Landslide Susceptibility Modeling Using Weight Of Evidence and Logistic Regression Models in Halila Catchment, Gamo Zone, South Ethiopia

dc.contributor.advisorLeulalem Shano (PhD) Yadeta Chemdesa (PhD)
dc.contributor.authorDame Tekalign
dc.date.accessioned2025-12-16T13:41:06Z
dc.date.issued2024-02
dc.description.abstractLandslides are one of the most harmful natural phenomena that devastate both property and human lives. Geology, topography, surface and subsurface water condition, land use/land cover are the main causative factors which are highly associated with the most landslide occurrence in study area. This study is aimed at identifying the areas which are most vulnerable to landslides and the important factors related to landslides throughout the Halila catchments of the Gamo zone using statistical methods. Seven landslide influencing factors were chosen for landslide susceptibility mapping, including Slope, Aspect, Curvature, distance from Stream, distance from Lineament, Lithology and Landuse landcover were considered, using 592 landslide inventories. These factors were selected based on the environmental characteristics and data availability. Their contrast weight and regression coefficient were determined from Weight of Evidence and Logistic Regression respectively and added using raster calculator on a spatial analysis tool of ArcGIS. The final landslide susceptibility map was reclassified as very low, low, moderate, high and very high susceptibility classes. Distance from lineament is the major factor concerning landslide occurrence as can be seen from its weights and regression coefficient. This susceptibility map was validated using landslide density index and area under the curve (AUC). The result from Weight of Evidence and Logistic regression model validation showed a validation rate accuracy of 82.4% and 83.4% respectively. This study conclude that the effectiveness of weight of evidence and Logistic regression model for landslide susceptibility map. Finally, implementing afforestation strategies on bare land, constructing surface drainage channels & ditches, providing engineering reinforcements such as gabion walls, retaining walls, anchors and bolts whenever necessary and prohibiting hazardous zones can be recommended in order to lessen the impact of landslides in this area.en_US
dc.description.sponsorshipASTUen_US
dc.identifier.urihttp://10.240.1.28:4000/handle/123456789/391
dc.language.isoen_USen_US
dc.publisherASTUen_US
dc.subjectHalila Catchment, Weight of Evidence, Logistic Regression, Gamo, Ethiopiaen_US
dc.titleLandslide Susceptibility Modeling Using Weight Of Evidence and Logistic Regression Models in Halila Catchment, Gamo Zone, South Ethiopiaen_US
dc.typeThesisen_US

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