Evaluation of landslide susceptibility for Wanzhou district of Three Gorges Reservoir

被引：0
|
作者：
Zhang J. [1 ]
Yin K. [1 ]
Wang J. [1 ]
Liu L. [1 ]
Huang F. [2 ]
机构：
[1] Faculty of Engineering, China University of Geosciences, Wuhan, 430074, Hubei
[2] Institute of Geological Survey, China University of Geosciences, Wuhan, 430074, Hubei
来源：
Yin, Kunlong (yinkl@126.com) | 1600年 / Academia Sinica卷 / 35期
基金：
中国国家自然科学基金;
关键词：
Landslide; Slope engineering; Susceptibility evaluation; The information value model; The K-means cluster model; The logistic regression model;
D O I：
10.13722/j.cnki.jrme.2015.0318
中图分类号：
学科分类号：
摘要：
Evaluation of susceptibility of landslide hazard plays an important role in landslide hazard risk management and urban planning. In previous studies, few scholars had done any in-depth analysis and discussion on the state division of index factors. Wanzhou district of the Three Gorges Reservoir region where landslide disasters take place frequently is the focus of this study. Seven influence factors including stratum lithology, geological structure, water distribution, gradient, direction and structure of slopes, and land utilization were chosen to be the evaluation indexes. The state of each index was graded based on the variation of gradients of the cumulative frequency curve of landslide, the landslide area ratio curve and the grading area ratio curve. The information value model and the logistic regression model were used to build the susceptibility evaluation systems based on the data of 655 landslides in the history of the district. The susceptibility results of the two methods above were graded by adopting the K-means cluster analysis. A zoned map of landslide susceptibility for the whole district was obtained based on GIS platform. The two models were compared with respect to the modeling results, the accuracy, the application condition etc. The results showed that the prediction accuracies of the information value model and the logistic regression model reached 73.0% and 54.9% respectively, indicating that the information value model had better performance than the logistic regression model. © 2016, Science Press. All right reserved.
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页码：284 / 296
页数：12
相关论文
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