Remote Sensing and GIS Integration: Theories, Methods, and Applications Theory, Methods, and Applications

by Weng, Qihao

• ISBN13: 9780071606530
• ISBN10: 007160653X
• Edition: 1st
• Format: Hardcover
• Copyright: 2009-11-09
• Publisher: McGraw-Hill Education

Summary

This book demystifies the subject of remote sensing and GIS integration. Readers can maximize their geographical information tool by incorporating it with up-to-date remotely sensed data.

Author Biography

Dr. Qihao Weng is an associate professor in the Department of Geography, Geology, and Anthropology at Indiana State University. He is a national director of the American Society for Photogrammetry and Remote Sensing (ASPRS).

Table of Contents

Foreword	p. ix
Preface	p. xiii
Acknowledgments	p. xvii
Principles of Remote Sensing and Geographic Information Systems (GIS)	p. 1
Principles of Remote Sensing	p. 1
Concept of Remote Sensing	p. 1
Principles of Electromagnetic Radiation	p. 2
Characteristics of Remotely Sensed Data	p. 5
Remote Sensing Data Interpretation and Analysis	p. 8
Principles of GIS	p. 21
Scope of Geographic Information System and Geographic Information Science	p. 21
Raster GIS and Capabilities	p. 23
Vector GIS and Capabilities	p. 25
Network Data Model	p. 29
Object-Oriented Data Model	p. 30
References	p. 31
Integration of Remote Sensing and Geographic Information Systems (GIS)	p. 43
Methods for the Integration between Remote Sensing and GIS	p. 43
Contributions of Remote Sensing to GIS	p. 44
Contributions of GIS to Remote Sensing	p. 46
Integration of Remote Sensing and GIS for Urban Analysis	p. 49
Theories of the Integration	p. 51
Evolutionary Integration	p. 51
Methodological Integration	p. 52
The Integration Models	p. 53
Impediments to Integration and Probable Solutions	p. 57
Conceptual Impediments and Probable Solutions	p. 57
Technical Impediments and Probable Solutions	p. 61
Prospects for Future Developments	p. 68
Impacts of Computer, Network, and Telecommunications Technologies	p. 68
Impacts of the Availability of Very High Resolution Satellite Imagery and LiDAR Data	p. 71
Impacts of New Image-Analysis Algorithms	p. 73
Conclusions	p. 78
References	p. 78
Urban Land Use and Land Cover Classification	p. 91
Incorporation of Ancillary Data for Improving Image Classification Accuracy	p. 92
Case Study: Landsat Image-Housing Data Integration for LULC Classification in Indianapolis	p. 95
Study Area	p. 95
Datasets Used	p. 96
Methodology	p. 98
Accuracy Assessment	p. 105
Classification Result by Using Housing Data at the Pre-Classification Stage	p. 105
Classification Result by Integrating Housing Data during the Classification	p. 109
Classification Result by Using Housing Data at the Post-Classification Stage	p. 111
Summary	p. 112
References	p. 114
Urban Landscape Characterization and Analysis	p. 117
Urban Landscape Analysis with Remote Sensing	p. 118
Urban Materials, Land Cover, and Land Use	p. 118
The Scale Issue	p. 120
The Image ”Scene Models&Idquo;	p. 121
The Continuum Model of UrbanLandscape	p. 121
Linear Spectral Mixture Analysis (LSMA)	p. 123
Case Study: Urban Landscape Patterns and Dynamics in Indianapolis	p. 125
Image Preprocessing	p. 125
Image Endmember Development	p. 125
Extraction of Impervious Surfaces	p. 127
Image Classification	p. 130
Urban Morphologic Analysis Based on the V-I-S Model	p. 130
Landscape Change and the V-I-S Dynamics	p. 134
Intra-Urban Variations and the V-I-S Compositions	p. 139
Discussion and Conclusions	p. 157
References	p. 160
Urban Feature Extraction	p. 165
Landscape Heterogeneity and Per-Field and Object-Based Image Classifications	p. 166
Case Study: Urban Feature Extraction from High Spatial-Resolution Satellite Imagery	p. 169
Data Used	p. 169
Image Segmentation	p. 169
Rule-Based Classification	p. 170
Post-Classification Refinement and Accuracy Assessment	p. 171
Results of Feature Extraction	p. 173
Discussion	p. 173
Conclusions	p. 178
References	p. 179
Building Extraction from LiDAR Data	p. 183
The LiDAR Technology	p. 185
Building Extraction	p. 186
Case Study	p. 188
Datasets	p. 188
Generation of the Normalized HeightModel	p. 189
