Quantitative Geomorphology in the Artificial Intelligence Era: Applications of AI for Earth and Environmental Change focuses on bridging the gaps in this emerging discipline, it delves into the complex interplay between landforms and the processes that shape them, offering innovative solutions through AI and data-driven methods. The book addresses the standards, quality assessment of data, spatial and temporal analysis tools, and rigorous validation techniques in geomorphology. It uses computational intelligence as a pivotal tool alongside GIS, remote sensing, and other advanced technologies. Readers will find a holistic resource that fosters collaboration and knowledge exchange among geological fields, aiming to address geomorphological challenges, hazards, and solutions. By harnessing AI, GIS, remote sensing, machine learning, and geophysical techniques, it offers new dimensions to existing assessment methods and techniques.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. List of contributors - p. xix 7. Chapter 1. Hierarchical random forest classification using multisource, multitemporal PolSAR, and multispectral data for forest species mapping - p. 1 8. Chapter 2. Utilizing remote sensing data to assess geomorphic and land use changes in watersheds for water resource management and risk mitigation: Maharloo Lake watershed - p. 21 9. Chapter 3. Application of sample fraction and machine learning models for groundwater potential mapping: a remedy for Urmia Lake? - p. 51 10. Chapter 4. Impacts of climate change on geomorphological processes and hazards using high-resolution data derived from unmanned aerial vehicle photogrammetry and terrestrial laser scanning - p. 91 11. Chapter 5. Mitigation of groundwater salinity vulnerability through land cultivation scenarios - p. 121 12. Geodiversity and biogeomorphology: Predicting species distribution, biodiversity changes, and climate adaptation - p. 145 13. Chapter 7. Investigating the nexus of climate change, land use change, and desertification using machine learning, stochastic models, and projected climate change scenarios - p. 171 14. Chapter 8. Mapping subsidence rate of the Kashan Plain using hybrid pluggable processing pipeline (HyP3) and stacking-InSAR method - p. 205 15. Chapter 9. Quantifying landslide risk: a critical reassessment of slope stability and human settlement impacts - p. 219 16. Chapter 10. Interstratal dissolution activities along the eastern portion of Ar-Riyadh city, Saudi Arabia - p. 233 17. Chapter 11. Assessment of water erosion using the ICONA model in arid and semiarid regions of northeastern Iran - p. 257 18. Chapter 12. Landscape metrics changes in Maharloo watershed, Fars Province, Iran - p. 269 19. Chapter 13. A multidisciplinary approach to understanding and mitigating erosional landforms - p. 283 20. Chapter 14. Spatial modeling of wildfires in the southern Zagros: a comparative analysis using frequency ratio and maximum entropy models - p. 301 21. Chapter 15. Examining the accuracy of G2 and RUSLE models in predicting soil erosion using Google Earth Engine information - p. 321 22. Chapter 16. Compilation of participatory management responses regarding landscape changes - p. 341 23. Chapter 17. Early warning systems for soil erosion assessment - p. 353 24. Chapter 18. Integrated geomorphological method for landslide and flood hazard mapping and risk assessment - p. 369 25. Chapter 19. Evaluating the accuracy of 3D photogrammetry models from uncalibrated aerial imagery for precision hydraulic river modeling - p. 399 26. Chapter 20. The importance of digital elevation model resolution on natural hazards studies - p. 415 27. Chapter 21. Geomorphological mapping for sustainable management of the Pacific coast of Costa Rica - p. 435 28. Chapter 22. Tracing dust sources in northern Iran using HYSLPIT model, remote sensing, and geomorphological analysis - p. 465 29. Chapter 23. Examining how changes in land use have affected land degradation patterns in northeastern Iran from 2002 to 2021 - p. 481 30. Chapter 24. Mass movements analysis along the Southern Escarpment of the Bamileke Plateaus (Western Cameroon highlands) using a rainfall data analytical approach - p. 495 31. Chapter 25. Piping collapse: geodiversity in loessial landscapes - p. 515 32. Index - p. 527
