气候变化领域集成服务门户(CCPortal): Remote sensing GIS-based landslide susceptibility & risk modeling in Darjeeling–Sikkim Himalaya together with FEM-based slope stability analysis of the terrain

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DOI	10.1007/s11069-021-04823-5
	Remote sensing GIS-based landslide susceptibility & risk modeling in Darjeeling–Sikkim Himalaya together with FEM-based slope stability analysis of the terrain
	Nath S.K.; Sengupta A.; Srivastava A.
发表日期	2021
ISSN	0921030X
起始页码	3271
结束页码	3304
卷号	108 期号:3
英文摘要	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 < LSI ≤ 0.17), ‘Low’ (with: 0.17 < LSI ≤ 0.34), ‘Moderate’ (with: 0.34 < LSI ≤ 0.51), ‘High’ (with: 0.51 < LSI ≤ 0.68),‘Very High’ (with: 0.68 < LSI ≤ 0.85) and ‘Severe’ (with: 0.85 < LSI ≤ 1.00) susceptible zones as validated through standard statistical accuracy tests and direct cross-correlation analysis of all the susceptible zonation maps generated by drawing comparison with the 30% landslide inventory test data. The best integrated thematic RF-based LSI vector layer with an accuracy level of 0.871, in turn, on integration with the vulnerability components like population density, number of households, building types, building height and building density has demarketed approximately 21% of the region under ‘Very High’ to ‘Severe’ socioeconomic risk zone while about 36% area are classified under ‘Very High’ to ‘Severe’ structural risk zone as implicated by devastating landslide hazards in the region. Ground Penetrating Radar Survey has been conducted on all the slopes in the ‘Very High to Severe’ landslide susceptible zones wherein near-surface lithologic setting, presence of paleo-slopes and microstructural features like fractures/faults and poorly stratified debris flow have been imaged that provided favorable subsurface conditions for slope failure. Finite element method-based slope failure analysis for Newmark displacement estimates factor of safety (FoS) value that acts as the proxy in defining the degree of slope instability is seen to vary between 1.905 and 2.357 in the ‘Low to Moderate’ landslide susceptible zone while it ranges between 1.051 and 1.652 in the ‘High’ landslide susceptible zone and between 0.649 and 1.349 in the ‘Very High to Severe’ landslide inventory subset along the slopes under both gravity loading and seismic shaking in the terrain. The slope stability analysis puts the yield acceleration between 0.0012 and 0.11984 m/s2 and the total deformation between 0.0027 and 1.4484 m. All these parameters in the classified landslide susceptible zones in unison demonstrate how unstable are the terrain slopes in the ‘High to Severe’ landslide susceptible zones. © 2021, The Author(s), under exclusive licence to Springer Nature B.V.
关键词	Darjeeling–Sikkim Himalaya Landslide susceptibility zones Static dynamic slope stability Vulnerability risk
语种	英语
来源期刊	Natural Hazards
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/206448
作者单位	Department of Geology and Geophysics, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India
推荐引用方式 GB/T 7714	Nath S.K.,Sengupta A.,Srivastava A.. Remote sensing GIS-based landslide susceptibility & risk modeling in Darjeeling–Sikkim Himalaya together with FEM-based slope stability analysis of the terrain[J],2021,108(3).
APA	Nath S.K.,Sengupta A.,&Srivastava A..(2021).Remote sensing GIS-based landslide susceptibility & risk modeling in Darjeeling–Sikkim Himalaya together with FEM-based slope stability analysis of the terrain.Natural Hazards,108(3).
MLA	Nath S.K.,et al."Remote sensing GIS-based landslide susceptibility & risk modeling in Darjeeling–Sikkim Himalaya together with FEM-based slope stability analysis of the terrain".Natural Hazards 108.3(2021).