Journal of Jilin University(Earth Science Edition) ›› 2015, Vol. 45 ›› Issue (5): 1470-1478.doi: 10.13278/j.cnki.jjuese.201505201

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Risk Zoning of Earthquake-Induced Landslides Based on Slope Units: A Case Study on Lushan Earthquake

Qiu Dandan1,2, Niu Ruiqing1, ZhaoYannan1, Wu Xueling1   

  1. 1. Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China;
    2. School of Resource and civil engineering, Wuhan Institute of Technology, Wuhan 430073, China
  • Received:2014-09-02 Published:2015-09-26

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Abstract:

Earthquake-induced landslide could cause serious damage, which could be even worse than the quake itself especial in a mountain area. We select Lushan as the research area where Lushan earthquake occurred on April 20, 2013. This earthquake caused massive landslides that resulted in a tragic loss of life and economy. Combining multi-source data, we select 10 evaluation factors after Pearson correlation analysis, including elevation, slope, aspect, shape, curvature classification, vegetation index, distance from drainages, slope structure, lithology, and distance from faults. Based on the digital elevation model, we use watershed overlay method to plot slope units, and resample the evaluation factors. After multi-group test, we get the appropriate parameter value of the neural network optimized by Genetic Algorithm model. The risk zoning of earthquake induced landslides is then calculated by using neural network optimized by Genetic Algorithm. The same risk zoning model is used to slope units and grid units. The accuracy rate of slope units is 96.6%; while the accuracy rate of grid units is 92.6%. In comparison with the grid units, the slope units are more accurate. Further, we analyze the uncertainty in this evaluation model by using multi-data receiver operating characteristic curve(ROC). Each curve has the equal position; and the areas under the line are almost the same. The result indicates that the proposed method has the advantages of high accuracy, stable performance, and small amount of data to process. It can be used for early warning and assessment of earthquake.

Key words: earthquake-induced landslide, risk zoning, evaluation factors, slope units, Lushan, Sichuan

CLC Number: 

  • P642.22

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