Application and validation of AHP and FR methods for landslide susceptibility mapping around choke mountain, northwestern ethiopia

Abstract

The present research was conducted around Choke Mountain, East Gojjam, Northwestern Ethiopia. This study aimed to apply and validate analytical hierarchy process (AHP) and frequency ratio (FR) Methods and produce landslide susceptibility maps of the area. At first, a landslide inventory map was produced with information on past and active landslide locations. To produce a susceptibility map, nine influencing factors including lithology, slope, elevation, distance to drainage, distance to road, profile curvature, plane curvature, NDVI, and aspect were determined and integrated into the ArcGIS platform. All these influencing factors were statistically analyzed to determine their relationship to past landslides. The landslide susceptibility maps generated in the GIS environment by the AHP and FR methods were classified into five susceptibility classes: very low, low, moderate, high, and very high. Accordingly, the AHP method showed that very high susceptibility zones and high susceptibility zones cover 9.8% and 19.3% of the area, respectively. Whereas, moderate, low, and very low susceptibility zones cover 26.1%, 28.0%, and 16.8% of the area, respectively. Similarly, the FR method showed that very high susceptibility zones and high susceptibility zones cover 12.2% and 22.5% of the area, respectively. Whereas, moderate, low, and very low susceptibility zones cover 27.6%, 24.2%, and 13.4% of the area, respectively. The final results were compared and validated using the area under the curve (AUC) method. According to the AUC graph, the AHP and FR methods had success rates of 85.8 and 82.0%, respectively, and prediction rates of 88.2 and 84.8%. According to the AUC validation results, the map obtained from the AHP method is more accurate than that obtained from the FR method. Thus, the validation of the landslide susceptibility map demonstrated that the methodologies used resulted in acceptable results. This type of map can be useful for damage and risk prevention management and land use planning.