Volume XLII-5
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-5, 409-419, 2018
https://doi.org/10.5194/isprs-archives-XLII-5-409-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-5, 409-419, 2018
https://doi.org/10.5194/isprs-archives-XLII-5-409-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  19 Nov 2018

19 Nov 2018

LANDSCAPE VULNERABILITY ASSESSMENT USING REMOTE SENSING AND GIS TOOLS IN THE INDIAN PART OF KAILASH SACRED LANDSCAPE

A. Hussain1, G. Singh2, and G. S. Rawat1 A. Hussain et al.
  • 1Wildlife Institute of India, Dehradun, India
  • 2Uttarakhand Space Application Centre, Dehradun, India

Keywords: KSL, AHP, Vulnerability, Fire, Flood, Landslide

Abstract. The Indian part of Kailash Sacred Landscape (KSL) is prone to flash floods, landslides and forest fires leading to various environmental and socio-economic problems. This study aims to identify areas vulnerable to these disasters by preparing hazard maps to curtail their impact on the overall landscape. The Indian part of KSL covering seven forest ranges in Pithoragarh district which is spread over an area of 7,212km2. This paper integrated the Geographic Information System and Remote Sensing and the multi criteria analysis through AHP to determine the disaster vulnerable areas in the landscape. All the thematic layers and final maps are prepared in ArcGIS 10.2. A total of ten variables for a landslide, six variables for flood and seven variables (topographic, climatic, and anthropogenic) were used to carry out the pairwise comparison for relatively weighting the variables through AHP. Consistency ratio (CR=0.01) for landslide and forest fire and for flood (CR=0.06) which shows the matrix was consistent. We identified 174km2 of the area which is highly fired prone to forest fire, 76km2 of area vulnerable to landslide and 24km2 of the area comes under hotspot of the flood. The sites vulnerable to key drivers identified and mapped through this study will form the basis for further conservation and development planning at landscape level by policy makers.