Jordan Journal of Civil Engineering

Landslide Susceptibility Mapping Using Information Value Method


Virender Kumar Sarda; Deepak Desh Pandey;


The aim of this study is to utilize the remotely sensed data and GIS techniques for instability assessment of terrain and prediction in the chosen study area, Rohtang to Baralacha, Lahaul Spiti District, Himanchal Pradesh, India. Several parameter maps were generated by the availability of different types of multi-temporal and various scales of remote sensing data. Inventory map was developed though the field work, past records and with the help of remote sensing data. Geological map, soil map, land use map, terrain map, slope map, aspect map, drainage density and snow melt parameter maps were generated or extracted from the existing ancillary data. In speeding up processing for hazard zonation and prediction assessment, GIS can be useful. To determine the degree of susceptibility to the landslides, information value method is used. The landslide hazard map is classified on the basis of its probability values into low, medium, high and very high risk zones. The results showed that over 3.09% of the area is liable to low landslide risk, 26.28% of the area is liable to medium landslide risk, 32.81% of the area is of high landslide risk and within this area about 37.81% has very high to severe risk. The landslide susceptibility map delineated in this paper can be used by various stakeholders, like state governments, researchers and citizens to develop and manage the developmental activities in the area in particular and in other similar areas in general.


Landslide, Susceptibility map, Remote sensing, GIS, Information value method, Area under curve (AUC).