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Abstract
Landslide susceptibility maps are very important tools in the planning and management of landslide prone areas. Qualitative and quantitative methods each have their own advantages and dis-advantages in landslide susceptibility mapping. The aim of this study is to compare three models, i.e., frequency ratio (FR), Shannon’s entropy and analytic hierarchy process (AHP) by implementing them for the preparation of landslide susceptibility maps. Shimla, a district in Himachal Pradesh (H.P.), India was chosen for the study. A landslide inventory containing more than 1500 landslide events was prepared using previous literature, available historical data and a field survey. Out of the total number of landslide events, 30% data was used for training and 70% data was used for testing purpose. The frequency ratio, Shannon’s entropy and AHP models were implemented and three landslide susceptibility maps were prepared for the study area. The final landslide susceptibility maps were validated using a receiver operating characteristic (ROC) curve. The frequency ratio (FR) model yielded the highest accuracy, with 0.925 fitted ROC area, while the accuracy achieved by Shannon’s entropy model was 0.883. Analytic hierarchy process (AHP) yielded the lowest accuracy, with 0.732 fitted ROC area. The results of this study can be used by engineers and planners for better management and mitigation of landslides in the study area.
Highlights
Regions are frequently affected by landslide disasters
The frequency ratio (FR) of the causative sub-factors is shown in the Table 2
Landslides areareone mostdisastrous disastrous phenomena in the Himalayan this study, statistical approaches and expert based approaches are compared for landslide this study, statistical approaches and expertThe based approaches compared for landsl susceptibility mapping in a geographic information systems (GIS) environment
Summary
Regions are frequently affected by landslide disasters. Landslides are responsible for huge loss of life and damage to infrastructure [1,2]. The accurate prediction of landslides can help in the planning and management of landslide hazards, and can be used for the reduction of risk [5]. Landslide susceptibility maps help in the identification of landslide prone areas. Landslide susceptibility maps can be very efficient tools for planners and risk managers [5]. The occurrence of landslides is a complex phenomenon which depends upon various factors. Geological factors, drainage characteristics, land-use of the region, construction activities, etc., can all be responsible for the occurrence of landslides [6]
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