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Nepal was hit by a 7.8 magnitude earthquake on 25~(th) April,2015.The main shock and many large aftershocks generated a large number of coseismic landslips in central Nepal.We have developed a landslide susceptibility map of the affected region based on the coseismic landslides collected from remotely sensed data and fieldwork,using bivariate statistical model with different landslide causative factors.From the investigation,it is observed that most of the coseismic landslides are independent of previous landslides.Out of 3,716 mapped landslides,we used 80% of them to develop a susceptibility map and the remaining 20% were taken for validating the model.A total of 11 different landslide-influencing parameters were considered.These include slope gradient,slope aspect,plan curvature,elevation,relative relief,Peak Ground Acceleration(PGA),distance from epicenters of the mainshock and major aftershocks,lithology,distance of the landslide from the fault,fold,and drainage line.The success rate of 87.66% and the prediction rate of86.87% indicate that the model is in good agreement between the developed susceptibility map and theexisting landslides data.PGA,lithology,slope angle and elevation have played a major role in triggering the coseismic mass movements.This susceptibility map can be used for relocating the people in the affected regions as well as for future land development.
Nepal was hit by a 7.8 magnitude earthquake on 25 April (th) April, 2015. The main shock and many large aftershocks generated a large number of coseismic landslips in central Nepal. We have developed a landslide susceptibility map of the affected region based on the coseismic landslides collected from remotely sensed data and fieldwork, using bivariate statistical model with different landslide causative factors. From the investigation, it is observed that most of the coseismic landslides are independent of previous landslides. Of of 3,716 mapped landslides, we used 80% of those to develop a susceptibility map and the remaining 20% were taken for validating the model. A total of 11 different landslide-influencing parameters were considered. These include slope gradient, slope aspect, plan curvature, elevation, relative relief, Peak Ground Acceleration ( PGA), distance from epicenters of the mainshock and major aftershocks, lithology, distance of the landslide from the fault, fold, and drainage line. The success ra te of 87.66% and the prediction rate of86.87% indicate that the model is in good agreement between the developed susceptibility map and the existing landslides data. PGA, lithology, slope angle and elevation have played a major role in triggering the coseismic mass movements. This susceptibility map can be used for relocating the people in the affected regions as well as for future land development.