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Landslide is one of the severe natural disaster that posse’s serious threats to human lives and economic resources in the Himalayan regions of India. It has created significant constraints in the pace of economic development of the particular region; sometimes it completely bifurcates the region using transport communication at the specific period of times 1 . Its block road and cut-off the area particularly to a watershed which is sometimes served by a single route. In this regards, landslide susceptibility mapping provides a quantitative assessment of the spatial probability of the landslide occurrence 2 . It is based on the understanding of complex geo-environmental processes and their controlling factors 3 . Precise landslide inventory dataset and appropriate modeling techniques are required for the analysis of landslide susceptibility 4 . Statistical methods have provided signification contribution to the development of spatial model and analysis of critical parameters under the circumstances they influence slope instability. The development of Geographic Information Systems (GIS) and statistical software allowing the integration of spatial and non-spatial models improve the modeling at various scales 5 . The recent development of remote sensing technology provides the user a detailed spatial analysis of macro-to-micro level details such as large-scale landslide to small debris fall, that is even smaller in dimension 6 . Sometimes there is a limitation of field data collection, particularly in that case mapping and data collection can be done using the satellite imagery for the inaccessible areas. Remote sensing data have been widely used for prediction of landslides 7,8 . The statistical methods, which are used for the susceptibility analysis includes; discriminant analysis 5 , Abstract:

Characteristics of Large Landslides and Application of Frequency Ratio Model for Susceptibility Assessment, Lower Jalal Catchment (Himachal Pradesh)