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International Journal of Geomatics and Geosciences
Year : 2011, Volume : 2, Issue : 1
First page : ( 121) Last page : ( 132)
Online ISSN : 0976-4380.

RS & GIS Based Landslide Hazard Zonation of Mountainous Terrains A Study from Middle Himalayan Kullu District, Himachal Pradesh, India

Chandel Vishwa B. S.1Map Curator, Brar Karanjot Kaur1Associate Professor, Chauhan Yashwant2Product Specialist (Remote Sensing)

1Centre of Advanced Study in Geography, Department of Geography, Panjab University, Chandigarh

2ESRI Muscat, Oman  vishwa.geoinvader@gmail.com

Online published on 4 January, 2012.


Landslides are short lived and suddenly occurring natural phenomena; it is just a hazard when it occurs in an uninhabited place, however it turns into a disaster causing extraordinary landscape changes and destruction of life and property when it occurs in the vicinity of human habitation. Landslides are particularly common and cause massive damage in tectonically active Himalayas. This work conducts a landslide hazard zonation in western Himalayan district of Kullu in Himachal Pradesh using remote sensing and GIS. The western Himalayan district of Kullu with a location on the southern side of Pirpanjal mountain range, an established history and inherent susceptibility to massive landslides has been chosen for landslide hazard zonation. The satellite imageries of LANDSAT ETM+, IRS P6, ASTER along with Survey of India (SOI) topographical sheets formed the basis for deriving baseline information on various parameters like slope, aspect, relative relief, drainage density, geology/lithology and land use/land cover. The weighted parametric approach was applied to determine degree of susceptibility to landslides. The landslide probability values thus obtained were classified into no risk, very low to moderate, high, and very high to severe landslide hazard risk zones. The results show that over 80 per cent area is liable to highsevere landslide risk and within this about 32 per cent has very high to severe risk.



Landslide, Hazard Zonation, Remote Sensing & GIS.


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