LANDSLIDE SUSCEPTIBILTY MAPPING USING GIS BASED MODIFIED FREQUENY RATIO AND INFORMATION VALUE METHOD – A CASE STUDY OF DEBRETABOR TO ALEMBER ROAD SECTION AND ITS SURROUNDING AREA, NORTHWESTERN ETHIOPIA

Abstract

In the present study Landslide Susceptibility Mapping was carried out along DebretaborAlember road section and its surrounding area in northwestern Ethiopia. The main objective of this study is to evaluate landslide causative factors and to generate a landslide susceptibility map (LSM) using modified frequency ratio (MFR) and information value (IV) methods. 89 past landslides were identified and mapped using intensive fieldwork and Google Earth image interpretation. From total past landsides 78% and 22% were used for training and validation respectively. For current study, slope angle, aspect, curvature, elevation, lithology, distance to road, distance to stream, land use and land cover, rainfall and NDVI landslide causative factors were selected and combined with 78% training dataset using geographic information system (GIS). Then, the corresponding landslide factor maps and LSMs were prepared using Arc GIS software for both MFR and IV models. Then the area was divided into five landslide susceptibility zones of very low, low, moderate, high and very high. The landslide susceptibility map of the study area through modified frequency ratio method shows that 19.9% (18.4 km2), 20.5% (18.9 km2), 20.3% (18.7 km2), 20% (18.5km2) and 19% (17.7 km2) area cover by very low, low, moderate, high and very high susceptible classes respectively. In case of the landslide susceptibility map of the study area through information value 19.8% (18.2km2), 20% (18.8km2), 19.5%(17.9km2), 20.5% (18.8km2) and 19.8% (18.3km2) area cover by very low, low, medium, high and very high susceptible classes respectively. Finally, the resulted LSMs have been validated by using landslide density index method by overlay analysis. The result showed that 72.16% and 73.86% validated past landslide inventory fall in very high and high susceptibility zone in modified frequency ratio and information value model respectively. This indicated that the LSM produced by IV model showed a better performance than that of MFR model. Finally, the produced LS map could be very useful to community and local officials for choosing suitable locations for future land-use planning and implementation of developments