Weight of Evidence (WOE) Model Based on GIS to Evaluate Landslides Susceptibility (Case study: Jaghargh Watershed)
Author(s):
Abstract:
Landslide is an important geological hazard that causes damage to natural and social environment. Landslide hazard assessment is an important step towards risk management and there are several methods of Landslide Hazard Zonation (LHZ). Landslide susceptibility maps are very helpful to planners and engineers for choosing suitable locations to carry out development. . In this research, we tried to mapping the landslide hazard at Jaghargh watershed by using weights-of-Evidence (WOE) method based on GIS technique. Eleven landslide causative factors were considered for the susceptibility analysis. Using landslide location and a spatial database containing information such as topography, lithology, land cover and lineament.The topographic database including information on slope angle, slope aspect, elevation, plan curvature, distance from road and distance from drainage, stream power index and Sediment transport index was developed from a digital elevation model (DEM) .The lithology and the distance from the lineament were derived from the geological database and layers of precipitation areas using meteorological data were obtained. By using weight of evidence method, the relationships between each factors and landslide points were determined and the weights of each factor were obtained. Finally, the accuracy of the map was determined by using Li Index. The results show that the sub affecting height and rainfall factors, respectively with weights 47.66 and 24.47, were identified as the most important factors in a landslide in the study aria. The results of evaluation model accuracy, showed a trend (low to high) in landslide hazard index from low to high risk area,that indicate the model is accurate. Using the provided landslide susceptibility map, we can identify unstable areas, and be used in program development.
Keywords:
Language:
Persian
Published:
Geographical Research, Volume:31 Issue: 2, 2016
Page:
137
https://magiran.com/p1614425
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