Zhu Chonghao, Zhang Jianjing, Ma Donghua, et al. 2020. Comprehensive analysis on risk of landslides in post-earthquake area based on DInSAR-BP neural networks[J]. Journal of Engineering Geology, 28(3): 530-540. doi: 10.13544/j.cnki.jeg.2019-132.
    Citation: Zhu Chonghao, Zhang Jianjing, Ma Donghua, et al. 2020. Comprehensive analysis on risk of landslides in post-earthquake area based on DInSAR-BP neural networks[J]. Journal of Engineering Geology, 28(3): 530-540. doi: 10.13544/j.cnki.jeg.2019-132.

    COMPREHENSIVE ANALYSIS ON RISK OF LANDSLIDES IN POST-EARTHQUAKE AREA BASED ON DINSAR-BP NEURAL NETWORKS

    • The threats of earthquakes to humans are not only the casualties and property losses, but also the hidden danger of geological hazards. To assess the risk of landslides in the area after earthquakes, a quick and reliable model for the landslide risk assessment is necessary. Based on the study area along the "Chuanzhusi-Jiuzhaigou" road, we proposes a comprehensive analysis model for the landslide hazard in the post-earthquake area. It can be called the DInSAR-BP model. The model results show that the area of the high-risk landsides in Jiuzhaigou after the earthquake is about 2602.35 km2 and 3.4 times larger than that before the earthquake. And these areas are mainly distributed in the Jiuzhaigou scenic area and the slope of the first 70 km along the "Chuanzhusi-Jiuzhaigou" road. These results match the survey results after the earthquake. The Multivariate nonlinear regression can consider the impact from the earthquake to the risk of landslides, which improves the accuracy of post-earthquake risk assessment results by 13.9%. And it proves that the model has good applicability in the study area.
    • loading

    Catalog

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return