Abstract
Landslides are the most frequent phenomenon in the northern part of Iran, which cause considerable financial and life damages every year. One of the most widely used approaches to reduce these damages is preparing a landslide susceptibility map (LSM) using suitable methods and selecting the proper conditioning factors. The current study is aimed at comparing four bivariate models, namely the frequency ratio (FR), Shannon entropy (SE), weights of evidence (WoE), and evidential belief function (EBF), for a LSM of Klijanrestagh Watershed, Iran. Firstly, 109 locations of landslides were obtained from field surveys and interpretation of aerial photographs. Then, the locations were categorized into two groups of 70% (74 locations) and 30% (35 locations), randomly, for modeling and validation processes, respectively. Then, 10 conditioning factors of slope aspect, curvature, elevation, distance from fault, lithology, normalized difference vegetation index (NDVI), distance from the river, distance from the road, the slope angle, and land use were determined to construct the spatial database. From the results of multicollinearity, it was concluded that no collinearity existed between the 10 considered conditioning factors in the occurrence of landslides. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used for validation of the four achieved LSMs. The AUC results introduced the success rates of 0.8, 0.86, 0.84, and 0.85 for EBF, WoE, SE, and FR, respectively. Also, they indicated that the rates of prediction were 0.84, 0.83, 0.82, and 0.79 for WoE, FR, SE, and EBF, respectively. Therefore, the WoE model, having the highest AUC, was the most accurate method among the four implemented methods in identifying the regions at risk of future landslides in the study area. The outcomes of this research are useful and essential for the government, planners, decision makers, researchers, and general land-use planners in the study area.
Highlights
A landslide is the movement of a debris, rock, or soil mass down the slope and is one of the most frequently occurring natural disasters in mountain areas that puts lives and properties of the people at risk [1,2,3]
A multicollinearity test was conducted by variance inflation factors (VIF) and the tolerances method for selection of suitable landslide conditioning factors to identify whether there was correlation between the conditioning factors (Table 2)
The results showed that the north aspect had the highest effect on landside occurrences, and the main reason may be that the north aspect has the most wetness among other aspects resulting from less solar radiation [70]
Summary
A landslide is the movement of a debris, rock, or soil mass down the slope and is one of the most frequently occurring natural disasters in mountain areas that puts lives and properties of the people at risk [1,2,3]. Based on the reports of the Centre for Research on the Epidemiology of Disasters (CRED), landslides are the cause of 17% of all casualties of natural hazards in the world [6]. Some researchers expect this trend to increase in the future with the increase in urbanization, deforestation, and changes in climate conditions [2,7]. The damages due to the occurrence of landslides are predicted to rise in the subsequent decades with population growth, progression of residential areas and infrastructure in high-risk areas, continuing deforestation, and the increase in regional precipitation [3]
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