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Information Value Model Based Mapping of Updated Spatial and Temporal Landslide Susceptibility: A Case Study from East Sikkim District, India’s Northeastern Himalayas
Version 1
: Received: 1 April 2024 / Approved: 1 April 2024 / Online: 2 April 2024 (12:48:03 CEST)
How to cite:
Rafique, M.F.; Joshi, V. Information Value Model Based Mapping of Updated Spatial and Temporal Landslide Susceptibility: A Case Study from East Sikkim District, India’s Northeastern Himalayas. Preprints2024, 2024040066. https://doi.org/10.20944/preprints202404.0066.v1
Rafique, M.F.; Joshi, V. Information Value Model Based Mapping of Updated Spatial and Temporal Landslide Susceptibility: A Case Study from East Sikkim District, India’s Northeastern Himalayas. Preprints 2024, 2024040066. https://doi.org/10.20944/preprints202404.0066.v1
Rafique, M.F.; Joshi, V. Information Value Model Based Mapping of Updated Spatial and Temporal Landslide Susceptibility: A Case Study from East Sikkim District, India’s Northeastern Himalayas. Preprints2024, 2024040066. https://doi.org/10.20944/preprints202404.0066.v1
APA Style
Rafique, M.F., & Joshi, V. (2024). Information Value Model Based Mapping of Updated Spatial and Temporal Landslide Susceptibility: A Case Study from East Sikkim District, India’s Northeastern Himalayas. Preprints. https://doi.org/10.20944/preprints202404.0066.v1
Chicago/Turabian Style
Rafique, M.F. and Varun Joshi. 2024 "Information Value Model Based Mapping of Updated Spatial and Temporal Landslide Susceptibility: A Case Study from East Sikkim District, India’s Northeastern Himalayas" Preprints. https://doi.org/10.20944/preprints202404.0066.v1
Abstract
The Indian Himalayan Region (IHR), due to its topography, geography, and active
tectonics, a rough mountain zone, is among the most vulnerable zones to the landslip
danger. The most cutting-edge and accurate ways for creating a landslip susceptibility
model (LSM) are advanced statistical techniques. The goal of the current work was to
use advanced statistical techniques to analyse and evaluate the updated landslip
susceptibility for East District in the NE Himalayas of Sikkim, India. The spatiotemporal
landslip inventory for the years are produced using literature surveys, historical
satellite imageries and on-site observations. Slope, aspect, elevation, curvature, plane
curvature, profile curvature, topographic wetness index (TWI), lithology, distance to
faults, distance to streams, distance to roads, normalised difference vegetation index
(NDVI), rainfall, drainage density and land use/ land cover (LULC) are some of the
topographic, environmental, geologic, and anthropogenic factors that were included in
the spatial database. These LCFs were chosen to study the area's periodic landslip
vulnerability. An inventory of 151 landslides from historical published records, field
visits and Imagery interpretations, respectively, were used in the experimental design.
Information Value Model (IVM), was used to evaluate the vulnerability to landslides as
determined by fifteen LCFs. The goal of the study is to reduce the number of fatalities
and possible economic harm caused by the region's frequent slope instabilities. It is
expected that the application of statistical algorithms would assist relevant authorities
and organisations in properly planning for and managing the region's landslip threat.
Keywords
East Sikkim; Landslide susceptibility; Information Value Model
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
