Landslide susceptibility mapping along national highway-1 in Jammu and Kashmir State (India)

Abstract

A remote sensing and GIS-based landslide susceptibility mapping (LSM) has been carried out using frequency ratio (FR) and weight of evidence (WoE) methods to identify and delineate the potential failure zones along National Highway – 1. The thematic layers of various landslide causative factors have been generated for modeling in GIS. In addition, a landslide inventory along the road network was prepared using satellite imagery, Google earth, and extensive field visits. LSM classified the area into five susceptibility classes: very low, low, moderate, high, and very high classes. The validation result further substantiates the study and inferred that area under success rate curve shows a satisfactory relation between landslide affecting factors and landslide occurrences in case of FR and WoE models having an accuracy of 86.57% and 76.86%, respectively. A landslide density method has also been adopted for validation of LSM which showed acceptable results with decreasing trend of landslide density from very high to very low susceptible zone for both FR and WoE models. The LSM generated will be helpful for various stakeholders like planners, engineers, designers, and local public for future construction and maintenance in the study area.