Remote Sensing and Gis-Based Landslide Susceptibility Mapping Over Complex Landscapes: a Case of Beshilo Watershed, Northern Ethiopia

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Addis Ababa University


The need to predict possible occurrence of landslides is increasingly becoming a concern of governments and humanitarian bodies in developing countries. The occurrence of landslides and other related disasters requires an intervention towards a better approach where mitigation measures are planned before the disaster. This paper explores the suitability of the available spatial datasets as inputs into GIS-based landslide risk assessment in Beshilo watershed. The datasets used in this study included digital elevation model, slope, aspect, soils, fault, lineament, drainage, precipitation, land use land cover and lithology. The relative importance of factors was established by a combing literature review, expert opinion and pair wise comparison technique. Through GIS tools, a prediction map was generated that showed risk levels of various areas in Beshilo. The results from GIS analysis showed that the areas of highest risk included mountain slopes associated with high fault and lineament density. The result of the susceptibility mapping done for landslide hazard has been classified into five classes and their spatial area coverage also calculated. The study area shows the distribution of the five vulnerability/susceptibility classes ranking from very low (1) to very high (5). Areas with very high landslide susceptibility zones are found in the north eastern and eastern parts of Beshilo watershed. Comparatively, northern and western parts have very low vulnerability areas. From the calculations done, 9%(874.32km2) of the study area occupies very low, 24% (2362.71km2) low, 31% (2955.60km2) medium, 23% (2279.87km2) High, and the rest 13% (1215.28km2) very high hazard zones. To validate landslide susceptibility map generated by Analytical Hierarchy Process technique, Receiver Operating Characteristics curve analysis was applied. From this; the result revealed that the performance of the model was acceptable. This research result demonstrates the need to incorporate the use of geospatial tools in the countries‘ disaster management strategies.



GIS, Landslide Susceptibility, Beshilo, Pair Wise Comparison