SUSTAINABLE DEVELOPMENT
Innovate. Sustain. Transform.
Save up to 30% on top Physical Sciences & Engineering titles!
Digital Terrain Analysis, Third Edition
- 3rd Edition - January 10, 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
Purchase options
Institutional subscription on ScienceDirect
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
- Digital Terrain Analysis
- Cover image
- Title page
- Table of Contents
- Copyright
- Preface to the third edition
- Acknowledgments
- Abbreviations and acronyms
- Chapter 1 Digital terrain analysis: Past and present
- Abstract
- Keywords
- 1.1 Why topography?
- 1.2 A short historical overviewa
- 1.3 Current advances in digital terrain analysis
- 1.3.1 Factors in the development of geomorphometry
- 1.3.2 Applications
- References☆
- Part I: Principles and methods of digital terrain modeling
- Chapter 2 Topographic surface and its characterization
- Abstract
- Keywords
- 2.1 Topographic surface
- 2.1.1 Definition and limitations
- 2.1.2 Contour line and special pointsb
- 2.1.3 Morphometric variables and their types
- 2.2 Local morphometric variables
- 2.2.1 Overview
- 2.2.2 Gradientd
- 2.2.3 Aspect
- 2.2.4 Curvatures
- 2.2.5 Deflections
- 2.3 Nonlocal morphometric variables
- 2.3.1 Catchment and dispersive areas
- 2.3.2 Topographic position index
- 2.4 Structural morphometric variables
- 2.5 Two-field-specific morphometric variables
- 2.5.1 Solar morphometric variables
- 2.5.2 Wind morphometric variables
- 2.5.3 View morphometric variables
- 2.6 Combined morphometric variables
- 2.6.1 Local-nonlocal morphometric variables
- 2.6.2 Local-local morphometric variables
- 2.7 Landform classifications
- 2.7.1 Gaussian landform classification
- 2.7.2 The Efremov-Krcho landform classification
- 2.7.3 The Shary landform classification
- 2.7.4 Other geomorphometric landform classifications
- References
- Chapter 3 Digital elevation models
- Abstract
- Keywords
- 3.1 DEM generation
- 3.1.1 Conventional topographic surveys
- 3.1.2 Kinematic GNSS surveys
- 3.1.3 Stereophotogrammetry of optical remote sensing images
- 3.1.4 Structure-from-motion technique for unmanned survey imagery
- 3.1.5 Laser altimetry
- 3.1.6 Synthetic aperture radar techniques
- 3.1.7 Echo sounding
- 3.1.8 Satellite radar altimetry
- 3.1.9 Optical sensing of bathymetry
- 3.1.10 Soil and geological core drilling
- 3.1.11 Three-dimensional seismic survey
- 3.1.12 Ice and ground penetrating surveys
- 3.1.13 Digitizing of contours
- 3.1.14 Fusion of data from different sources
- 3.2 DEM grids
- 3.2.1 Plane grids
- 3.2.2 Spheroidal grids
- 3.2.3 Dense point clouds
- 3.2.4 Datums and coordinate systems
- 3.3 DEM resolution
- 3.4 DEM interpolation
- 3.4.1 General
- 3.4.2 Selected methods
- References☆
- Chapter 4 Calculation methods
- Abstract
- Keywords
- 4.1 The Evans-Young method
- 4.2 Calculation of local morphometric variables on a plane square grid
- 4.2.1 Motivation
- 4.2.2 Formulas
- 4.2.3 Method validation
- 4.3 Calculation of local morphometric variables on a spheroidal equal angular grid on a sphere and an ellipsoid of revolution
- 4.3.1 Motivation
- 4.3.2 Formulas
- 4.3.3 Linear sizes of a spheroidal equal angular window
- 4.3.4 Discussion
- 4.4 Calculation of nonlocal morphometric variables
- 4.4.1 Plane square grid
