Comparative Analysis of GIS-based Quantitative Approaches for Landslide Susceptibility Assessment along National Highway-1(NH-1), North Kashmir Himalaya, India

Landslide susceptibility assessment (LSA) is crucial for identifying landslide-prone locations to avoid future landslide menace in the changing climate regime of Kashmir Himalaya, particularly along the National Highway-1 (NH-1). Therefore, the present study aims to create, contrast, and validate the resultant landslide susceptibility maps (LSMs) to develop an applicable landslide disaster risk reduction (DRR) plan. Besides, we employed twelve contributing factors (CFs) or thematic maps based on their correlation to the historical landslide occurrences. Further, two GIS-based statistical models, viz., frequency ratio model (FRM) and relative effective model (REM), were used to obtain landslide susceptibility indexes and zoning in the study area, respectively. A landslide inventory database was compiled from field surveys and other secondary sources for simulating and testing models. Further, the performance of the generated LSMs was evaluated using the receiver operating characteristic (ROC) curve. The accuracy of the FR and RE models generated LSMs was 90.40% and 77.20%, respectively. Furthermore, the verification results showed a good agreement between the produced LSMs and the existing historical landslide locations. Additionally, the study concluded that the FR model outperforms the RE model in prediction accuracy, highlighting its importance in training landslide susceptibility modeling. Moreover, the resulting LSMs would benefit regional-scale LSA, land use development, and regional disaster management.