Series Foreword ................................................ xi
Preface ...................................................... xiii
List of Contributors ........................................... xv
1 GIS and remote sensing integration: in search of a
definition ................................................... 1
Victor Mesev and Alexandra Watrath
1.1 Introduction ............................................ 1
1.2 In search of a definition ............................... 2
1.2.1 Evolutionary integration ......................... 4
1.2.2 Methodological integration ....................... 5
1.3 Outline of the book ..................................... 8
1.4 Conclusions ............................................ 13
2 Integration taxonomy and uncertainty ........................ 17
Manfred Ehlers
2.1 Introduction ........................................... 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
2.5 Conclusions ............................................ 38
3 Data fusion related to GIS and remote sensing ............... 43
Paolo Gamba and Fabio Delt'Acqua
3.1 Introduction ........................................... 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 Conclusions ............................................ 60
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 ........................... 69
Peter M. Atkinson
4.1 Introduction ........................................... 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
4.5 Conclusion ............................................. 87
5 Of patterns and processes: spatial metrics and
geostatistics in urban analysis ............................. 93
XiaoHang Liu and Martin Herold
5.1 Introduction ........................................... 93
5.2 Geostatistics .......................................... 95
5.3 Spatial metrics ........................................ 96
5.4 Examples .............................................. 100
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
5.5 Conclusion ............................................ 112
6 Using remote sensing and GIS integration to identify
spatial characteristics of sprawl at the building-unit
level ...................................................... 117
John Hasse
6.1 Introduction .......................................... 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 ................................................... 149
Changshan Wu
7.1 Introduction .......................................... 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
7.6 Conclusions ........................................... 168
8 Integrating remote sensing, GIS and spatial modelling for
sustainable urban growth management ........................ 173
Xiaojun Yang
8.1 Introduction .......................................... 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
8.4 Conclusions ........................................... 193
9 An integrative GIS and remote sensing model for - place-
based urban vulnerability analysis ......................... 199
Torek Rashed, John Weeks, Helen Coudelis and Martin
Herold
9.1 Introduction .......................................... 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
9.7 Conclusions ........................................... 224
10 Using GIS and remote sensing for ecological mapping and
monitoring ................................................. 233
Jennifer A. Miller and John Rogan
10.1 Introduction .......................................... 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 Вiophysical 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
10.7 Conclusions ........................................... 260
11 Remote sensing and GIS for ephemeral wetland monitoring
and sustainability in southern Mauritania .................. 269
Тага Shine and Victor Mesev
11.1 Introduction .......................................... 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
11.3 Conclusions .......................................... 284
Index ......................................................... 291
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