- 4.4.2 Spheroidal equal angular grid on a sphere and an ellipsoid of revolution
- 4.5 Calculation of structural morphometric variables
- 4.5.1 Conventional algorithms
- 4.5.2 Horizontal deflection
- 4.6 Calculation of two-field-specific morphometric variables
- 4.6.1 Calculation of solar morphometric variables
- 4.6.2 Calculation of wind morphometric variables
- 4.6.3 Calculation of view morphometric variables
- 4.7 Calculation of combined morphometric variables
- 4.8 Calculation of landform classifications
- 4.9 Calculations on a triaxial ellipsoid
- 4.9.1 Motivation
- 4.9.2 Coordinate systems
- 4.9.3 Solution for the inverse geodetic problem
- 4.9.4 Length of meridian and parallel arcs
- 4.9.5 Cell area
- 4.9.6 General algorithms for geomorphometric calculations
- References
- Chapter 5 Errors and accuracy
- Abstract
- Keywords
- 5.1 Sources of DEM errors
- 5.1.1 DEMs from conventional topographic surveys
- 5.1.2 DEMs from kinematic GNSS topographic surveys
- 5.1.3 DEMs from stereophotogrammetry of optical remote sensing images
- 5.1.4 UAV- and SfM-based DEMs
- 5.1.5 Lidar DEMs
- 5.1.6 Interferometric DEMs
- 5.1.7 Bathymetric DEMs
- 5.1.8 Subsurface DEMs
- 5.1.9 Contour-based DEMs
- 5.1.10 Fused DEMs
- 5.2 Estimation of DEM accuracy
- 5.3 Calculation accuracy of local morphometric variables
- 5.3.1 Motivation
- 5.3.2 RMSE formulas for local morphometric variables
- 5.3.3 RMSE formulas for the partial derivatives
- 5.3.4 RMSE mapping
- 5.4 Ignoring the sampling theorem
- 5.4.1 Motivation
- 5.4.2 Materials and data processing
- 5.4.3 Results and discussion
- 5.5 The Gibbs phenomenon
- 5.5.1 Motivation
- 5.5.2 Materials and data processing
- 5.5.3 Results and discussion
- 5.6 Grid displacement
- 5.6.1 Motivation
- 5.6.2 Materials and data processing
- 5.6.3 Results and discussion
- 5.7 Linear artifacts
- 5.7.1 Motivation
- 5.7.2 Isotropy of local morphometric variables
- References
- Chapter 6 Filtering
- Abstract
- Keywords
- 6.1 Tasks of DTM filtering
- 6.1.1 Decomposition of the topographic surface
- 6.1.2 Denoising
- 6.1.3 Generalization
- 6.2 Methods of DTM filtering
- 6.2.1 Trend-surface analysis
- 6.2.2 The Filosofov method
- 6.2.3 Two-dimensional discrete Fourier transform
- 6.2.4 Two-dimensional discrete wavelet transform
- 6.2.5 Smoothing
- 6.2.6 Data elimination
- 6.2.7 Cutting method
- 6.3 Two-dimensional singular spectrum analysis
- 6.3.1 Formulas
- 6.3.2 Materials and data processing
- 6.3.3 Results and discussion
- References
- Chapter 7 Universal spectral analytical modeling
- Abstract
- Keywords
- 7.1 Motivation
- 7.2 Method
- 7.2.1 Calculation of expansion coefficients
- 7.2.2 The Fejér summation
- 7.2.3 Reconstruction of the approximated function
- 7.2.4 Calculation of derivatives
- 7.3 Algorithm
- 7.4 Materials and data processing
- 7.5 Results and discussion
- References
- Chapter 8 Mapping and visualization
- Abstract
- Keywords
- 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
- 8.5.1 Three-dimensional terrain modeling
- 8.5.2 Three-dimensional subsurface modeling
- 8.6 Virtual globes
- 8.6.1 Desktop globes
- 8.6.2 Web globes
- References
- Part II: Digital terrain modeling in soil science
- Chapter 9 Influence of topography on soil properties
- Abstract
- Keywords
- 9.1 Introduction
- 9.2 Local morphometric variables and soil
- 9.3 Nonlocal morphometric variables and soil