Quantitative Geomorphology in the Artificial Intelligence Era: Applications of AI for Earth and Environmental Change focuses on bridging the gaps in this emerging discipline, it delves into the complex interplay between landforms and the processes that shape them, offering innovative solutions through AI and data-driven methods. The book addresses the standards, quality assessment of data, spatial and temporal analysis tools, and rigorous validation techniques in geomorphology. It uses computational intelligence as a pivotal tool alongside GIS, remote sensing, and other advanced technologies. Readers will find a holistic resource that fosters collaboration and knowledge exchange among geological fields, aiming to address geomorphological challenges, hazards, and solutions. By harnessing AI, GIS, remote sensing, machine learning, and geophysical techniques, it offers new dimensions to existing assessment methods and techniques.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. List of contributors - p. xix 7. Chapter 1. Hierarchical random forest classification using multisource, multitemporal PolSAR, and multispectral data for forest species mapping - p. 1 8. Chapter 2. Utilizing remote sensing data to assess geomorphic and land use changes in watersheds for water resource management and risk mitigation: Maharloo Lake watershed - p. 21 9. Chapter 3. Application of sample fraction and machine learning models for groundwater potential mapping: a remedy for Urmia Lake? - p. 51 10. Chapter 4. Impacts of climate change on geomorphological processes and hazards using high-resolution data derived from unmanned aerial vehicle photogrammetry and terrestrial laser scanning - p. 91 11. Chapter 5. Mitigation of groundwater salinity vulnerability through land cultivation scenarios - p. 121 12. Geodiversity and biogeomorphology: Predicting species distribution, biodiversity changes, and climate adaptation - p. 145 13. Chapter 7. Investigating the nexus of climate change, land use change, and desertification using machine learning, stochastic models, and projected climate change scenarios - p. 171 14. Chapter 8. Mapping subsidence rate of the Kashan Plain using hybrid pluggable processing pipeline (HyP3) and stacking-InSAR method - p. 205 15. Chapter 9. Quantifying landslide risk: a critical reassessment of slope stability and human settlement impacts - p. 219 16. Chapter 10. Interstratal dissolution activities along the eastern portion of Ar-Riyadh city, Saudi Arabia - p. 233 17. Chapter 11. Assessment of water erosion using the ICONA model in arid and semiarid regions of northeastern Iran - p. 257 18. Chapter 12. Landscape metrics changes in Maharloo watershed, Fars Province, Iran - p. 269 19. Chapter 13. A multidisciplinary approach to understanding and mitigating erosional landforms - p. 283 20. Chapter 14. Spatial modeling of wildfires in the southern Zagros: a comparative analysis using frequency ratio and maximum entropy models - p. 301 21. Chapter 15. Examining the accuracy of G2 and RUSLE models in predicting soil erosion using Google Earth Engine information - p. 321 22. Chapter 16. Compilation of participatory management responses regarding landscape changes - p. 341 23. Chapter 17. Early warning systems for soil erosion assessment - p. 353 24. Chapter 18. Integrated geomorphological method for landslide and flood hazard mapping and risk assessment - p. 369 25. Chapter 19. Evaluating the accuracy of 3D photogrammetry models from uncalibrated aerial imagery for precision hydraulic river modeling - p. 399 26. Chapter 20. The importance of digital elevation model resolution on natural hazards studies - p. 415 27. Chapter 21. Geomorphological mapping for sustainable management of the Pacific coast of Costa Rica - p. 435 28. Chapter 22. Tracing dust sources in northern Iran using HYSLPIT model, remote sensing, and geomorphological analysis - p. 465 29. Chapter 23. Examining how changes in land use have affected land degradation patterns in northeastern Iran from 2002 to 2021 - p. 481 30. Chapter 24. Mass movements analysis along the Southern Escarpment of the Bamileke Plateaus (Western Cameroon highlands) using a rainfall data analytical approach - p. 495 31. Chapter 25. Piping collapse: geodiversity in loessial landscapes - p. 515 32. Index - p. 527
