Scale in Spatial Information and Analysis

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Scale in Spatial Information and Analysis

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 367 p.
  • 言語 ENG,ENG
  • 商品コード 9781138075368
  • DDC分類 519

Full Description


Now ubiquitous in modern life, spatial data present great opportunities to transform many of the processes on which we base our everyday lives. However, not only do these data depend on the scale of measurement, but also handling these data (e.g., to make suitable maps) requires that we account for the scale of measurement explicitly. Scale in Spatial Information and Analysis describes the scales of measurement and scales of spatial variation that exist in the measured data. It provides you with a series of tools for handling spatial data while accounting for scale.The authors detail a systematic strategy for handling scale issues from geographic reality, through measurements, to resultant spatial data and their analyses. They also explore a process-pattern paradigm in approaching scale issues. This is well reflected, for example, in chapters dealing with terrain analysis, in which scale in terrain derivatives is described in relation to the processing involved in the derivation of specific terrain variables from elevation data, and area classes, which are viewed as driven by class-forming covariates. Lastly, this book provides coverage of some of the issues related to scale that are relatively under-represented in the literature, such as the effects of scale on information content in remotely sensed images, and the interaction between scale and uncertainty that is increasingly important for spatial information and analysis. By taking a rigorous, scientific approach to scale and its various meanings in relation to the geographic world, the book alleviates some of the frustration caused by dealing with issues of scale. While past research has led to an increasing number of journal articles and a few books dedicated to scale modeling and change of scale, this book helps you to develop coherent strategies for scale modeling, highlighting applicability for a variety of fields, from geomatic engineering and geoinformatics to environmental modeling.

