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Digital Terrain Analysis, Third Edition
- 3rd Edition - January 1, 2025
- Author: Igor Florinsky
- Language: English
- Hardback ISBN:9 7 8 - 0 - 4 4 3 - 2 4 7 9 8 - 9
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 4 7 9 9 - 6
Digital Terrain Analysis, Third Edition synthesizes knowledge on methods and applications of digital terrain analysis and geomorphometry in the context of multi-scale proble… Read more
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Request a sales quoteDigital Terrain Analysis, Third Edition synthesizes knowledge on methods and applications of digital terrain analysis and geomorphometry in the context of multi-scale problems in soil science, geology, and polar research. Divided into four parts, the book examines the main concepts, principles, and methods of digital terrain modeling, methods for analysis, modeling, and mapping of spatial distribution of soil properties, techniques for recognition, analysis, and interpretation of topographically manifested geological features, and finally, polar research. This new release provides a theoretical and methodological basis for understanding and applying geographical modeling techniques.
- Presents an integrated and unified view of digital terrain analysis in both soil science and geology
- Includes a rigorous description of the mathematical principles of digital terrain analysis
- Provides both a theoretical and methodological basis for understanding and applying geographical modeling
- Contain a new section on Digital Terrain Modeling in polar research, as well as updated information, methods, and figures from previous editions
Researchers and advances students in geomorphometry, geoinformatics, geomorphology, soil science, geology, polar science, and glaciology
1 Digital terrain analysis: past and present
1.1 Why topography?
1.2 A short historical overview
1.3 Current advances in digital terrain analysis
Part I: Principles and Methods of Digital Terrain Modeling
2 Topographic surface and its characterization
2.1 Topographic surface
2.2 Local morphometric variables
2.3 Nonlocal morphometric variables
2.4 Structural morphometric variables
2.5 Two-field specific morphometric variables
2.6 Combined morphometric variables
2.7 Landform classifications
3 Digital elevation models
3.1 DEM generation
3.2 DEM grids
3.3 DEM resolution
3.4 DEM interpolation
4 Calculation methods
4.1 The Evans–Young method
4.2 Calculation of local morphometric variables on a plane square grid
4.3 Calculation of local morphometric variables on a spheroidal equal angular grid on a sphere and an ellipsoid of revolution
