Terrain analysis : principles and applications / edited by John P. Wilson, John C. Gallant.

Format:

Book

Contributor:

Wilson, John P. (John Peter), 1955-

Gallant, John C.

Language:

English

Subjects (All):

Landforms--Measurement.

Landforms.

Geomorphology--Technique.

Geomorphology.

Earth science--Remote sensing.

Local Subjects:

Earth science--Remote sensing.

Genre:

Festschriften.

Physical Description:

xxiii, 479 pages, 8 unnumbered pages of plates : illustrations (some color), maps (some color) ; 25 cm

Place of Publication:

New York : Wiley, [2000]

Summary:

Terrain analysis quantifies, as measured by elevation, the influence of a landscape's shape on the processes occurring at the land surface. Information drawn from terrain analysis is useful in such areas as hydrology (including the structure of watersheds and wetlands); studies of soil classification and erosion; geomorphology research; and studies of regional ecology. Television and radio signal propagation, meteorological applications, and military considerations are other areas which make use of terrain analysis data. This important book is the first to describe the applications of GIS to terrain analysis problems, instructing GIS users on how to make optimal use of GIS for a whole range of practical problems.

Contents:

1. Digital Terrain Analysis / John P. Wilson, John C. Gallant 1

1.1 Principles and Applications 1

1.1.1 Digital Elevation Data Sources and Structures 3

1.1.2 Calculation and Use of Topographic Attributes in Hydrological, Geomorphological, and Biological Applications 5

1.1.3 Identification and Treatment of Error and Uncertainty 15

1.2 The Purpose of This Book 20

1.3.1 Digital Terrain Analysis Methods 22

1.3.2 Hydrological Applications 24

1.3.3 Geomorphological Applications 25

1.3.4 Biological Applications 26

2. Digital Elevation Models and Representation of Terrain Shape / Michael F. Hutchinson, John C. Gallant 29

2.2 Sources of Topographic Data 32

2.2.1 Surface-Specific Point Elevation Data 32

2.2.2 Contour and Stream-Line Data 32

2.2.3 Remotely Sensed Elevation Data 33

2.2.4 Scales of Source Topographic Data 34

2.3 DEM Interpolation Methods 34

2.3.1 Triangulation 35

2.3.2 Local Surface Patches 35

2.3.3 Locally Adaptive Gridding 36

2.4 Filtering of Remotely Sensed Gridded DEMs 37

2.5 Quality Assessment of DEMs 38

2.5.1 Spurious Sinks and Drainage Analysis 38

2.5.2 Views of Shaded Relief and Other Terrain Attributes 39

2.5.3 Derived Elevation Contours 39

2.5.4 Frequency Histograms of Primary Terrain Attributes 39

2.6 Optimization of DEM Resolution 39

2.7 Interpolation of the Cottonwood DEM Using ANUDEM 41

2.7.1 Specification of ANUDEM Options 43

2.7.2 Elevation Units and Vertical Precision 43

2.8 Assessment of Resolution and Quality of the Cottonwood DEM 44

2.8.1 Optimization of Resolution Using the Root Mean Square Slope Criterion 44

2.8.2 Comparison of Data Contours With Derived Contours 45

2.8.3 Views of Slope and Profile Curvature 45

2.8.4 Histograms of Elevation and Aspect 46

3. Primary Topographic Attributes / John C. Gallant, John P. Wilson 51

3.1 Tapes-G: Terrain Analysis on Gridded DEMs 51

3.1.1 Surface Derivatives 51

3.1.2 Slope 53

3.1.3 Aspect and Primary Flow Direction 54

3.1.4 Curvature 56

3.1.5 Upslope Contributing Area and Specific Catchment Area 58

3.1.6 Flow Width 69

3.1.7 Maximum Flow-Path Length 70

3.1.8 Downslope Attributes 70

3.1.9 Upslope Averages of Terrain Attributes 71

3.1.10 Other Terrain Attributes 71

