Landslide susceptibility mapping using knowledge driven statistical models in Darjeeling District, West Bengal, India

Landslide is an important geological hazard in the large extent of geo-environment, damaging the human lives and properties. The present work, intends to identify the landslide susceptibility zones for Darjeeling, India, using the ensembles of important knowledge driven statistical technique i.e. fuzzy logic with Landslide Numerical Risk Factor (LNRF) and Analytical Hierarchical Process (AHP). In the study area, 326 landslides have been identified and a landslide inventory map has been prepared based on these landslides. The landslide inventory map has considered as the dependent factor and the geo-environmental factors like rainfall, slope, aspect, altitude, geology, soil texture, distance from river, lineament and road, land use/ land cover, NDVI and TWI have been considered as independent factors. Landslide susceptibility maps were prepared based on the Fuzzy- Landslide Numerical Risk Factor (LNRF) and Fuzzy- analytic hierarchy process (AHP) methods in a GIS environment. According to the results of LNRF and AHP based fuzzy logic 34 and 22% areas are highly susceptible to landslide in this district. The landslide maps of both models have been validated through ROC curve and RMSE. The areas under curves are 91% (for Fuzzy-LNRF) and 90% (for Fuzzy-AHP) and RMSE values of these models are 0.18 and 0.14 which are indicating the good accuracy of both models in the identification of landslide susceptibility zones. Moreover, the Fuzzy-LNRF model is promising and sufficient to be advised as a method to prepare landslide susceptibility map at regional scale.