Integration of GIS and remote sensing / edited by Victor Mesev.

Format:

Book

Contributor:

Mesev, Victor.

Series:

Mastering GIS

Language:

English

Subjects (All):

Geographic information systems.

Remote sensing.

Physical Description:

xvi, 296 pages : illustrations ; 24 cm.

Place of Publication:

Chichester, England ; Hoboken, NJ : Wiley, [2007]

Summary:

Integration of GIS and Remote Sensing explores the tremendous potential that lies along the interface between GIS and remote sensing for activating interoperable databases and instigating information interchange. It concentrates on the rigorous and meticulous aspects of analytical data matching and thematic compatibility - the true roots of all branches of GIS/remote sensing applications. However, closer harmonization is tempered by numerous technical and institutional issues, including scale incompatibility, measurement disparities, and the inescapable notion that data from GIS and remote sensing essentially represent diametrically opposing conceptual views of reality.

The first part of the book defines and characterizes GIS and remote sensing and presents the reader with an awareness of the many scale, taxonomical and analytical problems when attempting integration. The second part of the book moves on to demonstrate the benefits and costs of integration across a number of human and environmental applications.

This book will be an invaluable reference for students and professionals dealing not only with GIS and remote sensing, but also computer science, civil engineering, environmental science and urban planning within the academic, governmental and commercial/business sectors.

Contents:

1 GIS and remote sensing integration: in search of a definition / Victor Mesev, Alexandra Walrath 1

1.2 In search of a definition 2

1.2.1 Evolutionary integration 4

1.2.2 Methodological integration 5

2 Integration taxonomy and uncertainty / Manfred Ehlers 17

2.2 Taxonomy issues 19

2.2.1 Taxonomy of GIS operators 19

2.2.2 Taxonomy of image analysis operators in remote sensing 20

2.2.3 An integrated taxonomy 20

2.3 Uncertainty issues 22

2.3.1 Uncertainty in geographic information 22

2.3.2 Uncertainty in the integration of GIS and remote sensing 23

2.4 Modelling positional and thematic error in the integration of remote sensing and GIS 27

2.4.1 Positional and thematic uncertainties 27

2.4.2 Problem formulation 28

2.4.3 Modelling positional uncertainty 29

2.4.4 Thematic uncertainties of a classified image 34

2.4.5 Modelling the combined positional and thematic uncertainties 35

3 Data fusion related to GIS and remote sensing / Paolo Gamba, Fabio Dell'Acqua 43

3.2 Why do we need GIS-remote sensing fusion? 43

3.2.1 Remote sensing output to GIS 44

3.2.2 GIS input to remote sensing interpretation algorithms 45

3.2.3 Example: urban planning check and update 46

3.3 Problems in GIS-remote sensing data fusion 47

3.3.1 Lack of consistent standards 48

3.3.2 Inconsistency of GIS-remote sensing accuracy, legends and scales 49

3.3.3 Different nature of the two sources 51

3.3.4 Need for information rather than data fusion 53

3.3.5 Example: population mapping through remote sensing 54

3.4 Present and future solutions 55

3.4.1 Multiscale analysis 55

3.4.2 Fusion techniques 57

3.5.1 Integration of remote sensing and GIS into a change detection module 61

4 The importance of scale in remote sensing and GIS and its implications for data integration / Peter M. Atkinson 69

4.2 Data models and scales of measurement 70

4.2.1 Raster imagery 70

4.2.2 Vector data 74

4.3 Scales of spatial variation 75

4.3.1 Spatial variation in raster data 75

4.3.2 Scales of variation in vector data 79

4.3.3 Processes in the environment 79

4.4 Remote sensing and GIS data integration 80

4.4.1 Overlay and regression 80

4.4.2 Remote sensing classification of land cover 84

5 Of patterns and processes: spatial metrics and geostatistics in urban analysis / XiaoHang Liu, Martin Herold 93

5.2 Geostatistics 95

5.3 Spatial metrics 96

5.4.1 Data preparation 100

5.4.2 Linkage from land cover to land use 103

5.4.3 Linking urban form to population density 107

5.4.5 Linking characteristics of spatial patterns and processes 109

6 Using remote sensing and GIS integration to identify spatial characteristics of sprawl at the building-unit level / John Hasse 117

