Advanced Tools for Studying Soil Erosion Processes: Erosion Modelling, Soil Redistribution Rates, Advanced Analysis, and Artificial Intelligence presents the most recent technologies and methods in quantifying soil erosion, focusing on quantitative geomorphological assessment, soil erosion interaction with natural and man-made hazards using new methods, and technologies that employ GIS, remote sensing (RS), spatial modeling, and machine learning tools as an effective plan for decision-makers and land users.
Organized into three parts: 1) Erosion processes and impacts, 2) Advanced computing techniques to quantify soil erosion, and 3) Methods of Soil Erosion, this book will be an invaluable source material for researchers, academicians, graduate and undergraduate students, and professionals in the field of geology, specifically focused on geographic information systems and remote sensing.
1. Chapter 3 : Comprehensive introduction to Digital Elevation Models, as a key dataset in soil erosion mapping - p. Page 25 2. Chapter 4 : Soil pipe pattern dynamics and illustration of the erosional landforms from a geomorphological perspective - p. Page 55 3. Chapter 5 : Extraction of water bodies using machine learning and water body indices in an arid region, comparison, and application: A case study Naser Lake Egypt - p. Page 70 4. Chapter 6 : Leveraging remote sensing data and machine learning models to estimate suspended sediment concentration (SSC), a vital water quality parameter to assess soil erosion effects - p. Page 92 5. Chapter 7 : The messianic breath of cyanobacteria: Revival role of microbial biological crust on restoring degraded soils - p. Page 111 6. Chapter 8 : Analyzing the homogeneity of the paired catchments using the fractal dimension of the drainage network and catchment shape - p. Page 124 7. Chapter 9 : Fractal analysis of drainage network and its relationship with flooding potential in arid areas - p. Page 152 8. Chapter 10 : Climate change and soil erosion dynamics: An overview - p. Page 177 9. Chapter 11 : Assessment and mapping of rangeland ecosystem services in soil conservation - p. Page 193 10. Chapter 12 : Event-based soil erosion estimation in a tropical watershed using OpenLISEM - p. Page 208 11. Chapter 13 : A scenario-based approach for modeling and monitoring the impacts of climate change on forest fire using MODIS time series images - p. Page 226 12. Chapter 14 : Soil erosion analysis based on UAV and SPOT-6 satellite images - p. Page 239 13. Chapter 15 : Gully erosion susceptibility assessment using machine learning methods and geostatistical multivariate approach - p. Page 254 14. Chapter 16 : Land subsidence modeling and mapping in Darab region, Iran - p. Page 271 15. Chapter 17 : Review of multihazards research with the basis of soil erosion - p. Page 292 16. Chapter 18 : Prediction of soil erosion using machine learning - p. Page 303 17. Chapter 19 : Artificial Intelligence including Machine Learning and Deep Learning algorithms - p. Page 320 18. Chapter 20 : The influence of weathering on piping erosion processes on large dimension pipes - p. Page 334 19. Chapter 21 : Quantile random forest technique for soil moisture contents digital mapping, Sarvestan Plain, Iran - p. Page 347 20. Chapter 22 : Modeling spatial variability of soil loss tolerance (T-value) using geostatistical approaches (case study: Dorudzan Watershed, Fars Province, Iran) - p. Page 364 21. Chapter 23 : Potential of spectroscopy-based approaches for predicting soil erosion-related parameters: A short review - p. Page 388 22. Chapter 24 : Spatiotemporal variations in land use of Mahvelat plain in Iran using Google Earth Engine from 2011 to 2030 - p. Page 408 23. Chapter 25 : Detecting soil salinization, sodicity, and alkalization hazards within cultivated lands using digital soil mapping approaches - p. Page 431 24. Chapter 26 : The impact of geomorphological hazards (i.e., mass movements/landslides) on soil erosion - p. Page 457 25. Chapter 27 : Involvement of soil erosion processes in the development of landslides in the locality of Echiock (West Cameroon) - p. Page 467 26. Chapter 28 : Digital mapping of soil pH in arid and semi-arid regions - p. Page 481 27. Chapter 29 : Unraveling the spatial signature of gully erosion in the arid and semi-arid regions of the northeast of Iran: Every single factor matters! - p. Page 497 28. Chapter 30 : Soil erosion monitoring using the perpendicular soil moisture index as a remote sensing index (case study: Salehiya Wetland, Iran) - p. Page 524 29. Chapter 31 : Scrutinizing of soil erosion spatial distribution through explicit spatial HRU approaches in SWAT model - p. Page 540 30. Chapter 32 : Application of ANSWERS model for calculating runoff and sediment prediction from steep agricultural watersheds in northern Iran and its comparison with the other related models - p. Page 559 31. Chapter 33 : Susceptibility mapping for land subsidence and collapsed pipes in north-east Iran - p. Page 575 32. Index - p. Page 593
Advanced Tools for Studying Soil Erosion Processes: Erosion Modelling, Soil Redistribution Rates, Advanced Analysis, and Artificial Intelligence presents the most recent technologies and methods in quantifying soil erosion, focusing on quantitative geomorphological assessment, soil erosion interaction with natural and man-made hazards using new methods, and technologies that employ GIS, remote sensing (RS), spatial modeling, and machine learning tools as an effective plan for decision-makers and land users.
