landslide hazard mapping using geospatial models
The purpose of this study is to map landslide hazard in Panchthar area, Nepal. The landslide hazard map was made and validated using frequency ratio, logistic regression and artificial neural network models with a geographic information system (GIS). The landslide locations were identified in the study area from interpretation of aerial photographs and checked by field survey. A spatial database of the topography, geology and land use was constructed and the 10 landslide-related factors were extracted. Using these factors, the hazard to landslides was analysed using the 3 models. The validation result showed that the frequency ratio, logistic regression and artificial neural network models had 82.2\%, 81.6\% and 78.3\% accuracies, respectively, representing an overall satisfactory agreement, with the frequency ratio model giving the best result. The generated maps could be used to estimate the hazard to population, property and existing infrastructure such as the transportation network.
landslide hazard frequency ratio logistic regression gis artificial neural network aerial photograph