Landslide susceptibility maps using different probabilistic and bivariate statistical models and comparison of their performance at Wadi Itwad Basin, Asir Region, Saudi Arabia

摘要: The purpose of the current study is to produce landslide susceptibility maps using different probabilistic and bivariate statistical approaches; namely, frequency ratio (FR), weights-of-evidence (WofE), index-of-entropy (IofE), Dempster–Shafer (DS) models, at Wadi Itwad, Asir region, in southwestern part Saudi Arabia. Landslide locations were identified mapped from interpretation high-resolution satellite images, historical records, extensive field surveys. In total, 326 ArcGIS divided into two groups; 75 % 25 % used for training validation respectively. Twelve layers landslide-related factors prepared, including altitude, slope degree, length, topography wetness index, curvature, aspect, distance lineaments, roads, streams, lithology, rainfall, normalized difference vegetation index. relationships between inventory map calculated models (FR, WofE, IofE, DS). model results verified with locations, which not during training. addition, receiver operating characteristic curves applied, area under curve (AUC) was success (training data) prediction (validation rate curves. showed that AUC rates are 0.813, 0.815, 0.800, 0.777, while 0.95, 0.952, 0.946, 0.934 FR, DS Subsequently, five classes, very low, moderate, high, high. Additionally, percentage validating landslides high classes each calculated. revealed produced reasonable accuracy. outcomes will be useful future general planned development activities environmental protection.