Optimized landslide susceptibility mapping and modelling using PS-InSAR technique: a case study of Chitral valley, Northern Pakistan

Chitral valley lies in the eastern Hindu Kush range, one of the hotspot of landslide activities that leads to loss of lives and economy. Comprehensive landslide inventory and Landslide susceptibility provide the basic information to analyses and medicate the landslide activities which are not available for the area. Probabilistic and statistical methods have been using to develop susceptibility maps but limitations are countered to assess high accuracy. In this study Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique has been applied to estimate the slope deformation velocity (Vslope), which can be used to optimize the landslide susceptibility map for the study area. The frequency ratio and logistic regression models were applied for comparative assessment and to forecast the correlation between causative factors and landslide occurrence. Area Under Curve (AUC) of Receiver Operating Characteristic (ROC) curve approach was used for accuracy comparison of both models which showed 75.45% and 85.61% accuracy for FR and LR respectively. LR method's result was found superior and combined with the results of PS-InSAR to extract new Landslide Susceptibility Mapping (LSM) for the area which removed misclassifications in the results. This optimized susceptibility model will be helpful to mitigate the landslide disaster and provide support to authorities in the management of different development programs in the study area.

Automated summary

The study applied PS-InSAR technique to estimate slope deformation velocity for optimizing landslide susceptibility mapping in the area. Frequency ratio and logistic regression models were used for comparative assessment and predicting correlations with landslide occurrence. LR method showed superior results and in combination with PS-InSAR, an optimized susceptibility model was developed to mitigate landslide disasters and support management of development programs in the area.