Water, Land, and Forest Susceptibility and Sustainability, Volume 1: Geospatial Approaches & Modeling brings an interdisciplinary perspective to solving complex problems in sustainability, utilizing the latest research and technologies, and includes case studies that emphasize the applications of remote sensing, GIS, and image processing for addressing the current state and future needs to achieve sustainability. As forests, land, and water are among the most precious resources on earth, emphasizing the need to conserve them for future generations and, of course, a safe and sustainable planet. The assessment of the susceptibility of all these three precious resources must therefore be addressed to inform their sustainable management. This 1st volume encourages adaptive activities among experts employed in interdisciplinary fields, from data mining and machine learning to environmental science by linking geospatial computational intelligence technology to forest, land and water issues. - Presents theoretical context and practical solutions for understanding the current knowledge and where future efforts should be directed - Includes case studies in each chapter demonstrating the use of geospatial technologies - Offers an interdisciplinary approach to addressing susceptibility and achieving sustainability

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Yes, you can access Water, Land, and Forest Susceptibility and Sustainability by Uday Chatterjee, Biswajeet Pradhan, Suresh Kumar Kailasa, Sourav Saha, Mohammad Zakwan, Uday Chatterjee,Biswajeet Pradhan,Suresh Kumar Subbiah,Sourav Saha,Mohammad Zakwan,Suresh Kumar Kailasa,Suresh Kumar in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Environmental Science. We have over one million books available in our catalogue for you to explore.

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Environmental Science

Index

Biological Sciences

Cover
Front Matter
Table of Contents
Copyright
Contributors
Foreword
List of Illustrations
List of Tables
Chapter 1 : Theoretical framework and approaches of susceptibility and sustainability: issues and drivers
Chapter 2 : Trap efficiency of reservoirs: concept, review, and application
Chapter 3 : GIS for Watershed Characterization and Modeling: example of the Taguenit River (Lakhssas, Morocco)∗
Chapter 4 : Application of artificial intelligence to estimate dispersion coefficient and pollution in river
Chapter 5 : Predicting nitrate concentration in river using advanced artificial intelligence techniques: extreme learning machines versus deep learning
Chapter 6 : Polluted water bodies remediation by using GIS and remote sensing approach: a deeper insight
Chapter 7 : GIS-based spatial distribution analysis of water quality assessment using water pollution index of Yamuna river at Delhi
Chapter 8 : Groundwater sustainability: role of monitoring, modeling, and management
Chapter 9 : Landslide susceptibility modeling using a generalized linear model in a tropical river basin of the Southern Western Ghats, India
Chapter 10 : Assessment of the land use and landcover changes using remote sensing and GIS techniques
Chapter 11 : Mapping and monitoring land dynamics using geospatial techniques on Pathar Pratima Block, South 24 Parganas, India
Chapter 12 : Geospatial technologies to investigate the wetland susceptibility to environmental challenges and identify sustainability options
Chapter 13 : Evaluation of spatial and temporal variability in rainfall erosivity and soil erosion risk in Maharashtra, India
Chapter 14 : Soil erosion modeling under future climate change: a case study on Marinduque Island, Philippines
Chapter 15 : Forest fire susceptibility mapping and risk assessment using integrated AHP and DEMATEL method for Purulia District, West Bengal (India)
Chapter 16 : Decline in vegetation cover over Kolkata city: an environmental concern from remote-sensing perspective
Chapter 17 : Understanding the forest cover dynamics and its health status using GIS-based analytical hierarchy process: a study from Alipurduar district, West Bengal, India
Chapter 18 : Detection of forest fragmented areas of Sonitpur, Lakhimpur, and Papum Reserve Forest using the FCD model
Index
A

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