- 9.4 Discussion
- References
- Chapter 10 Adequate resolution of models
- Abstract
- Keywords
- 10.1 Motivation
- 10.2 Theory
- 10.3 Field study
- 10.3.1 Study site
- 10.3.2 Materials and methods
- 10.3.3 Results and discussion
- References
- Chapter 11 Predictive soil mapping
- Abstract
- Keywords
- 11.1 The Dokuchaev hypothesis as a central idea of soil predictions
- 11.2 Early models
- 11.3 Current predictive methods
- 11.3.1 Classification of methods
- 11.3.2 Mathematical approaches
- 11.3.3 Small-scale predictive models and upscaling
- 11.3.4 Prediction accuracy
- 11.4 Topographic multivariable approach
- References
- Chapter 12 Analyzing relationships in the topography-soil system
- Abstract
- Keywords
- 12.1 Motivation
- 12.2 Study sites
- 12.3 Materials and methods
- 12.3.1 Field work
- 12.3.2 Laboratory analyses
- 12.3.3 Data processing
- 12.4 Results and discussion
- 12.4.1 Variability in relationships between soil and morphometric variables
- 12.4.2 Topography and denitrification
- References
- Part III: Digital terrain modeling in geology
- Chapter 13 Folds and folding
- Abstract
- Keywords
- 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
- References
- Chapter 14 Lineaments and faults
- Abstract
- Keywords
- 14.1 Motivation
- 14.2 Theory
- 14.3 Method validation
- 14.3.1 Materials and data processing
- 14.3.2 Results and discussion
- 14.3.3 Strike, dip, and displacement estimation
- 14.4 Two case studies
- 14.4.1 The Crimean peninsula
- 14.4.2 The Kurchatov city area
- References
- Chapter 15 Accumulation zones and fault intersections
- Abstract
- Keywords
- 15.1 Motivation
- 15.2 Study area
- 15.3 Materials and methods
- 15.4 Results and discussion
- References
- Chapter 16 Global topography and tectonic structures
- Abstract
- Keywords
- 16.1 Motivation
- 16.2 Materials and data processing
- 16.3 Results and discussion
- 16.3.1 General interpretation
- 16.3.2 Global helical structures
- References
- Part IV: Digital terrain modeling in glaciology and polar research
- Chapter 17 Glacier motion and evolution
- Abstract
- Keywords
- 17.1 Introduction
- 17.2 Glacier mass balance
- 17.3 Ice flow velocity
- 17.4 Glacier force balance
- References
- Chapter 18 Crevasses
- Abstract
- Keywords
- 18.1 Motivation
- 18.2 Study area
- 18.3 Materials and methods
- 18.3.1 UAS characteristics
- 18.3.2 UAS surveying
- 18.3.3 Data processing
- 18.4 Results and discussion
- References
- Chapter 19 Catastrophic glacier events
- Abstract
- Keywords
- 19.1 Motivation
- 19.2 Study area
- 19.3 Materials and methods
- 19.3.1 UAS surveying
- 19.3.2 Data processing
- 19.4 Results and interpretation
- References
- Chapter 20 Antarctic oases
- Abstract
- Keywords
- 20.1 Motivation
- 20.2 Study area
- 20.3 Materials and methods
- 20.3.1 Geomorphometric modeling
- 20.3.2 Field geomorphometric interpretation
- 20.4 Results
- 20.5 Discussion
- References
- Chapter 21 Concluding remarks and pending problems
- Abstract
- Keywords
- 21.1 Geomorphometry today
- 21.2 Theory
- 21.3 Data processing
- 21.4 Applications
- References
- References
- Index
- No. of pages: 476
- Language: English
- Edition: 3
- Published: January 10, 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, RussiaRead Digital Terrain Analysis, Third Edition on ScienceDirect