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