Table of Contents

Preface                                            ix
Acknowledgment xi
Authors xiii
Chapter 1 Introduction 1 (16)
1.1 Issue of Scale 1 (3)
1.2 Models of Scale 4 (5)
1.3 Scaling Up and Down 9 (3)
1.4 Book Chapters 12 (5)
Chapter 2 Geographic Representations 17 (18)
2.1 Geo-Atoms 20 (1)
2.2 Geo-Fields 21 (4)
2.3 Geo-Objects 25 (3)
2.4 Hierarchical Data Structures 28 (3)
2.4.1 Quadtrees 28 (1)
2.4.2 Hierarchical TINs 29 (2)
2.5 Discussion 31 (4)
2.5.1 Geo-Dipoles and Spatial 31 (1)
Interactions
2.5.2 Temporal Dimension 32 (1)
2.5.3 Scale Dependence of 32 (3)
Representations
Chapter 3 Geospatial Measurements 35 (32)
3.1 Framework for Spatial Sampling 36 (11)
3.1.1 Spatial Sampling Design 36 (7)
3.1.2 Data Supports 43 (1)
3.1.3 Spatial Resolution in Remotely 44 (1)
Sensed Images
3.1.3.1 Rayleigh Criterion 45 (1)
3.1.3.2 MTF and Its Equivalent Bandwidth 45 (1)
3.1.3.3 Effective Radiometric 46 (1)
Resolution Element
3.2 Optical Remote Sensing and Resolution 47 (8)
3.2.1 Spatial and Spectral Responses 47 (3)
3.2.2 Geometric Characteristics 50 (5)
3.3 Microwave Remote Sensing and 55 (9)
Resolution
3.3.1 Resolution 55 (3)
3.3.2 Radar Signals, Imaging, and 58 (4)
Distortions
3.3.3 Passive Microwave 62 (2)
3.4 Discussion 64 (3)
Chapter 4 Geostatistical Models of Scale 67 (24)
4.1 Geostatistical Fundamentals and 68 (9)
Variograms
4.1.1 Random Fields 68 (2)
4.1.2 Variograms and Covariance 70 (5)
Functions
4.1.3 Indicator Variograms and 75 (2)
Transition Probability-Based Models
4.2 Variogram Regularization and 77 (5)
Deregularization
4.2.1 Regularization 77 (3)
4.2.2 Deconvolution of Regularized 80 (2)
Variograms
4.3 Statistics for Determining 82 (5)
Measurement Scales
4.4 Discussion 87 (4)
Chapter 5 Lattice Data and Scale Models 91 (16)
5.1 Lattice Data 93 (2)
5.2 Spatial Autocorrelation and Its 95 (4)
Measures
5.3 Local Models 99 (4)
5.4 Discussion 103 (4)
Chapter 6 Geostatistical Methods for Scaling 107 (22)
6.1 Kriging 109 (7)
6.2 Indicator Approaches 116 (2)
6.3 Upscaling by Block Kriging 118 (2)
6.4 Downscaling by Area-to-Point Kriging 120 (4)
6.5 Geostatistical Inverse Modeling 124 (2)
6.6 Discussion 126 (3)
Chapter 7 Methods for Scaling Gridded Data 129 (18)
7.1 Upscaling 131 (6)
7.1.1 Statistical Approaches 131 (3)
7.1.2 Mechanistic Approaches 134 (3)
7.2 Downscaling 137 (8)
7.2.1 Deconvolution 137 (4)
7.2.2 Super-Resolution Mapping 141 (3)
7.2.3 Subpixel Mapping 144 (1)
7.3 Discussion 145 (2)
Chapter 8 Multiscale Data Conflation 147 (22)
8.1 Multivariate Geostatistics 149 (5)
8.2 Image Fusion 154 (9)
8.2.1 Conventional Approaches 154 (1)
8.2.2 Multiresolution Representations 155 (6)
Based on Wavelets
8.2.3 Wavelet-Based Image Fusion 161 (2)
8.3 Other Multiscale Methods 163 (3)
8.4 Discussion 166 (3)
Chapter 9 Scale in Terrain Analysis 169 (32)
9.1 Digital Elevation Data and Their 171 (5)
Scales
9.2 Terrain Derivatives 176 (11)
9.2.1 Slope and Aspect 176 (4)
9.2.2 Curvature 180 (6)
9.2.3 Secondary Properties 186 (1)
9.3 Models of Scale in Topography 187 (6)
9.4 Methods for Scaling Terrain Variables 193 (5)
9.4.1 Upscaling 193 (3)
9.4.2 Downscaling 196 (2)
9.5 Discussion 198 (3)
Chapter 10 Scale in Area-Class Mapping 201 (26)
10.1 Area-Class Mapping 204 (9)
10.1.1 Discriminant-Space Model 204 (5)
10.1.2 Methods for Mapping Area Classes 209 (4)
10.2 Spatial Scales and Patterns in Area 213 (6)
Classes
10.3 Scaling Area-Class Information 219 (4)
10.3.1 Upscaling 219 (1)
10.3.2 Downscaling 220 (3)
10.4 Discussion 223 (4)
Chapter 11 Information Content 227 (38)
11.1 Information Theory 230 (8)
11.2 Information Content in Remotely 238 (12)
Sensed Images
11.2.1 Informational Characteristics of 238 (4)
Images
11.2.2 Information Conveyed in Images 242 (5)
with Additive Noise
11.2.3 Information in Images with 247 (3)
Multiplicative Noise
11.3 Image Resolution and Information 250 (5)
Content
11.3.1 Effects of Resolution on 250 (3)
Information Content
11.3.2 Information Capacity and Super 253 (2)
Resolution
11.4 Information Content in Map Data 255 (6)
11.5 Discussion 261 (4)
Chapter 12 Uncertainty Characterization 265 (34)
12.1 Accuracy Metrics and Assessment 268 (10)
12.1.1 Accuracy in Interval/Ratio Fields 268 (3)
12.1.2 Accuracy in Area Classes 271 (2)
12.1.3 Positional Accuracy 273 (1)
12.1.4 Confidence Intervals and 274 (4)
Hypothesis Testing
12.2 Geostatistical Approaches to 278 (4)
Validation
12.3 Analytical Approaches to Error 282 (5)
Propagation
12.4 Geostatistical Simulation 287 (9)
12.4.1 Simulation over a Point Support 287 (4)
12.4.2 Point-Support Simulation 291 (2)
Conditional to Areal Data
12.4.3 Simulation over Blocks 293 (3)
12.5 Discussion 296 (3)
Epilogue 299 (10)
References 309 (38)
Index 347