DOI: 10.1007/s11069-021-04823-5
论文题名: Remote sensing GIS-based landslide susceptibility & risk modeling in Darjeeling–Sikkim Himalaya together with FEM-based slope stability analysis of the terrain
作者: Nath S.K. ; Sengupta A. ; Srivastava A.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2021
卷: 108, 期: 3 起始页码: 3271
结束页码: 3304
语种: 英语
中文关键词: Darjeeling–Sikkim Himalaya
; Landslide susceptibility zones
; Static dynamic slope stability
; Vulnerability risk
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. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/169247
Appears in Collections: 气候变化与战略
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作者单位: Department of Geology and Geophysics, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India
Recommended Citation:
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]. Natural Hazards,2021-01-01,108(3)