Remote sensing GIS-based landslide susceptibility & risk modeling in Darjeeling–Sikkim Himalaya together with FEM-based slope stability analysis of the terrain
Sankar Kumar Nath (),
Arnab Sengupta () and
Anand Srivastava ()
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Sankar Kumar Nath: Indian Institute of Technology Kharagpur
Arnab Sengupta: Indian Institute of Technology Kharagpur
Anand Srivastava: Indian Institute of Technology Kharagpur
Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2021, vol. 108, issue 3, No 40, 3304 pages
Abstract:
Abstract Landslide susceptibility (LSI) modeling of Darjeeling–Sikkim Himalaya is performed by integrating 28 causative factors on 28C28 combinations on Geographical Information System (GIS) following analytic hierarchy process (AHP)-based multicriteria decision protocol, logistic regression (LR)-based multivariate technique, machine learning data-driven random forest (RF) and artificial neural network (ANN) methods wherein the terrain is classified into ‘None’ (with: 0.0
Keywords: Landslide susceptibility zones; Vulnerability risk; Static dynamic slope stability; Darjeeling–Sikkim Himalaya (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:108:y:2021:i:3:d:10.1007_s11069-021-04823-5
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DOI: 10.1007/s11069-021-04823-5
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