| Abstrakt: |
Landslide susceptibility maps are important for planning and dealing with natural disasters in mountainous areas like the Soran study area. The current study uses frequency ratio (FR) models to analyze the susceptibility of the Kamarbandi Soran-Papshtia route and its surrounding area to landslides. Three data sources are used to create a landslide inventory map, such as previous studies, field investigation, and a satellite image. The satellite picture utilized in this investigation is LANDSAT-8 which was downloaded from the USGS website consisting of 11 bands with 16-days and 30 meters temporal and spatial resolutions respectively. As a consequence, 72 landslides were identified and mapped, with 53 (70%) being chosen at random for creating landslide susceptibility model designs and the remaining 19 (30%) being used to confirm the models. Eight landslide conditioning elements were studied in this case study to build up frequency ratio (FR) models to produce a landslide susceptibility map. These factors encompass Aspect, Slope, Land use, Elevation, Curvature; NDVI map; Distance to road; and Distance from stream. According to the area Under Curve AUC, the result reveals that the measure of the level of disorder in the model with an AUC value of 0.7 has the maximum accuracy of prediction at 73.3 percent. The susceptibility maps generated by FR produce an accurate prediction of the susceptibility of the Kamarbandi Soran-Papshtia road segment to landslides, which can be used as a tool for planning land use and reducing disasters. [ABSTRACT FROM AUTHOR] |
