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Landslides are the most prevalent natural hazard in hilly regions of India. This study examines the landslide susceptibility of the Pithoragarh, Uttarakhand, India, using multi-criteria decision based analysis by analytical hierarchy process (AHP), and logistic regression (LR) analysis. The LSZ modelling was performed using fourteen landslide causative factors. Based on past landslide data, landslide locations were identified, which were further divided into a 70/30 ratio, with 70 representing training and 30 representing validation. Validation of the findings of the predicted maps of landslide susceptibility using Area under Curve (AUC) indicates that the predicted map using the LR approach has the highest prediction rate compared to other methods used for landslide susceptibility prediction. Also, validation of all the models was done using Landslide Density Index (LDI) which shows the validity of all models. Thus, the results of all models can be used to predict landslide susceptibility in Pithoragarh.

applied earth science

Assessment of landslide susceptibility of Pithoragarh, Uttarakhand (India) using logistic regression and multi-criteria decision-based analysis by analytical hierarchy process