Landslide Susceptibility Zonation of Tehri Reservoir Rim Region Using Binary Logistic Regression Model

A remote sensing and GIS based landslide susceptibility zonation (LSZ) of the Tehri reservoir rim region has been presented here. Landslide causal factors such as land use/land cover, photo-lineaments, landslide incidences, drainage, slope, aspect, relative relief, topographic wetness index and stream power index were derived from remote sensing data. Ancillary data included published geological map, soil map and topographic map. Correlation between factor classes and landslides was computed using binary logistic regression model and a probability estimate of landslide occurrence on cell-by-cell basis for the entire study area was obtained. The probability map was further classified into very low, low, moderate, high and very high susceptible zones using statistical class break technique. Accuracy assessment of the model was performed using ROC curve technique, which in turn gave acceptable 80.2% accuracy. LSZ indicates that the area immediate to the reservoir side slope is highly prone to landslides.