assessment Using a Fuzzy Multi-Criteria Evaluation....Pages 215-235
Neighborhood Interaction in Urban Land-Use Changes Using Cellular Automata-Based Geo-Simulation....Pages 237-251
Web-Based Interactive Walkability Measurement Using Remote Sensing and Geographical Information Systems....Pages 253-272
Watershed Evaluation Using Geospatial Techniques....Pages 273-285
Back Matter....Pages 287-291

---

This book examines current trends and developments in the methods and applications of geospatial analysis and highlights future development prospects. It provides a comprehensive discussion of remote sensing- and geographical information system (GIS)-based data processing techniques, current practices, theories, models, and applications of geospatial analysis. Data acquisition and processing techniques such as remote sensing image selections, classifications, accuracy assessments, models of GIS data, and spatial modeling processes are the focus of the first part of the book. In the second part, theories and methods related to fuzzy sets, spatial weights and prominence, geographically weighted regression, weight of evidence, Markov-cellular automata, artificial neural network, agent-based simulation, multi-criteria evaluation, analytic hierarchy process, and a GIS network model are included. Part three presents selected best practices in geospatial analysis. The chapters, all by expert authors, are arranged so that readers who are new to the field will gain an overview and important insights. Those readers who are already practitioners will gain from the advanced and updated materials and state-of-the-art developments in geospatial analysis.
Content:
Front Matter....Pages i-xii
Introduction: Geospatial Analysis....Pages 1-9
Front Matter....Pages 11-11
Multispectral Classification of Remote Sensing Data for Geospatial Analysis....Pages 13-28
Data Collection, Processing, and Applications for Geospatial Analysis....Pages 29-48
Front Matter....Pages 49-49
Fuzzy Set Theory in Geospatial Analysis....Pages 51-71
Spatial Prominence and Spatial Weights Matrix in Geospatial Analysis....Pages 73-84
Geographically Weighted Regression in Geospatial Analysis....Pages 85-96
Weight of Evidence in Geospatial Analysis....Pages 97-106
Markov–Cellular Automata in Geospatial Analysis....Pages 107-124
Multi-layer Perceptron Neural Networks in Geospatial Analysis....Pages 125-141
Agent-Based Simulation in Geospatial Analysis....Pages 143-156
Analytic Hierarchy Process in Geospatial Analysis....Pages 157-181
GIS Network Model in Geospatial Analysis....Pages 183-194
Front Matter....Pages 195-195
Urban Growth Modeling Using the Bayesian Probability Function....Pages 197-214
Land Suitability Assessment Using a Fuzzy Multi-Criteria Evaluation....Pages 215-235
Neighborhood Interaction in Urban Land-Use Changes Using Cellular Automata-Based Geo-Simulation....Pages 237-251
Web-Based Interactive Walkability Measurement Using Remote Sensing and Geographical Information Systems....Pages 253-272
Watershed Evaluation Using Geospatial Techniques....Pages 273-285
Back Matter....Pages 287-291
....