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Landslides in Himalaya cause widespread damage in terms of property and human lives. It the present study, an attempt is made to derive information on causative parameters and preparation of landslide-susceptible map using fuzzy data integration in one of the seismically active region of Garhwal Himalaya that was recently devastated by a huge landslide. High-resolution remotely sensed data products acquired from Indian Remote Sensing Satellite before and after the landslide event were processed to improve interpretability and derivation of causative parameters. Spatial data sets such as lithology, rock weathering, geomorphology, lineaments, drainage, land use, anthropogenic factor, soil type and depth, slope gradient, and slope aspect were integrated using fuzzy gamma operator. The final map was reclassified in to five classes such as highly to lowly susceptible classes based on cumulative cutoff. The result shows around 72% of known landslide areas including the large Uttarkashi landslide in the high and very high susceptibility classes comprising of only 37% of the total area. The precipitation data from ground-and satellite-based observations were compared; the precipitation threshold and the role of seismic activity were analyzed for initiation of landslide.

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