Editors:
- Written in reader-friendly, lucid language
- Presents clear concepts of geospatial techniques
- Includes case studies that apply modern machine learning models
- Motivates general readers as well as researchers to become involved in forest resources management
- Covers novel analytical and diagnostic techniques using open source software like Q-GIS, R programming, Dyna-CLUE LULC model
Part of the book series: Environmental Science and Engineering (ESE)
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Table of contents (28 chapters)
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Front Matter
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Forest Resources Measurement, Monitoring and Mapping
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Front Matter
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Modeling, Risk Assessment and Vulnerability
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Front Matter
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About this book
Discusses major topics such as forest health assessment, estimating forest biomass & carbon stock, land use forest cover (LUFC), dynamic vegetation modeling (DVM) approaches, forest-based rural livelihood, habitat suitability analysis, biodiversity and ecology, and biodiversity, the book presents novel advances and applications of RS-GIS and R in a precise and clear manner.
By offering insights into various concepts and their importance for real-world applications, it equips researchers, professionals, and policy-makers with the knowledge and skills to tackle a wide range of issues related to geographic data, including those with scientific, societal, and environmental implications.
Editors and Affiliations
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PG Department of Geography, Raja Narendra Lal Khan Women’s College (Autonomous), Vidyasagar University, Midnapore, India
Pravat Kumar Shit
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Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, Iran
Hamid Reza Pourghasemi
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Department of Remote Sensing & GIS, Vidyasagar University, Midnapore, India
Pulakesh Das
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TPF Getinsa Euroestudios S.l, Gurgaon, India
Gouri Sankar Bhunia
About the editors
Hamid Reza Pourghasemi is an Associate Professor of Watershed Management Engineering at the College of Agriculture, Shiraz University, Iran. He holds a B.Sc, an M.Sc, and PhD in Watershed Management Engineering from the University of Gorgan, Iran, and Tarbiat Modares University, Iran, respectively. His main research interests are GIS-based spatial modeling using machine learning/data mining techniques in different fields, such as landslide, flood, gully erosion, forest fire, land subsidence, species distribution modeling, and groundwater/hydrology. He has published more than 100 peer-reviewed papers in high-quality journals. Also, he published two books with Springer.
Pulakesh Das received his Ph.D. from the Indian Institution of Technology Kharagpur, India. Currently he is teaching as an Assistant Professor at the Department of Remote Sensing & GIS, Vidyasagar University, West Bengal, India. He completed his B.Sc in Physics and M.Sc in Remote Sensing & GIS at the same university. His research areas include land use and forest cover modeling, hydrological modeling, study of forest cover dynamics and climate change, and digital image processing. He has published more than 15 research articles in respected, peer-reviewed journals.
Gouri Sankar Bhunia received his Ph.D. from the University of Calcutta, India. His Ph.D. dissertation focused on environmental control of infectious disease using geospatial technology. His research interests include environmental modeling, risk assessment, natural resources mapping and modeling, data mining and information retrieval using geospatial technology. Dr. Bhunia has published more than 60 articles in various leading journals
Bibliographic Information
Book Title: Spatial Modeling in Forest Resources Management
Book Subtitle: Rural Livelihood and Sustainable Development
Editors: Pravat Kumar Shit, Hamid Reza Pourghasemi, Pulakesh Das, Gouri Sankar Bhunia
Series Title: Environmental Science and Engineering
DOI: https://doi.org/10.1007/978-3-030-56542-8
Publisher: Springer Cham
eBook Packages: Earth and Environmental Science, Earth and Environmental Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-56541-1Published: 09 October 2020
Softcover ISBN: 978-3-030-56544-2Published: 10 October 2021
eBook ISBN: 978-3-030-56542-8Published: 08 October 2020
Series ISSN: 1863-5520
Series E-ISSN: 1863-5539
Edition Number: 1
Number of Pages: XIX, 675
Number of Illustrations: 27 b/w illustrations, 188 illustrations in colour