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Seismic risk zonation using the geospatial tool: A case study over East and South district of Sikkim
Rachna Kachhap 1 , Amitesh Gupta * 2 , Rajarshi Bhattacharjee * 2 , Triparna Sett 2
1  Birla Institute of Technology Mesra
2  Indian Institute of Remote Sensing

10.3390/mol2net-05-06231
Abstract:

Seismic risk assessment in the high mountains of Himalaya is necessary to
accommodate safe and suitable sites for homing with also to direct the pathway of plan and policy
for development sustainably. The continuous orogeny results often earthquakes, mostly, the area
around fault lines as have been documented by USGS. Hence, to prepare the vulnerability and
susceptible zonation in East and South Sikkim districts Analytical Hierarchy Process (AHP)
technique has been adopted. LANDSAT 8 onboard OLI multispectral data is used to prepare the
Land-use Land-cover map of study area using supervised classification techniques, while
CartoSAT-1 version 2 DEM is used to look into the physiographical aspects of this region. With
also, Geological Survey of India prepared soil and geological map is used to prepare the soil and
lineament map. Not only that, ground motion data of four different parameters, have also been
acquired form USGS on about of an earthquake event on 18th September 2011, which had
epicenter at 27.730°N, 88.155°E. Certainly, it has been achieved that, area with soil type of
udorthents entisol in the 10 km buffer zone from the major faults victimized of seismic hazard
mostly. By the AHP comparison matrix, proximity of any area to the fault lines found to be most
influential followed by the ground motion vectors while the LULC categories are the least
influential. Using the weighted overlay analysis, area along the western boundary of East district
and north-west of South district in Sikkim found to be under high seismic risk zone. Risk zones has
been verified with the help of archive earthquake data from USGS and approximately 22% area in
these two districts comes under high risk zone.

Keywords: Seismic, risk assessment, Remote Sensing, AHP, LANDSAT.
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