Volume 7, Issue 14 (2-2017)                   jwmr 2017, 7(14): 77-69 | Back to browse issues page


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(2017). Evaluating the Efficiency of Probabilistic Weight of Evidence Model for Landslide Susceptibility Mapping (Case Study: Siyahbisheh Watershed, Mazandaran). jwmr. 7(14), 77-69. doi:10.29252/jwmr.7.14.77
URL: http://jwmr.sanru.ac.ir/article-1-758-en.html
Abstract:   (3673 Views)

Mass movements are usually natural erosion, but the human can aggravate it by operations such as mining, road construction and destroying the natural vegetation. The purpose of this study is to identify the factors influencing the occurrence of landslides by using a probabilistic model Weight of Evidence and Geography Information System in the Siyahbisheh Watershed. 132 landslide points are identified and recorded through interpretation of aerial photos and wide field surveys. Randomly out of this number, 92 landslide points (70%) for modeling and 40 landslide points (30%) are implemented for evaluation. The factors studied in causing landslide includes slope, aspect, plan Curvature, elevation, distance from the road, distance from the streams, distance from the faults and geological survey using GIS digit and maps are provided for each of the factors. The relationship between each factor with landslide points is determined by using a probabilistic model weight of evidence and the landslide susceptibility map is provided.WOE model introduces classes, 30-15slope degree, aspect of northeast, the elevation of 2200-2600m,150-200m distance from the road, less than100 meters from the road, distance of more than 400 meters from the fault, the geological formations Jurassic-Triassic, concave curvature as the most important factor causing landslide in the Siyahbisheh Watershed. The results of ROC curve analysis showed that the WOE model with the AUC 0.81 has an acceptable accuracy for landslide susceptibility analysis in the study area.

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Type of Study: Research | Subject: Special
Received: 2017/01/24 | Accepted: 2017/01/24 | Published: 2017/01/24

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