GIS-based spatial prediction of landslide susceptibility using frequency ratio model of Lachung River basin, North Sikkim, India

Landslide causes damage to property and life in the Himalayan region as well as Sikkim Himalaya. Landslide susceptibility assessment is very important to mark out the landslide susceptibility area, and researchers take some plans for the future. Landslide susceptibility map has become essential to identify the landslide-prone zones and to find out the probable causes of a landslide in an area. The main objectives of this study are to produce landslide susceptibility mapping by frequency ratio method and to find out the dominant parameters which are responsible for the occurrences of frequent landslide in Lachung River basin, the main tributary of Teesta River in Sikkim Himalaya. The study utilized different types of data which include geological data, advanced spaceborne thermal emission and reflection radiometer-based digital elevation model, Sentinel-2A sensor data, published thematic map and precipitation data, and all data have been processed with the help of remote sensing and GIS tools. Ten influential causative factors of landslide occurrence are used for the susceptibility assessment, and they are slope angle, slope aspect, elevation, profile curvature, land use/land cover, normalized differences vegetation index, drainage density, road density, geology and rainfall. The GIS-based landslide susceptibility analysis has been discussed with ten dominant factors by using frequency ratio model. Finally, the landslide susceptibility map was classified into very high (0.591%), high (1.867%), moderately high (5.172%), moderate (19.682%), moderately low (25.685%), low (29.816%) and very low (17.187%). The map was compared with the validation of landslide location, and the model was verified by the receiver operating characteristic curve. The results revealed 88.9% prediction rate and 92.3% success rate, which means this model is validated with landslide susceptibility analysis in the study area.