Environmental Soil-Landscape Modeling: Geographic Information Technologies and Pedometrics (Books in Soils, Plants, and the Environment)

Front cover......Page 1
Foreword......Page 14
The Editor......Page 16
Contributors......Page 18
Contents......Page 20
History and Trends in Soil-Landscape Modeling......Page 22
What Do We Really Know about the Space-Time Continuum of Soil-Landscapes?......Page 24
1.1 Introduction......Page 25
1.2 Philosophical Perspectives of Soil-landscapes......Page 26
1.3 What Are Soils, Landscapes, and Soil- landscapes?......Page 27
1.4.1 Crisp Soil Map Unit Model......Page 28
1.4.3 Two-Dimensional vs. Three-Dimensional Geographic Space......Page 30
1.5 Attribute Space......Page 31
1.6 Pedometrics......Page 35
1.6.1 Jenny’s Soil Factorial Model......Page 37
1.6.2 Catena Model......Page 39
1.6.3 Prediction of a Soil Attribute from Other Soil Attributes......Page 40
1.6.4 Soil Classification Models......Page 41
1.6.5 Geospatial Models......Page 43
1.6.6 Multivariate Geospatial Models......Page 45
1.6.7 Space-Time Models......Page 47
1.7 Critical Remarks......Page 50
References......Page 52
Soil Survey and Soil Classification......Page 58
2.1 Introduction......Page 59
2.1.3 Major Dilemmas......Page 60
2.2.1 Landscape Distribution......Page 62
2.2.3 Descriptions of Major Soils......Page 63
2.2.5 Descriptive Soil-Landscape Models......Page 64
2.2.7 Soil Survey Maps......Page 65
2.2.8 Generalized Soil Maps......Page 66
2.2.9 Special Soil Resource Inventories......Page 67
2.3 Soil Classification......Page 68
2.3.3 Importance of Soil Series......Page 69
2.3.5 Diagnostic Horizons and Features......Page 70
2.4.2 Databases......Page 71
2.4.4 Correlation......Page 72
2.4.6 Map Units Test Models......Page 73
2.5.1 Search for Unifying Concepts......Page 74
2.5.4 Landscapes of Soil Series......Page 75
2.5.7 Criteria Definitions......Page 76
2.5.10 Soil-Landscape Anthology......Page 77
References......Page 78
A Historical Perspective on Soil-Landscape Modeling......Page 82
3.1 Introduction......Page 83
3.2.1 Geologic Understandings of Soil-Geology Relationships......Page 85
3.2.2 The Use of Geology in the U.S. National Cooperative Soil Survey......Page 88
3.2.3 Soil Survey of Southeastern England......Page 90
3.3 von Humboldt, Dokuchaev, and Soil Geography......Page 91
3.3.1 Humboldt and Russian Soil Geography......Page 92
3.3.2 Other Geographic Influences in Pedology......Page 95
3.3.3 Russian Soil Mapping Techniques, circa 1900......Page 96
3.3.4 Use of the Factorial Approach in the NCSS (U.S.)......Page 97
3.4.1 The Origin and Definition of the Catena Concept......Page 98
3.4.2 Challenging the Zonal Soils Tradition......Page 101
3.4.3 Catena Concept vs. Soil Association......Page 104
3.4.4 Applications of the Catena Concept (or Association)......Page 106
3.5.1 The Roots of Late-19th-Century Morphology......Page 108
3.5.2 Marbut’s Soil Anatomy......Page 109
3.5.3 Marbut’s Reign, 1913-1933......Page 111
3.5.4 Three-Dimensional Soil Bodies......Page 112
3.6 The Introduction of Aerial Photography, 1927-1952......Page 113
3.7.1 Historical Summary......Page 115
3.7.2 Contemporary Relevance......Page 117
References......Page 118
Abstract......Page 126
4.1 Introduction......Page 127
4.2.1 Soil Formation Concepts and Evolution......Page 128
4.2.2 Factor Models......Page 129
4.3.1 Soil Development Models......Page 131
4.3.2 Mass Balance Modeling......Page 132
4.3.4 Soil-Landscape Modeling......Page 133
4.3.4.1 Hillslope Models......Page 135
4.4 Conclusions......Page 139
References......Page 140
Collection of Soil-Landscape Datasets......Page 146
The Impact of Emerging Geographic Information Technology on Soil-Landscape Modeling......Page 148
5.1.1 Soil Mapping Technologies......Page 149
5.1.2 Soil Mapping Paradigms......Page 150
5.1.3 Data Management......Page 152
5.2.1 Global Positioning Systems......Page 154
5.2.2.1 Electromagnetic Induction......Page 155
5.2.2.2 Ground-Penetrating Radar......Page 156
5.2.3.1 Soil Sensors......Page 157
