Akademik Veri Yönetim Sistemi
Earth Sciences Research Journal, cilt.29, sa.3, ss.261-273, 2025 (SCI-Expanded, Scopus)
Landslides are the most prevalent natural hazards in the Sub-Himalayan region, posing extensive socio-economic losses. Their occurrence is highly influenced by weak geological formations, steep and dissected topography, irregular land-use, high seismic activity, and seasonal precipitation and snowmelt. Despite the high threat, there is an absence of landslide susceptibility maps for most of northern Pakistan, hindering effective measures for landslide hazard prevention. In this study, a relevant deep-seated landslide inventory for landslide susceptibility assessment of the Galiat Region was prepared based on field studies and multi-temporal Google Earth images, identifying 68 landslide polygons. Due to the localized nature of landslides, substantial predictions cannot be made with classical statistical modelling. Therefore, the landslide susceptibility map of the study area was modelled using the maximum entropy method, which allows predictions based on limited observational data. The analyses were repeated, with three randomly selected data sets being 30% and 70% for training and testing data, respectively. Fourteen environmental variables were considered, including geology, digital elevation model (DEM), and first and second DEM derivatives. The accuracy of the obtained models reached 0.80 ±0.002, evaluated by the AUC technique. The high to very high susceptible classes correspond to 26.16 % of the study area, including 74.3 % of the mapped landslides. The resultant landslide susceptibility map will raise understanding of dynamic and potential landslides for citizens, engineers, and land-use agencies.