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Volume 39 Issue 6
Nov.  2020
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Article Navigation >  Bulletin of Geological Science and Technology  > 2020  >  39(6): 131-144
Zheng Yingkai, Chen Jianguo, Wang Chengbin, Chen Tanwu. Application of certainty factor and random forests model in landslide susceptibility evaluation in Mangshi City, Yunnan Province[J]. Bulletin of Geological Science and Technology, 2020, 39(6): 131-144. doi: 10.19509/j.cnki.dzkq.2020.0616
Citation: Zheng Yingkai, Chen Jianguo, Wang Chengbin, Chen Tanwu. Application of certainty factor and random forests model in landslide susceptibility evaluation in Mangshi City, Yunnan Province[J]. Bulletin of Geological Science and Technology, 2020, 39(6): 131-144. doi: 10.19509/j.cnki.dzkq.2020.0616
shu

Application of certainty factor and random forests model in landslide susceptibility evaluation in Mangshi City, Yunnan Province

doi: 10.19509/j.cnki.dzkq.2020.0616
  • Received Date: 24 Oct 2019
    Abstract
  • Drawing up scientific zoning maps of landslide susceptibility can effectively reduce the loss caused by disasters.Taking Mangshi City, Yunnan Province as the research area, the researchers used certainty factor (CF) method to calculate the sensitive values of each factor, and used them as classified data of random forests (RF), selected appropriate training data and optimized model parameters, and finally established the prediction model of susceptibility in the research area.In this paper, the frequency ratio method is adopted to discretize the continuity factor, so as to calculate the landslide susceptibility of different sections of the factor through the deterministic coefficient.Meanwhile, CF prior model is used to select negative samples in the research area.The optimized RF parameters are obtained by calculating the out-of-pocket errors, and then the RF model is used to train and predict the research area model.ROC curve and 3D remote sensing image were drawn to evaluate the prediction model results quantitatively and qualitatively, and the results showed that the accuracy of the model was 91%, which was better than that of random sampling Finally, the importance of each factor in the study area was calculated and evaluated by using two calculation methods of average Gini impurity reduction and average accuracy reduction.Based on the above, the landslide vulnerability assessment is carried out in the study area to provide a basis for disaster risk assessment and management in this area.

     

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