5.2.3.2 Soil Spectroscopy......Page 159
5.2.3.3 Remote Sensors......Page 161
5.3.1 Geographic Information Systems......Page 162
5.3.2 Soil Information Systems......Page 166
5.4 Significance for Future Soil-Landscape Modeling......Page 168
References......Page 169
Topographic Mapping......Page 176
6.1 What Are Topographic Maps?......Page 177
6.1.1 National Topographic Mapping Efforts......Page 178
6.2.1.1 Plane Table Surveying......Page 181
6.2.1.2 Ground Surveying......Page 182
6.2.2 Topographic Relief Representation......Page 183
6.2.2.1 Digital Elevation and Digital Terrain Models......Page 184
6.2.2.2 Triangulated Irregular Networks......Page 185
6.2.3 Photogrammetry......Page 186
6.2.3.1 Geometry of Photogrammetric Topographic Mapping......Page 187
6.2.3.3 Aerial Triangulation......Page 188
6.2.3.5 Analog Aerial Photogrammetry......Page 189
6.2.3.6 Digital Photogrammetry......Page 190
6.2.3.7 Digital Photogrammetric Workstations......Page 191
6.2.3.8 Aerial Digital Cameras......Page 192
6.2.3.9 Light Detection and Ranging (Lidar)......Page 193
6.2.3.10 Radio Detection and Ranging (Radar)......Page 197
6.2.3.11 The Space Shuttle Radar Topographic Mapping Experiment......Page 198
6.3.1 Map Compilation......Page 199
6.3.3 Map Accuracy Standards......Page 200
6.4 Summary and Conclusion......Page 201
Books......Page 202
Miscellaneous......Page 203
Pedometrics......Page 204
Abstract......Page 206
7.1 Basic Concepts: Digital Terrain Modeling......Page 207
7.2 Soil-Terrain Modeling......Page 209
7.3.1 Introduction......Page 218
7.3.2 Example......Page 219
7.4.1 Introduction......Page 223
7.4.2 Example......Page 224
References......Page 229
Fuzzy Logic Models......Page 236
8.2.1 Set and Crisp Set......Page 237
8.2.2.1 Definition 1: Fuzzy Set5......Page 238
8.2.3.3 Definition 4: Complement......Page 241
8.3 Soil as a Continuum and Presentation of Soils under Boolean Logic......Page 242
8.4.1 Fuzzy Representation of Soils......Page 244
8.4.2.1 Definition of Class Centroid......Page 246
8.4.2.2 Membership in Classes: Membership Functions......Page 248
8.4.2.3 Fuzzy Membership Maps......Page 250
8.4.3 Use of Fuzzy Membership......Page 251
8.5.1 Limitations of the Conventional Approach to Soil Survey......Page 253
8.5.3 Populating the Similarity Model......Page 255
8.6 Challenges and Future Directions......Page 257
References......Page 259
Modeling Spatial Variation of Soil as Random Functions......Page 262
9.1 Introduction......Page 263
9.2 Soil Classification......Page 264
9.2.1 Sampling and Estimation......Page 265
9.3.1 Random Variables and Random Functions......Page 266
9.3.2 Stationarity......Page 267
9.3.3 Intrinsic Variation and the Variogram......Page 268
9.3.4 Estimating the Variogram......Page 269
9.3.5 Models for Variograms......Page 270
9.3.5.1 Circular......Page 271
9.3.5.3 Pentaspherical......Page 272
9.3.5.6 Unbounded Models......Page 273
9.3.5.7 Anisotropy......Page 274
9.3.6 Combining Trend and Random Fluctuation......Page 275
9.3.7.1 Complexity......Page 277
9.4 Combining Classification with Geostatistics......Page 278
9.5 Simultaneous Variation in Two or More Variables......Page 279
9.5.1 Modeling the Cross-Variogram......Page 281
9.6 Kriging: Implementing the Geostatistical Model......Page 282
9.6.1 Weights......Page 286
9.7 Factorial Kriging Analysis......Page 287
9.8 Case Study: Soil Variation at Yattendon......Page 290
9.10 Modeling the Variogram and Cross-Validation......Page 291
9.11 Kriging......Page 297
9.11.1 Examples of Trend......Page 301
9.12 Coregionalization......Page 305
9.13 Conclusion......Page 306
References......Page 307
Stochastic Simulation of Soil Variations......Page 310
10.1 Introduction and Definitions......Page 311
10.1.2 Importance of the Spatial Distribution......Page 313
10.1.4 Outline of the Chapter......Page 315
10.2.1 Gaussian Transformation......Page 316
10.2.2 Sequential Gaussian Simulation......Page 317
10.2.3 Conditioning by Kriging......Page 318
10.2.4 Turning Bands......Page 319
10.2.5.3 Simulation with a Change of Support......Page 321
