Remote Sensing and GIS Integration: Theories, Methods, and Applications Theory, Methods, and Applications
, by Weng, Qihao
- ISBN: 9780071606530 | 007160653X
- Cover: Hardcover
- Copyright: 11/9/2009
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.
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).
| 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 |
| Table of Contents provided by Ingram. All Rights Reserved. |
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