The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-5
https://doi.org/10.5194/isprs-archives-XLII-5-481-2018
https://doi.org/10.5194/isprs-archives-XLII-5-481-2018
19 Nov 2018
 | 19 Nov 2018

LANDSLIDE HAZARD ZONATION IN AND AROUND KEDARNATH REGION AND ITS VALIDATION BASED ON REAL TIME KEDARNATH DISASTER USING GEOSPATIAL TECHNIQUES

D. Uniyal, S. Purohit, S. Dangwal, A. Aswal, M. P. S. Bisht, and M. M. Kimothi

Keywords: Landslide Hazard Zonation, GIS, Orthorectification, Drainage Density, Geomorphology

Abstract. Landslides are one of the frequently happening disasters in this hilly state of Uttarakhand which accounts to the loss of lives and property every year especially during the rainy season which lead to affect the families. With the development of satellite observation technique, advanced data analysis tool and new modeling techniques landslide hazard zonation map can be prepared.

In the present study, Landslide Hazard Zonation (LHZ) for Kedarnath to Augustmuni region of Rudraprayag district of Uttarakhand state was carried out using Remote Sensing and GIS technique. For the preparation of LHZ map, year 2010 high resolution satellite data have been used. After preprocessing of the data various thematic layers are prepared in GIS environment. The weighted-rating system technique were used for the LHZ map showing the five zones, namely “very low hazard”, “low hazard”, “moderate hazard”, “high hazard” and “very high hazard” . This map has been validated after the tragedy of Kedarnath in Uttarakhand, Total no. of 224 Landslides has been marked from Kedarnath to Augustmuni region just after the kedarnath tragedy in year 2013. When this landslides thematic layer is overlaid on LHZ, the study shows that approximately 50% landslides was there where in LHZ map high and very high hazard zones have been identified. After the tragedy our team workers have gone to the field, with the help of DGPS around 40 ground control points have been taken to validate our result. So by using this geospatial technique around 50% people’s life can be saved.