Organized into three parts: 1) Erosion processes and impacts, 2) Advanced computing techniques to quantify soil erosion, and 3) Methods of Soil Erosion, this book will be an invaluable source material for researchers, academicians, graduate and undergraduate students, and professionals in the field of geology, specifically focused on geographic information systems and remote sensing.
1. Chapter 3 : Comprehensive introduction to Digital Elevation Models, as a key dataset in soil erosion mapping - p. Page 25 2. Chapter 4 : Soil pipe pattern dynamics and illustration of the erosional landforms from a geomorphological perspective - p. Page 55 3. Chapter 5 : Extraction of water bodies using machine learning and water body indices in an arid region, comparison, and application: A case study Naser Lake Egypt - p. Page 70 4. Chapter 6 : Leveraging remote sensing data and machine learning models to estimate suspended sediment concentration (SSC), a vital water quality parameter to assess soil erosion effects - p. Page 92 5. Chapter 7 : The messianic breath of cyanobacteria: Revival role of microbial biological crust on restoring degraded soils - p. Page 111 6. Chapter 8 : Analyzing the homogeneity of the paired catchments using the fractal dimension of the drainage network and catchment shape - p. Page 124 7. Chapter 9 : Fractal analysis of drainage network and its relationship with flooding potential in arid areas - p. Page 152 8. Chapter 10 : Climate change and soil erosion dynamics: An overview - p. Page 177 9. Chapter 11 : Assessment and mapping of rangeland ecosystem services in soil conservation - p. Page 193 10. Chapter 12 : Event-based soil erosion estimation in a tropical watershed using OpenLISEM - p. Page 208 11. Chapter 13 : A scenario-based approach for modeling and monitoring the impacts of climate change on forest fire using MODIS time series images - p. Page 226 12. Chapter 14 : Soil erosion analysis based on UAV and SPOT-6 satellite images - p. Page 239 13. Chapter 15 : Gully erosion susceptibility assessment using machine learning methods and geostatistical multivariate approach - p. Page 254 14. Chapter 16 : Land subsidence modeling and mapping in Darab region, Iran - p. Page 271 15. Chapter 17 : Review of multihazards research with the basis of soil erosion - p. Page 292 16. Chapter 18 : Prediction of soil erosion using machine learning - p. Page 303 17. Chapter 19 : Artificial Intelligence including Machine Learning and Deep Learning algorithms - p. Page 320 18. Chapter 20 : The influence of weathering on piping erosion processes on large dimension pipes - p. Page 334 19. Chapter 21 : Quantile random forest technique for soil moisture contents digital mapping, Sarvestan Plain, Iran - p. Page 347 20. Chapter 22 : Modeling spatial variability of soil loss tolerance (T-value) using geostatistical approaches (case study: Dorudzan Watershed, Fars Province, Iran) - p. Page 364 21. Chapter 23 : Potential of spectroscopy-based approaches for predicting soil erosion-related parameters: A short review - p. Page 388 22. Chapter 24 : Spatiotemporal variations in land use of Mahvelat plain in Iran using Google Earth Engine from 2011 to 2030 - p. Page 408 23. Chapter 25 : Detecting soil salinization, sodicity, and alkalization hazards within cultivated lands using digital soil mapping approaches - p. Page 431 24. Chapter 26 : The impact of geomorphological hazards (i.e., mass movements/landslides) on soil erosion - p. Page 457 25. Chapter 27 : Involvement of soil erosion processes in the development of landslides in the locality of Echiock (West Cameroon) - p. Page 467 26. Chapter 28 : Digital mapping of soil pH in arid and semi-arid regions - p. Page 481 27. Chapter 29 : Unraveling the spatial signature of gully erosion in the arid and semi-arid regions of the northeast of Iran: Every single factor matters! - p. Page 497 28. Chapter 30 : Soil erosion monitoring using the perpendicular soil moisture index as a remote sensing index (case study: Salehiya Wetland, Iran) - p. Page 524 29. Chapter 31 : Scrutinizing of soil erosion spatial distribution through explicit spatial HRU approaches in SWAT model - p. Page 540 30. Chapter 32 : Application of ANSWERS model for calculating runoff and sediment prediction from steep agricultural watersheds in northern Iran and its comparison with the other related models - p. Page 559 31. Chapter 33 : Susceptibility mapping for land subsidence and collapsed pipes in north-east Iran - p. Page 575 32. Index - p. Page 593
