Study of Land Surface Temperature on Landslide Susceptibility Zonation in Ramban District of Jammu and Kashmir, India

Abstract

The increased frequency of landslides in Jammu and Kashmir region of India not only cause ravage to infrastructure but are also a major threat to geo-environment and socio-economic life of humans. This research work constructs two susceptibility maps in static and dynamic mode where the causative factors were considered in previous while adding the multi-temporal land surface temperature (LST) to the later. Six causative factors were considered to prepare a susceptibility map in static mode. A bivariate statistical model, information value model was used to prepare the susceptibility maps for the area. Both the susceptibility maps were classified into three susceptibility zones of low, moderate and high risk. All the susceptibility maps were further validated using actual distribution of landslides in the area and success rate curve. It was observed that the addition of LST to the static susceptibility model increased the accuracy to predict the landslide sites. © 2022 IEEE.