10.2.5.4 Intrinsic Random Functions with an Unbounded Variogram......Page 322
10.2.5.5 Multivariate Simulations......Page 323
10.3 Simulation of a Categorical Variable......Page 324
10.3.1.1 Simulation of a Single Indicator Variable......Page 326
10.3.2 Truncated Gaussian Simulation......Page 327
10.3.3 Object-Based Simulation: Boolean Models......Page 328
10.3.3.1 Poisson Point Process......Page 329
10.3.3.2 Boolean Random Set......Page 330
10.3.3.4 Extensions......Page 331
10.4.1 Introduction......Page 332
10.4.2 Gaussian Transformation......Page 336
10.4.3 Conditional Cosimulation......Page 337
10.4.4 Results......Page 339
References......Page 340
Abstract......Page 344
11.1 Introduction......Page 345
11.2 Characterizing Soil Texture Variability from within Field to a Regional Scale......Page 346
11.3.2 Study Area......Page 350
11.3.3 Dataset, Stratification, and Variograms......Page 351
11.3.4.1 Ordinary Kriging......Page 352
11.3.4.2 Ordinary Kriging with Integrated Properties of Map Delineations......Page 354
11.3.4.3 Compositional Ordinary Kriging......Page 355
11.3.4.4 Results......Page 356
11.3.4.5 Sensitivity Analysis of Soil Texture Classification......Page 358
11.4 Conclusions......Page 360
References......Page 361
Abstract......Page 364
12.1 Introduction......Page 365
12.2.1 General Principles......Page 367
12.2.2 The Discrete Wavelet Transform......Page 370
12.2.3 Multiresolution Analysis......Page 372
12.3.1 Wavelet Variance and Change Detection......Page 373
12.3.2 Wavelet Covariance and Change Detection......Page 375
12.4.1 The Data......Page 377
12.4.2 Multiresolution Analysis......Page 380
12.4.3 Uniformity of the Variance......Page 382
12.4.4 Covariation with Soil Carbon Content......Page 386
12.5 Conclusions......Page 389
References......Page 390
Three-Dimensional Reconstruction and Scientific Visualization of Soil-Landscapes......Page 394
13.1 Introduction......Page 395
13.2 Space and Time Concepts......Page 399
13.3 Reconstruction and Scientific Visualization......Page 401
13.4.1.2 Logical and Representation Universe......Page 403
13.4.1.4 Cognitive Universe......Page 404
13.4.2.3 Implementation Universe......Page 406
13.4.3.2 Logical and Representation Universe......Page 407
13.4.3.3 Implementation Universe......Page 408
13.5 Final Remarks......Page 409
References......Page 410
Abstract......Page 414
14.1 Introduction......Page 415
14.2 Multiresolution Tree-Structured Spatial Linear Model......Page 418
14.2.2 The Local Variation......Page 419
14.2.4 Statistical Inference......Page 421
14.2.5 Model Selection and Evaluation......Page 422
14.3 Materials and Methods......Page 423
14.4.1 Exploratory Data Analysis......Page 425
14.4.2 Model Selection and Parameter Estimation......Page 426
14.4.3 Model Comparisons......Page 429
14.4.4 Prediction of Soil Properties......Page 434
Acknowledgments......Page 436
References......Page 437
Abstract......Page 438
15.2 The Historical Importance of the Landscape in Soil Science and Modeling......Page 439
15.2.1 Soil-Landscape Modeling and Scale Issues......Page 441
15.2.2 The Fifth Dimension and Sustainability......Page 444
15.3.1 Case Study Area for the Modeling Example......Page 445
15.3.3 Parameters and Assumptions......Page 446
15.4 Results and Discussion......Page 447
15.4.1 Spatial Patterns and Scale Effects......Page 448
15.4.2 Scale Effects and Temporal Extension......Page 451
15.5 Conclusions......Page 452
References......Page 453
Abstract......Page 458
16.2 Characterizing Space-Time Variability......Page 459
16.2.1 Decomposition of the Space-Time Signal into a Drift and Stochastic Residual......Page 460
16.2.2.1 Product-Sum Model......Page 461
16.2.3 Space-Time Kriging......Page 462
16.3 Space-Time Interpolation of Soil Water Content in a Grassland Plot in Molenschot, The Netherlands......Page 463
16.3.1 Space-Time Variography......Page 465
16.3.2 Space-Time Kriging......Page 468
16.4 Discussion and Conclusions......Page 469
References......Page 471
Index......Page 474