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ZHANG Linfan, WANG Jiayun, ZHANG Maosheng, CHEN Shebin, WANG Tao. 2022. Evaluation of Regional Landslide Susceptibility Assessment Based on BP Neural Network. Northwestern Geology, 55(2): 260-270. doi: 10.19751/j.cnki.61-1149/p.2022.02.023
Citation: ZHANG Linfan, WANG Jiayun, ZHANG Maosheng, CHEN Shebin, WANG Tao. 2022. Evaluation of Regional Landslide Susceptibility Assessment Based on BP Neural Network. Northwestern Geology, 55(2): 260-270. doi: 10.19751/j.cnki.61-1149/p.2022.02.023
shu

Evaluation of Regional Landslide Susceptibility Assessment Based on BP Neural Network

  • 1. Xi'an Geological Survey Center of China Geological Survey, Xi'an 710054, Shaanxi, China;

  • 2. Shaanxi Railway Engineering Survey Co., LTD, Xi'an 710064, Shaanxi

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Received Date:  07 April 2021
Revised Date:  19 November 2021
    Abstract
  • The evaluation of regional landslide susceptibility is the basis of regional landslide hazard assessment and regional landslide risk assessment. Combined with the field geological survey data of Yining County in Xinjiang, the controlling factors of landslide in the study area are analyzed by using data mining technology, which can be used as the criteria for selecting disaster causing factors. The BP neural network model is used to build the prediction model of regional landslide susceptibility. The trained BP neural network model is combined with the DEM data and remote sensing interpretation data of the whole study area to obtain the landslide hazard susceptibility zoning map of the study area, which provides a certain reference for the local regional landslide prevention and governance decision-making.
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