Advanced Tools for Studying Soil Erosion Processes: Erosion Modelling, Soil Redistribution Rates, Advanced Analysis, and Artificial Intelligence

by Hamid Reza Pourghasemi (Editor), Narges Kariminejad (Editor)

Overview

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. - Provides an overview of soil erosion and its interaction with natural hazards (i.e., geological, hydrological, meteorological, and biological) - Introduces advanced tools and technologies in soil erosion management - Presents future soil erosion opportunities and challenges

Product Details

ISBN-13:	9780443222634
Publisher:	Elsevier Science
Publication date:	08/17/2024
Sold by:	Barnes & Noble
Format:	eBook
Pages:	650
File size:	138 MB
Note:	This product may take a few minutes to download.

About the Author

Hamid Reza Pourghasemi is a professor of watershed management engineering in the College of Agriculture, Shiraz University, in Iran. His main research interests are GIS-based spatial modelling using machine learning/data mining techniques in different fields such as landslides, floods, gully erosion, forest fires, land subsidence, species distribution modelling, and groundwater/hydrology. Professor Pourghasemi also works on multi-criteria decision-making methods in natural resources and environmental science. He has published over 230 peer-reviewed papers in high-quality journals and seven edited books for Springer and Elsevier and is an active reviewer for over 90 international journals. He was selected as one of the five young scientists under 40 by The World Academy of Science (TWAS 2019) and was a highly cited researcher in 2019 and 2020
Narges Kariminejad is a geomorphologist with about 10 years of work experience in field and laboratory-based soil erosion research in arid and semi-arid environments. She is also currently a researcher at the Department of Natural Resources and Environment Engineering in the College of Agriculture at Shiraz University, in Iran. Her research interests are in soil erosion, especially in rill, soil piping, and gully erosion. She has served as a guest scientist or visiting researcher at various research institutes and universities in different countries all over the world. Dr. Kariminejad has been a guest lecturer in difference courses, including quantitative geomorphology, spatial analysis and satellite imagery, plant ecology, and geostatistics. She has published more than 20 papers in international scientific journals.

Table of Contents

Part-I - Erosional processes and impacts1. Mapping land subsidence using time-series analysis of Sentinel-1 InSAR in various land use areas2. Use of hydrological models in erosion and sediment studies: a review3. Comprehensive introduction to Digital Elevation Models, as a key dataset in soil erosion mapping4. Eco-geomorphic reconstruction and illustration of the erosional landforms from a geomorphological point of view5. Extraction of water bodies using machine learning and water body indices in an arid region, comparison, and application: A case study Naser Lake Egypt6. Leveraging remote sensing data and machine learning models to estimate suspended sediment concentration (SSC), a vital water quality parameter to assess soil erosion effects7. The messianic tail of cyanobacteria: Revival role of microbial biological crust on restoring degraded soils8. Analyzing the homogeneity of the paired catchments using the fractal dimension of the drainage network and catchment shape9. Fractal analysis of drainage network and its relationship with flooding potential in arid areas10. Climate change and soil erosion dynamics: An overview11. Mapping rangeland vegetation types sensitive to soil erosion in semi-arid of IranPart-II - Advanced computing techniques to quantify soil erosion12. Event-based soil erosion estimation in a tropical watershed using OpenLISEM13. A scenario-based approach for modeling and monitoring the impacts of climate change on forest fire using MODIS time series images14. Soil erosion analysis based on UAV and SPOT-6 satellite images15. Gully erosion susceptibility assessment using machine learning methods and geostatistical multivariate approach16. Land subsidence modeling and mapping in Darab region, Iran17. Review of multihazards research with the basis of soil erosion18. Prediction of soil erosion using machine learning19. Artificial Intelligence including Machine Learning and Deep Learning algorithms20. Understanding piping process on large dimension piping: Erosion versus weathering21. Quantile random forest technique for soil moisture contents digital mapping, Sarvestan Plain, Iran22. Modeling spatial variability of soil loss tolerance (T-value) using geostatistical approaches (case study: Dorudzan Watershed, Fars Province, Iran)Part-III - Methods of soil analysis23. Potential of spectroscopy-based approaches for predicting soil erosion-related parameters: A short review24. Spatiotemporal variations in land use of Mahvelat plain in Iran using Google Earth Engine from 2011 to 203025. Detecting soil salinization, sodicity, and alkalization hazards within cultivated lands using digital soil mapping approaches26. The impact of geomorphological hazards (i.e., mass movements/landslides) on soil erosion27. Involvement of erosion processes in the development of landslides in the locality of Echiock-Santchou (West Cameroon)28. Digital mapping of soil pH in arid and semi-arid regions29. Unraveling the spatial signature of gully erosion in the arid and semi-arid regions of the northeast of Iran: Every single factor matters!30. Soil erosion monitoring using the perpendicular soil moisture index as a remote sensing index(case study: Salehiya Wetland, Iran)31. Scrutinizing of soil erosion spatial distribution through explicit spatial HRU approaches in SWAT model32. Application of ANSWERS model for calculating runoff and sediment prediction from steep agricultural watersheds in northern Iran and its comparison with the other related models33. Susceptibility of the erosional landforms (Case study: Razavi Khorasan Province, Iran) Index

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From the Publisher

Presents recent technological improvements and knowledge on quantitative geomorphological assessment using geographic information systems, remote sensing, and machine learning