4.4 Calculation of nonlocal morphometric variables
4.5 Calculation of structural morphometric variables
4.6 Calculation of two-field specific morphometric variables
4.7 Calculation of combined morphometric variables
4.8 Calculation of landform classifications
4.9 Calculations on a triaxial ellipsoid
5 Errors and accuracy
5.1 Sources of DEM errors
5.2 Estimation of DEM accuracy
5.3 Calculation accuracy of local morphometric variables
5.4 Ignoring of the sampling theorem
5.5 The Gibbs phenomenon
5.6 Grid displacement
5.7 Linear artifacts
6 Filtering
6.1 Tasks of DTM filtering
6.2 Methods of DTM filtering
6.3 Two-dimensional singular spectrum analysis
7 Universal spectral analytical modeling
7.1 Motivation
7.2 Method
7.3 Algorithm
7.4 Materials and data processing
7.5 Results and discussion
8 Mapping and visualization
8.1 Peculiarities of morphometric mapping
8.2 Combined visualization of morphometric variables
8.3 Combining hill-shaded maps with soil and geological data
8.4 Cross sections
8.5 Three-dimensional modeling
8.6 Virtual globes
Part II: Digital Terrain Modeling in Soil Science
9 Influence of topography on soil properties
9.1 Introduction
9.2 Local morphometric variables and soil
9.3 Nonlocal morphometric variables and soil
9.4 Discussion
10 Adequate resolution of models
10.1 Motivation
10.2 Theory
10.3 Field Study
11 Predictive soil mapping
11.1 The Dokuchaev hypothesis as a central idea of soil predictions
11.2 Early models
11.3 Current predictive methods
11.4 Topographic multivariable approach
12 Analyzing relationships in the topography–soil system
12.1 Motivation
12.2 Study sites
12.3 Materials and methods
12.4 Results and discussion
Part III: Digital Terrain Modeling in Geology
13 Folds and folding
13.1 Introduction
13.2 Fold geometry and fold classification
13.3 Predicting the degree of fold deformation and fracturing
13.4 Folding models and the Theorema Egregium
14 Lineaments and faults
14.1 Motivation
14.2 Theory
14.3 Method validation
14.4 Two case studies
15 Accumulation zones and fault intersections
15.1 Motivation
15.2 Study area
15.3 Materials and methods
15.4 Results and discussion
16 Global topography and tectonic structures
16.1 Motivation
16.2 Materials and data processing
16.3 Results and discussion
Part IV: Digital Terrain Modeling in Glaciology and Polar Research
17 Glacier motion and evolution
17.1 Introduction
17.2 Glacier mass balance
17.3 Ice flow velocity
17.4 Glacier force balance
18 Crevasses
18.1 Motivation
18.2 Study area
18.3 Materials and methods
18.4 Results and discussion
19 Catastrophic glacier events
19.1 Motivation
19.2 Study area
19.3 Materials and methods
19.4 Results and interpretation
20 Antarctic oases
20.1 Motivation
20.2 Study area
20.3 Materials and data processing
20.4 Results
20.5 Discussion
21 Concluding remarks and pending problems
21.1 Geomorphometry today
21.2 Theory
21.3 Data processing
21.4 Applications
1.1 Why topography?
1.2 A short historical overview
1.3 Current advances in digital terrain analysis
Part I: Principles and Methods of Digital Terrain Modeling
2 Topographic surface and its characterization
2.1 Topographic surface
2.2 Local morphometric variables
2.3 Nonlocal morphometric variables
2.4 Structural morphometric variables
2.5 Two-field specific morphometric variables
2.6 Combined morphometric variables
2.7 Landform classifications
3 Digital elevation models
3.1 DEM generation
3.2 DEM grids
3.3 DEM resolution
3.4 DEM interpolation
4 Calculation methods
4.1 The Evans–Young method
4.2 Calculation of local morphometric variables on a plane square grid
4.3 Calculation of local morphometric variables on a spheroidal equal angular grid on a sphere and an ellipsoid of revolution
4.4 Calculation of nonlocal morphometric variables
4.5 Calculation of structural morphometric variables
4.6 Calculation of two-field specific morphometric variables
4.7 Calculation of combined morphometric variables
4.8 Calculation of landform classifications
4.9 Calculations on a triaxial ellipsoid
5 Errors and accuracy
5.1 Sources of DEM errors
5.2 Estimation of DEM accuracy
5.3 Calculation accuracy of local morphometric variables
5.4 Ignoring of the sampling theorem
5.5 The Gibbs phenomenon
5.6 Grid displacement
5.7 Linear artifacts
6 Filtering
6.1 Tasks of DTM filtering
6.2 Methods of DTM filtering
6.3 Two-dimensional singular spectrum analysis
7 Universal spectral analytical modeling
7.1 Motivation
7.2 Method
7.3 Algorithm
7.4 Materials and data processing
7.5 Results and discussion
8 Mapping and visualization
8.1 Peculiarities of morphometric mapping
8.2 Combined visualization of morphometric variables
8.3 Combining hill-shaded maps with soil and geological data
8.4 Cross sections
8.5 Three-dimensional modeling
8.6 Virtual globes
Part II: Digital Terrain Modeling in Soil Science
9 Influence of topography on soil properties
9.1 Introduction
9.2 Local morphometric variables and soil
9.3 Nonlocal morphometric variables and soil
9.4 Discussion
10 Adequate resolution of models
10.1 Motivation
10.2 Theory
10.3 Field Study
11 Predictive soil mapping
11.1 The Dokuchaev hypothesis as a central idea of soil predictions
11.2 Early models
11.3 Current predictive methods
11.4 Topographic multivariable approach
12 Analyzing relationships in the topography–soil system
12.1 Motivation
12.2 Study sites
12.3 Materials and methods
12.4 Results and discussion
Part III: Digital Terrain Modeling in Geology
13 Folds and folding
13.1 Introduction
13.2 Fold geometry and fold classification
13.3 Predicting the degree of fold deformation and fracturing
13.4 Folding models and the Theorema Egregium
14 Lineaments and faults
14.1 Motivation
14.2 Theory
14.3 Method validation
14.4 Two case studies
15 Accumulation zones and fault intersections
15.1 Motivation
15.2 Study area
15.3 Materials and methods
15.4 Results and discussion
16 Global topography and tectonic structures
16.1 Motivation
16.2 Materials and data processing
16.3 Results and discussion
Part IV: Digital Terrain Modeling in Glaciology and Polar Research
17 Glacier motion and evolution
17.1 Introduction
17.2 Glacier mass balance
17.3 Ice flow velocity
17.4 Glacier force balance
18 Crevasses
18.1 Motivation
18.2 Study area
18.3 Materials and methods
18.4 Results and discussion
19 Catastrophic glacier events
19.1 Motivation
19.2 Study area
19.3 Materials and methods
19.4 Results and interpretation
20 Antarctic oases
20.1 Motivation
20.2 Study area
20.3 Materials and data processing
20.4 Results
20.5 Discussion
21 Concluding remarks and pending problems
21.1 Geomorphometry today
21.2 Theory
21.3 Data processing
21.4 Applications
- No. of pages: 430
- Language: English
- Edition: 3
- Published: January 1, 2025
- Imprint: Academic Press
- Hardback ISBN: 9780443247989
- eBook ISBN: 9780443247996
IF
Igor Florinsky
Igor Florinsky is a Principal Research Scientist at the Keldysh Institute of Applied Mathematics, Russian Academy of Sciences. He has previously held positions as a Visiting Fellow at the Agriculture and Agri-Food Canada and a Research Scientist at the University of Manitoba in Canada. He is an author, co-author, or editor of over 125 publications including 2 books, 2 edited volumes, 50 papers in peer-reviewed journals, and 13 peer-reviewed book chapters. He is an Editorial Board Member for the journals Chinese Geographical Science, Space and Time, and the International Journal of Ecology and Development. His research interests include digital terrain modeling and geomorphometry, interrelationships between topography, soils, and tectonics, and the influence of the geological environment on humans, society and civilization.
Affiliations and expertise
Principal Research Scientist, Institute of Mathematical Problems of Biology, The Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, Pushchino, Russia