Abstract
<p>Landslide is the most significant natural hazard that causes socio-economic devastation in mountainous terrains around the world. In India, lands of mountains especially the Himalayas are vulnerable to landslide due to the high intensity of seismic shaking, prolonged rainfall and complex lithological setting. In the present study, Landslide Susceptibility Zonation (LSZ) has been carried out using Random Forest technique on Geographical Information System by combining different landslide causative factors i.e. slope angle, slope aspect, drainage density, distance to drainage, elevation, shape of slope, distance to lineament, lineament density, surface geology, soil, geomorphology, landform, rainfall, epicenter proximity, Normalize Differences Vegetation Index, Landuse/Landcover, road density and distance to road are integrated to model Landslide Susceptibility Index, thus classifying the terrain in terms of  ‘None’, ‘Low’, ‘Moderate’, ‘High’, ‘Very High’ and ‘Severe’. It is observed that around 45% of the terrain falls under the ‘High’ to ‘Severe’ landslide susceptibility zones. Receiver Operating Characteristics (ROC) places an 85% confidence level that predicts a strong correlation between LSZ and landslide inventory dataset of the region. Thus, this study suggests that a comprehensive approach for slope failure mapping can be used to develop appropriate mitigational strategies for landslide disaster management in the socio-economic context.</p><p><strong>Keywords</strong>: Landslide Susceptibility Zonation; Northwest Himalaya.</p>
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