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Greenway DR. (1987). Vegetation and slope stability. In M. G. Anderson & K. S. Richards (Eds.), Slope stability (pp. 187-230). New York: Wiley.

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Article

Landslide Susceptibility Mapping in East Sikkim Region of Sikkim Himalaya Using High Resolution Remote Sensing Data and GIS techniques

1University School of Environment Management, Guru Gobind Singh Indraprastha University, New Delhi-110078, India

2Department of Geology, Mizoram University, Aizawl-796 004, India


Applied Ecology and Environmental Sciences. 2020, Vol. 8 No. 4, 143-153
DOI: 10.12691/aees-8-4-1
Copyright © 2020 Science and Education Publishing

Cite this paper:
Prakash Biswakarma, Binoy Kumar Barman, Varun Joshi, K. Srinivasa Rao. Landslide Susceptibility Mapping in East Sikkim Region of Sikkim Himalaya Using High Resolution Remote Sensing Data and GIS techniques. Applied Ecology and Environmental Sciences. 2020; 8(4):143-153. doi: 10.12691/aees-8-4-1.

Correspondence to: Varun  Joshi, University School of Environment Management, Guru Gobind Singh Indraprastha University, New Delhi-110078, India. Email: varunj63@gmail.com

Abstract

Occurrence of landslides is very common and frequent phenomenon in hilly terrain of Indian Himalayan region leading to severe environmental and socio-economic issues. The current research used the method of weighted parameter, Remote Sensing (RS) and Geographic Information System (GIS) for landslide susceptibility mapping in the study area, East Sikkim district of Sikkim Himalaya. The different thematic layers were produced from high-resolution terrain corrected ALOS PALSAR DEM of 12.5 meter spatial resolution, Sentinel-2A data of 10 meter spatial resolution multi-spectral satellite information, LANDSAT 8 multi-spectral satellite information and multiple other landslide-related sources such as rainfall distribution, slope and structural/linear features (faults, thrusts, roads). These thematic map layers were integrated in a GIS platform (ArcGIS10.7) to delineate vulnerable landslide prone zones. The weighted assigned values were used for assigning weightage ranging from 0 to 10 for various causative factors responsible for landslide occurrences using standard weighted overly techniques. Landslide susceptibility map of the entire research area is split into three categories i.e. low susceptibility, medium susceptibility and high susceptibility. The final map of the landslide susceptibility was further validated with GPS location information gathered from the field survey of active landslide locations. This research would be helpful in the study region for adequate planning of future development of infrastructure, landslide hazard prevention, and geo-environmental development.

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