Comparative GIS-Based Landslide Susceptibility and Relative Risk Assessment Using Frequency Ratio, Shannon Entropy and Statistical Information Index Models

Abstract

Landslides are recurrent geomorphic hazards in the Nepal Himalaya, where fragile geology, steep terrain, monsoonal rainfall and expanding road construction increase slope instability. This study assesses landslide susceptibility and relative risk in Tamakoshi Rural Municipality, Dolakha, Nepal, by comparing three GIS-based bivariate models: frequency ratio (FR), Shannon entropy (SE) and statistical information index (SII). A landslide inventory of 121 events was prepared from Google Earth imagery, satellite-image interpretation and field verification, and divided into 70% training and 30% validation subsets. Ten conditioning factors were analysed at 30 m spatial resolution: slope, aspect, curvature, elevation, topographic wetness index, lithology, soil type, land use/land cover, distance from roads and distance from rivers. Model discrimination was evaluated using receiver operating characteristic-area under the curve analysis. Landslides were concentrated on steep, mid-elevation slopes, particularly within 250 m of rivers and 100 m of roads, indicating the influence of fluvial undercutting, road excavation and drainage disturbance. SII produced the highest success and prediction AUC values (0.654 and 0.628), followed by FR (0.645 and 0.623) and SE (0.634 and 0.613), although all three models showed only modest discrimination. An AHP-based exposure–vulnerability index was prepared from settlement, population, road, school, hospital and temple indicators. The resulting relative risk zonation identified approximately 15% of the municipality as high or very high risk, mainly in wards 1, 3 and 5. The findings provide a spatial basis for field prioritization, risk-sensitive land-use planning and local disaster risk reduction.