Earth observation data and GIS based landslide susceptibility analysis through frequency ratio model in lesser Himalayan region, India

Landslide incidents are resulted into significant monetary losses, human deaths, and irrevocable changes to the natural landscape. Basically, geological, climatic, and human factors contribute to landslides. In this research, the landslide susceptibility mapping was applied using satellite data and a probability-frequency ratio model with overlay analysis for the lesser Himalayan region in GIS. For this purpose, ten factors that affect the likelihood of landslides have been taken into account. The topographical data analysis provides information on parameters like slope, curvature, aspect, and distance from drainage. The Giovanni website's rainfall database was used to calculate the quantity of precipitation, and land use/land cover (LULC) of ESRI was used for susceptibility analysis.The weight of each factor was determined using Frequency ratio model and afterwards the overlay was performed using GIS. Landslide inventory was downloaded from Bhukosh-Geological Survey of India portal. With the aid of landslide spot data, the results of the inspection were verified and susceptibility map was categorised in different class. The accuracy of the susceptibility map was 73.2%. Landslide susceptibility map (LSM) was classified into four classes namely non-hazardous zone, moderately hazardous zone, highly hazardous zone, and very hazardous zone. This model's data can be used to estimate the likelihood of hazards to local residents, the environment, and any existing foundational structures.