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The purpose of this study was to evaluate landslides influencing factors and prepare landslide susceptibility zonation map, Dessie area is situated in South wello Ethiopia. For this study, lithology, slope, curvature, elevation, land use, slope aspect, distance from road, river and tectonic fault were considered as landslide causative factors. The landslide inventory database was developed from extensive fieldwork and Google Earth imagery and randomly partitioned as training datasets (70%) and testing datasets (30%) using the Subset features Tools in ArcGIS. The training datasets combined with landslide causative factors to produce landslide susceptibility zonation maps. The testing datasets used to validate the maps using Area under the curve (AUC) of the Receiver Operating Characteristic (ROC) method. The spatial relationship between landslide and landslide causative factors analyzed in frequency Ratio and logistic regression models and the results used to prepare landslide susceptibility zonation (LSZ) maps in GIS environments. Landslide susceptibility zonation maps were classified into five categories: very low, low, medium, high and very high zones. Finally, the results of analysis were validated by comparing known landslide location with LSZ maps using AUC of ROC. The prediction accuracy value obtained shows that the logistic regression model (84.4%) is better in prediction than frequency ratio model (80.8%). The analysis shows that the prediction rate of FR model achieved 80.8% while the LR model achieved 84.4%. These maps show areas prone to landslides that will be used for proper land use planning and further sustainable development activities in the area. |
