GIS based landslide susceptibility zonation mapping using frequency ratio, information value and weight of evidence: a case study in Kinnaur District HP India

Landslides are the most catastrophic natural disasters that constitute geological, geomorphological slope instability risks and affects the economy worldwide. The causes of landslides are growing population, instability slopes, climate change, earthquakes, and mining. The aim of the study is to determine and evaluate the landslide susceptibility zonation of Kinnaur district in HP, enabling for the provision of preventive and remedial measures, at present assessment three statistical methods including frequency ratio, information value and weight of evidence were used to map the susceptibility of landslide hazard. The landslide inventory was created using data acquired from the Geological Survey of India (Bhukosh). According to the current literature, a variety of geo-environmental factors were selected to create landslide susceptibility including slope, aspect, lithology, soil, drainage density, lineament density, curvature, rainfall, and land use and land cover. Landslide susceptibility maps were categorized into five categories based on the mapping data: very high, high, medium, low, and very low. The area under the curve (AUC) approach was used to validate the maps prepared by the three statistical methods. The frequency ratio model-prepared landslide susceptibility zonation map has a prediction rate of 88.90%, while the information value and weight of evidence-prepared maps have prediction rates of 85.28% and 85.74%, respectively. By comparing the prediction rate, the map obtained using frequency ratio method, was found more appropriate for the study area. The outcomes of the study emphasize the landslide area and assist local authorities and decision makers in taking necessary precautionary measures and improving contingency plans.