Object-Oriented Building Extraction	p. 192
Accuracy Assessment	p. 196
Strategies for Object-Oriented Building Extraction	p. 197
Error Analysis	p. 201
Discussion and Conclusions	p. 205
References	p. 206
Urban Land Surface Temperature Analysis	p. 209
Remote Sensing Analysis of Urban Land Surface Temperatures	p. 210
Case Study: Land-Use Zoning and LST Variations	p. 211
Satellite Image Preprocessing	p. 211
LULC Classification	p. 212
Spectral Mixture Analysis	p. 213
Estimation of LSTs	p. 215
Statistical Analysis	p. 218
Landscape Metrics Computation	p. 219
Factors Contributing to LST Variations	p. 225
General Zoning, Residential Zoning, and LST Variations	p. 234
Seasonal Dynamics of LSTPatterns	p. 237
Discussion and Conclusions: Remote Sensing-GIS Integration in Urban Land-Use Planning	p. 240
References	p. 242
Surface Runoff Modeling and Analysis	p. 247
The Distributed Surface Runoff Modeling	p. 248
Study Area	p. 251
Integrated Remote Sensing-GIS Approach to Surface Runoff Modeling	p. 253
Hydrologic Parameter Determination Using GIS	p. 253
Hydrologic Modeling within the GIS	p. 257
Urban Growth in the Zhujiang Delta	p. 257
Impact of Urban Growth on Surface Runoff	p. 259
Impact of Urban Growth on Rainfall-Runoff Relationship	p. 261
Discussion and Conclusions	p. 263
References	p. 264
Assessing Urban Air Pollution Patterns	p. 267
Relationship between Urban Air Pollution and Land-Use Patterns	p. 268
Case Study: Air Pollution Pattern in Guangzhou, China, 1980-2000	p. 270
Study Area: Guangzhou, China	p. 270
Data Acquisition and Analysis	p. 272
Air Pollution Patterns	p. 275
Urban Land Use and Air Pollution Patterns	p. 283
Urban Thermal Patterns and Air Pollution	p. 288
Summary	p. 291
Remote Sensing-GIS Integration for Studies of Urban Environments	p. 291
References	p. 292
Population Estimation	p. 295
Approaches to Population Estimation with Remote Sensing-GIS Techniques	p. 296
Measurements of Built-Up Areas	p. 296
Counts of Dwelling Units	p. 299
Measurement of Different Land-Use Areas	p. 300
Spectral Radiance	p. 301
Case Study: Population Estimation Using Landsat ETM+Imagery	p. 303
Study Area and Datasets	p. 303
Methods	p. 303
Result of Population Estimation Based on a Non-Stratified Sampling Method	p. 308
Result of Population Estimation Based on Stratified Sampling Method	p. 313
Discussion	p. 320
Conclusions	p. 321
References	p. 322
Quality of Life Assessment	p. 327
Assessing Quality of Life	p. 328
Concept of QOL	p. 328
QOL Domains and Models	p. 329
Application of Remote Sensing and GIS in QOL Studies	p. 330
Case Study: QOL Assessment in Indianapolis with Integration of Remote Sensing and GIS	p. 331
Study Area and Datasets	p. 331
Extraction of Socioeconomic Variables from Census Data	p. 332
Extraction of Environmental Variables	p. 332
Statistical Analysis and Development of a QOL Index	p. 333
Geographic Patterns of Environmental and Socioeconomic Variables	p. 334
Factor Analysis Results	p. 335
Result of Regression Analysis	p. 341
Discussion and Conclusions	p. 342
References	p. 343
Urban and Regional Development	p. 345
Regional LULC Change	p. 345
Definitions of Land Use and Land Cover	p. 346
Dynamics of Land Use and Land Cover and Their Interplay	p. 346
Driving Forces in LULC Change	p. 348
Case Study: Urban Growth and Socioeconomic Development in the Zhujiang Delta, China	p. 350
Urban Growth Analysis	p. 350
Driving Forces Analysis	p. 350
Urban LULC Modeling	p. 351
Urban Growth in the Zhujiang Delta, 1989-1997	p. 352
Urban Growth and Socioeconomic Development	p. 355
Major Types of Urban Expansion	p. 357
Summary	p. 359
Discussion: Integration of Remote Sensing and GIS for Urban Growth Analysis	p. 359
References	p. 360
Public Health Applications	p. 363
WNV Dissemination and Environmental Characteristics	p. 364
Case Study: WNV Dissemination in Indianapolis, 2002-2007	p. 365
Data Collection and Preprocessing	p. 365
Plotting Epidemic Curves	p. 368
Risk Area Estimation	p. 368
Discriminant Analysis	p. 368
Results	p. 369
Discussion and Conclusions	p. 377
References	p. 379
Index	p. 383
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