Overview
- Explores all geographical parameters and their roles in landslide processes
- Presents various statistical models and discusses the development of landslide susceptibility and risk maps
- Describes modern tools and techniques, i.e. remote sensing and geographical information systems
- Highlights quantitative and semi-quantitative approaches
Part of the book series: Environmental Science and Engineering (ESE)
Part of the book sub series: Environmental Science (ENVSCIENCE)
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Table of contents (10 chapters)
Keywords
About this book
This book discusses various statistical models and their implications for developing landslide susceptibility and risk zonation maps. It also presents a range of statistical techniques, i.e. bivariate and multivariate statistical models and machine learning models, as well as multi-criteria evaluation, pseudo-quantitative and probabilistic approaches. As such, it provides methods and techniques for RS & GIS-based models in spatial distribution for all those engaged in the preparation and development of projects, research, training courses and postgraduate studies. Further, the book offers a valuable resource for students using RS & GIS techniques in their studies.
Authors and Affiliations
Bibliographic Information
Book Title: Geoinformatics and Modelling of Landslide Susceptibility and Risk
Book Subtitle: An RS & GIS-based Model Building Approach in the Eastern Himalaya
Authors: Sujit Mandal, Subrata Mondal
Series Title: Environmental Science and Engineering
DOI: https://doi.org/10.1007/978-3-030-10495-5
Publisher: Springer Cham
eBook Packages: Earth and Environmental Science, Earth and Environmental Science (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-10494-8Published: 11 June 2019
eBook ISBN: 978-3-030-10495-5Published: 28 May 2019
Series ISSN: 1863-5520
Series E-ISSN: 1863-5539
Edition Number: 1
Number of Pages: XIII, 223
Topics: Earth System Sciences, Remote Sensing/Photogrammetry, Geomorphology, Natural Hazards, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Environmental Geography