3.2 Elevation Residual Analysis 73

3.2.1 Mean Elevation 74

3.2.2 Difference From Mean Elevation 74

3.2.3 Standard Deviation of Elevation 74

3.2.4 Elevation Range 75

3.2.5 Deviation From Mean Elevation 75

3.2.6 Percentile 75

3.2.7 Other Attributes 75

3.2.8 Elevresidgrid Examples 76

3.3 TAPES-C: Terrain Analysis on Contour DEMs 77

3.3.1 Element Construction 79

3.3.2 Computed Terrain Attributes 82

3.3.3 Differences Between TAPES-C and TOPOG Element Networks 83

4. Secondary Topographic Attributes / John P. Wilson, John C. Gallant 87

4.2 EROS 88

4.3 SRAD 91

4.4 WET 106

4.5 DYNWET-G 113

4.6 Sample Application 118

5. Effect of Data Source, Grid Resolution, and Flow-Routing Method on Computed Topographic Attributes / John P. Wilson, Philip L. Repetto, Robert D. Snyder 133

5.2 Squaw Creek, Montana Sensitivity Analysis 135

5.2.2 Results and Discussion 137

5.3 Idaho Farm Field Model Validation Field Experiment 150

6. Spatial Analysis of Soil-Moisture Deficit and Potential Soil Loss in the Elbe River Basin / Valentina Krysanova, Dirk-Ingmar Muller-Wohlfeil, Wolfgang Cramer, Alfred Becker 163

6.2 Freshwater Availability 166

6.2.2 Large-Scale Applications of Topography-Based Models 168

6.2.3 Application in the Elbe Basin 170

6.2.4 Results and Comparisons With Previous Studies 172

6.3 Erosion 177

6.3.1 GIS-Based Approaches for the Analysis of Pollutant Yield in Large Basins 177

7. Mapping Contributing Areas for Stormwater Discharge to Streams Using Terrain Analysis / Jeremy S. Fried, Daniel G. Brown, Mark O. Zweifler, Michael A. Gold 183

7.1.1 Implications of Sediment for Water Quality 185

7.1.2 Sediment Management With Riparian Buffer Strips 185

7.1.3 Hydrological Principles 185

7.2 Description of Study Area 188

7.3.1 GIS Database and Terrain Model Creation 188

7.3.2 Generation of Terrain-Analysis Indices 190

7.3.3 Formulation of Investigative Buffer Model 191

7.3.4 Collection of Validation Data 192

7.4.1 Comparison of Indices 194

7.4.2 Comparison of Variable-Width Investigative Buffers 196

7.4.3 Concordance With Validation Data Set 198

8. Soil-Moisture Modeling in Humid Mountainous Landscapes / J. Alan Yeakley, George M. Hornberger, Wayne T. Swank, Paul V. Bolstad, James M. Vose 205

8.3 Modeling Approach 207

8.3.1 Terrain Analysis 207

8.3.2 Canopy Interception Modeling 210

8.3.3 Hillslope Hydrology Model 210

8.4 Parameterization and Calibration 212

8.4.1 Structural Parameters 212

8.4.2 Above-Ground Parameters 213

8.4.3 Below-Ground Parameters 215

8.4.4 Storm-Scale Calibration 216

8.5 Validation 217

8.5.1 Storm Scale 217

8.5.1.2 Soil-Moisture Response 218

8.5.2 Seasonal Scale 219

8.5.3 Model Comparisons 220

9. Stochastic Analysis of a Coupled Surface/Subsurface Hydrologic Model / Gregory M. Pohll, John J. Warwick 225

9.1.1 Statement of the Problem 225

9.1.2 Review of Existing Coupled Modeling Approaches 226

9.1.3 Stochastic Model 227

9.2 Description of Numerical Models 229

9.2.1 Vadose Zone Model 229

9.2.2 Coupled Surface/Subsurface Model 231

9.2.3 Stochastic Model 235

9.3 Simulation Results 237

9.3.1 Coupled Model Calibration 237

9.3.2 Model Comparison (Vadose Zone Versus Coupled Model) 238

9.3.3 Long-Term Simulation Comparison of Stochastic Structures and the Vadose Zone Model 240

9.4.1 Coupled Surface/Subsurface Model 241

9.4.2 Coupled Surface/Subsurface Model Versus Vadose Zone Model 243

9.4.3 Stochastic Model 244

10. The Role of Terrain Analysis in Soil Mapping / Neil J. McKenzie, Paul E. Gessler, Philip J. Ryan, Deborah O'Connell 245

