A comparative study of frequency ratio, weights of evidence and logistic regression methods for landslide susceptibility mapping: Sultan Mountains, SW Turkey

被引:333
作者
Ozdemir, Adnan [1 ]
Altural, Tolga [2 ]
机构
[1] Selcuk Univ, Dept Geol Engn, Konya, Turkey
[2] Selcuk Univ, Grad Sch Nat & Appl Sci, Konya, Turkey
关键词
Frequency ratio; Logistic regression; Weights of evidence; Landslide susceptibility; ARTIFICIAL NEURAL-NETWORKS; CONDITIONAL-PROBABILITY; HAZARD ASSESSMENT; SAMPLING STRATEGIES; AREA; GIS; VALIDATION; REGION; BASIN; MODELS;
D O I
10.1016/j.jseaes.2012.12.014
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
This study evaluated and compared landslide susceptibility maps produced with three different methods, frequency ratio, weights of evidence, and logistic regression, by using validation datasets. The field surveys performed as part of this investigation mapped the locations of 90 landslides that had been identified in the Sultan Mountains of south-western Turkey. The landslide influence parameters used for this study are geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total curvature, plan curvature, profile curvature, wetness index, stream power index, sediment transportation capacity index, distance to drainage, distance to fault, drainage density, fault density, and spring density maps. The relationships between landslide distributions and these parameters were analysed using the three methods, and the results of these methods were then used to calculate the landslide susceptibility of the entire study area. The accuracy of the final landslide susceptibility maps was evaluated based on the landslides observed during the fieldwork, and the accuracy of the models was evaluated by calculating each model's relative operating characteristic curve. The predictive capability of each model was determined from the area under the relative operating characteristic curve and the areas under the curves obtained using the frequency ratio, logistic regression, and weights of evidence methods are 0.976, 0.952, and 0.937, respectively. These results indicate that the frequency ratio and weights of evidence models are relatively good estimators of landslide susceptibility in the study area. Specifically, the results of the correlation analysis show a high correlation between the frequency ratio and weights of evidence results, and the frequency ratio and logistic regression methods exhibit correlation coefficients of 0.771 and 0.727, respectively. The frequency ratio model is simple, and its input, calculation and output processes are easily understood. The interpretations of the susceptibility map reveal that geology, slope steepness, slope aspect, and elevation played major roles in landslide occurrence and distribution in the Sultan Mountains. The landslide susceptibility maps produced from this study could therefore assist planners and engineers during development and land-use planning. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:180 / 197
页数:18
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