6.2 Sprawl in the remote sensing and GIS literature 118

6.2.1 Definitions of sprawl 119

6.2.2 Spatial characteristics of sprawl at a metropolitan level 122

6.2.3 Spatial characteristics of sprawl at a submetropolitan level 125

6.3 Integrating remote sensing and GIS for sprawl research 127

6.4 Spatial characteristics of sprawl at a building-unit level 133

6.5 A practical building-unit level model for analysing sprawl 135

6.5.1 Urban density 138

6.5.2 Leapfrog 138

6.5.3 Segregated land use 140

6.5.4 Highway strip 141

6.5.5 Community node inaccessibility 141

6.5.6 Normalizing municipal sprawl indicator measures 142

6.6 Future benefits of integrating remote sensing and GIS in sprawl research 143

7 Remote sensing applications in urban socio-economic analysis / Changshan Wu 149

7.2 Principles of urban socio-economic studies using remote sensing technologies 150

7.3 Socio-economic information estimation 153

7.3.1 Population estimation 153

7.3.2 Employment estimation 155

7.3.3 GDP estimation 155

7.3.4 Electrical power consumption estimation 156

7.4 Socio-economic activity modelling 157

7.4.1 Population interpolation 157

7.4.2 Socio-economic index generation 158

7.4.3 Understanding and modelling socio-economic phenomena 159

7.5 Advantages and limitations of remote sensing technologies in socioeconomic applications 167

7.5.1 Socio-economic information estimation 167

7.5.2 Socio-economic information modelling 168

8 Integrating remote sensing, GIS and spatial modelling for sustainable urban growth management / Xiaojun Yang 173

8.2 Research methodology 175

8.2.1 Study area 176

8.2.2 Data acquisition and collection 176

8.2.3 Satellite image processing 178

8.2.4 Change analysis 180

8.2.5 Spatial statistical analysis 181

8.2.6 Dynamic spatial modelling 182

8.3 Results and discussion 184

8.3.1 Urban growth 184

8.3.2 Driving force 187

8.3.3 Future growth scenario simulation 191

9 An integrative GIS and remote sensing model for place-based urban vulnerability analysis / Tarek Rashed, John Weeks, Helen Couclelis, Martin Herold 199

9.2 Analysis of urban vulnerability: what is it all about? 201

9.3 A conceptual framework for place-based analysis of urban vulnerability 202

9.4 Integrating GIS and remote sensing into vulnerability analysis 205

9.5 A GIS-remote sensing place-based model for urban vulnerability analysis 206

9.6 An illustrative example of model application 208

9.6.1 Study area 209

9.6.2 Data 209

9.6.3 Identifying vulnerability hot spots 210

9.6.4 Deriving remote sensing measures of urban morphology in Los Angeles 212

9.6.5 Deriving an index of wealth for Los Angeles County 216

9.6.6 Spatial filtering of variables 217

9.6.7 Generating place-based knowledge of urban vulnerability in Los Angeles 218

9.6.8 To what extent do model results conform to universal knowledge of vulnerability? 222

10 Using GIS and remote sensing for ecological mapping and monitoring / Jennifer A. Miller, John Rogan 233

10.2 Integration of GIS and remote sensing in ecological research 237

10.3 GIS data used in ecological applications 237

10.3.1 Gradient analysis 238

10.3.2 Climate 240

10.3.3 Topography 241

10.4 Remotely sensed data for ecological applications 242

10.4.1 Spectral enhancements 243

10.4.2 Land cover 244

10.4.3 Habitat structure 245

10.4.4 Biophysical processes 246

10.5 Species distribution models 247

10.5.1 Biodiversity mapping 251

10.6 Change detection 253

10.6.1 Case study: using GIS and remote sensing for large-area change detection and efficient map updating 253

11 Remote sensing and GIS for ephemeral wetland monitoring and sustainability in southern Mauritania / Tara Shine, Victor Mesev 269

11.1.1 Ephemeral wetlands 269

11.1.2 Remote sensing of ephemeral wetlands 270

11.2 Ephemeral wetlands in Mauritania 272

11.2.1 Data and processing 274

11.2.2 Results 279

11.2.3 Implications for management 283.

Notes:

Includes bibliographical references and index.

ISBN:

0470864095

9780470864098

0470864109

9780470864104

OCLC:

76935862

Online:

Publisher description