遥感与地理信息系统学报

抽象的

Landslide Susceptibility Mapping Using Shannon’s Entropy Methods Using Hybrid Technique: A Case Study of Kinnaur District, Himachal Pradesh, India

Vicky Anand, Aastha Sharma, Amit Kumar Sahni, Sahnoor Bano, Sunil Kumar Jangra

Global climate change has developed into one of the most complex problems facing mankind in the current scenario. This change has an irrefutable disturbance on the stability of natural and engineered slopes, including landslides. In mountainous terrain such as the Himalayas, landslides are among the most harmful hazards. Most landslides occur under the influence of earthquakes or rainfall, and they are often among the most devastating natural hazards. Increasing awareness of landslides’ socioeconomic impacts has attracted global attention to landslide studies. A landslide risk assessment in Himachal Pradesh’s Kinnaur region was conducted using remote sensing and Geographic Information Systems (GIS). For the Landslide Susceptibility Mapping, a hybrid approach is used. Using a hybrid approach, weighted overlay is combined with Shannon’s entropy, an eminent technique based on evidence. To prepare a susceptibility map, eight landslide-related criteria are used in conjunction with the inventory of landslides that contained recent and historical landslides. The validation results show that the models derived using the following approach have the highest prediction capability.