Landslide susceptibility zonation mapping and its validation in part of Garhwal Lesser Himalaya, India, using binary logistic regression analysis and receiver operating characteristic curve method Abstract A landslide susceptibility zonation (LSZ) map helps to understand the spatial distribution of slope failure probability in an area and hence it is useful for effective landslide hazard mitigation measures. Such maps can be generated using qualitative or quantitative approaches. The present study is an attempt to utilise a multivariate statistical method called binary logistic regression (BLR) analysis for LSZ mapping in part of the Garhwal Lesser Himalaya, India, lying close to the Main Boundary Thrust (MBT). This method gives the freedom to use categorical and continuous predictor variables together in a regression analysis. Geographic Information System has been used for preparing the database on causal factors of slope instability and landslide locations as well as for carrying out the spatial modelling of landslide susceptibility. A forward stepwise logistic regression analysis using maximum likelihood estimation method has been used in the regression. The constant and the coefficients of the predictor variables retained by the regression model have been used to calculate the probability of slope failure for the entire study area. The predictive logistic regression model has been validated by receiver operating characteristic curve analysis, which has given 91.7% accuracy for the developed BLR model.

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High-altitude Himalayan terrain exhibits extreme geometric distortion along north-facing (dilation) and south-facing (compression) slopes as observed in satellite stereo data with high look angles. In the present study, Cartosat-1 stereo pairs have been used for generating Digital Elevation Model (DEM) using Differential Global Positioning System based Ground Control Points. DEM quality assessment through stereoscopic visualization revealed distortions especially in E-W oriented steep valleys. The study highlights issues and challenges in DEM generation for Himalayan terrain and articulates density of editing required. Quantitative and qualitative assessment of the DEM produced showed considerable improvements after post processing.

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