10.1 The Potential of Terrain Analysis 245

10.2 Theories of Pedogenesis and Modeling for Prediction 246

10.2.1 The Functional Factorial Approach 246

10.2.2 Contemporary Views 247

10.2.3 Environmental Change in Ancient Landscapes 248

10.2.4 The Role of Landform 250

10.3 Examples of the Use of Terrain Analysis in Australian Soil Survey Research 251

10.3.1 Improved Environmental Information 254

10.3.2 Explicit Survey Design 256

10.3.3 Quantitative Spatial Prediction 259

10.4 Factors Affecting the Utility of Terrain Analysis 263

10.4.1 Landscape Complexity 263

10.4.2 Issues of Scale 263

10.4.3 Technology 264

10.4.4 Quantitative Versus Intuitive Mental Models 265

11. Automated Landform Classification Methods for Soil-Landscape Studies / Stephen J. Ventura, Barbara J. Irvin 267

11.2 Role of Landform Classification in Modern Soil Survey and Soil-Landscape Studies 268

11.3 Pleasant Valley Study 274

11.4.1 Calculation of Topographic Attributes From a DEM 277

11.4.2 ISODATA Unsupervised Classification 281

11.4.3 Continuous Classification Overview 282

12. A Soil-Terrain Model for Estimating Spatial Patterns of Soil Organic Carbon / Jay C. Bell, David F. Grigal, Peter C. Bates 295

12.2.2 Field Sampling 298

12.2.3 Laboratory Methods 299

12.2.4 Spatial Data 299

12.2.5 Spatial Modeling 301

12.3 Results and Discussion 302

12.3.1 Mineral Soils 303

12.3.2 Peatlands 304

12.3.3 Estimating Spatial Patterns of SOC 305

13. Shallow Landslide Delineation for Steep Forest Watersheds Based on Topographic Attributes and Probability Analysis / Jinfan Duan, Gordon E.

Grant 311

13.3.1 Infinite Slope Model 316

13.3.2 Parameter Estimation From Probability Analysis 317

13.3.3 Effect of Vegetation 319

13.3.4 Terrain Analysis and Climate Data Acquisition 320

13.3.5 Monte Carlo Simulation and Probability Derivation 323

13.5 Implications for Management and Future Modeling 328

14. Terrain Variables Used for Predictive Mapping of Vegetation Communities in Southern California / Janet Franklin, Paul McCullough, Curtis Gray 331

14.1.1 Species Distributions and Environmental Gradients 332

14.1.2 Ecological Field Data in Geographical Databases 332

14.1.3 Error in Digital Elevation Models 333

14.1.4 Modeling Methods 333

15. Automated Land Cover Mapping Using Landsat Thematic Mapper Images and Topographic Attributes / Jonathan M. Wheatley, John P. Wilson, Roland L. Redmond, Zhenkui Ma, Jeff DiBenedetto 355

15.3.1 Landsat TM Image Classification 362

15.3.2 Digital Elevation Models 363

15.3.3 Terrain Analysis 364

15.3.4 Ground-Truth Data 366

15.3.5 Performance Evaluation 366

15.4.1 Terrain Attribute Maps 367

15.4.2 Land Cover Classification Without Topographic Attributes 370

15.4.3 Adding Topographic Attributes 377

15.4.4 Use of Stream Buffers to Delineate Riparian and Upland Cover Classes 377

15.4.5 Evaluation of Land Cover Maps 381

16. Toward a Spatial Model of Boreal Forest Ecosystems: The Role of Digital Terrain Analysis / Brendan G. Mackey, Ian C. Mullen, Kenneth A. Baldwin, John C. Gallant, Richard A. Sims, Daniel W. McKenney 391

16.1.1 The Niche Hypothesis 392

16.1.2 The Disturbance Hypothesis 393

16.3 Why Digital Terrain Analysis? 396

16.4.1 Ecology of the Target Tree Species 398

16.4.3 Analytical Techniques 403

16.5.1 AMF Analyses 409

16.5.2 Domain Analyses 410

16.6.1 The Domain Hypothesis 420

17. Future Directions for Terrain Analysis / John C. Gallant, Michael F. Hutchinson, John P. Wilson 423

17.3 Knowledge of Relationships 425

17.4 Scaling 426.

Notes:

Includes bibliographical references (pages 429-468) and index.

ISBN:

0471321885

OCLC:

43060654