Volume XLII-5
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-5, 461-468, 2018
https://doi.org/10.5194/isprs-archives-XLII-5-461-2018
© 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, 461-468, 2018
https://doi.org/10.5194/isprs-archives-XLII-5-461-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  19 Nov 2018

19 Nov 2018

ASSESSMENT OF SNOW AVALANCHE SUSCEPTIBILITY OF ROAD NETWORK - A CASE STUDY OF ALAKNANDA BASIN

V. Singh1,2, P. K. Thakur2, V. Garg2, and S. P. Aggarwal2 V. Singh et al.
  • 1ITBP, Leh, on deputation at IIRS Dehradun for M.Tech, India
  • 2Water Resources Department, Indian Institute of Remote Sensing, Dehradun, India

Keywords: AHP, ASTER GDEM, Hazard, Snow Avalanche, Susceptibility

Abstract. Snow avalanche occurring in a micro-climatic condition causing hydro-geo (Hydrological and geological) hazard to the deployed armed forces and nearby inhabitant to the North Western Himalaya about 3000 MSL. In recent years, frequencies of snow avalanche have increase and consequently the death toll have also surged to many folds. These unavoidable occurrences not only cause road blocks which disrupts transportation connectivity in the rugged terrain of Himalaya as well as loss of infrastructure and life. Here, in this study an attempt has been made to assess the susceptibility of road network of Alaknanda Basin from snow avalanche. Potential avalanche formation zones have been generated using Analytical Hierarchical Process (AHP) of Multi-Criteria Decision Making (MCDM. Advance Thermal Emission Reflection Radiometer (ASTER) Global Digital Elevation (GDEM) 30 meter has been used to generate static parameters like slope, aspect, curvature etc. using GIS platform. ISRO-Geosphere Biosphere Program Land Use Land Cover (LULC) used as another static parameter. Weights are generated using comparison matrix and ratings to different static parameter layers assigned on the basis of field visit and literature review while the road network are digitized from Google earth. A methodology has been prepared to categorize the road stretches on the basis of potential snow avalanche formation zone including hydrological processing. Buffer zone are assigned with weights according to potential snow avalanche formation zones. Later roads are intersected with sub basin with assigned values that resulted very high avalanche potential zonation, considered as most susceptible to snow avalanche hazard.