ISSN 1003-8035 CN 11-2852/P
    YIN Chao,LI Zhongbo,LIU Xinliang,et al. Landslide susceptibility assessment and zonation based on landslide classification and improved Convolutional Neural Networks[J]. The Chinese Journal of Geological Hazard and Control,2023,34(0): 1-14. DOI: 10.16031/j.cnki.issn.1003-8035.202301003
    Citation: YIN Chao,LI Zhongbo,LIU Xinliang,et al. Landslide susceptibility assessment and zonation based on landslide classification and improved Convolutional Neural Networks[J]. The Chinese Journal of Geological Hazard and Control,2023,34(0): 1-14. DOI: 10.16031/j.cnki.issn.1003-8035.202301003

    Landslide susceptibility assessment and zonation based on landslide classification and improved Convolutional Neural Networks

    • Landslide susceptibility regionalization aims to analyze the combined characteristics of hazard-inducing factors and their impact on the probability of landslide occurrence, thereby dividing the study area into different susceptible zones. This provides a theoretical basis for land use planning and the formulation of policies for landslide prevention and control. A landslide database was established for Boshan District by integrating various data sources and geological survey data. Hazard-inducing factors were selected using the Pearson correlation coefficient method, and these factors were classified for all landslides, natural landslides, and engineering landslides using the information content method. An improved 7-layer Convolutional Neural Network (CNN) with two rounds of convolution and pooling was constructed. Evaluation models were trained and verified separately for all landslides, natural landslides, and engineering landslides, and the accuracy of the models was assessed using the AUC method. The landslide susceptibility probabilities of all grid cells in Boshan district were calculated, and a landslide susceptibility regionalization map was generated using ArcGIS12.0. The results indicate that the hazard-inducing factors include elevation, slope, aspect, profile curvature, plane curvature, distance from rivers, STI, TWI, distance from roads, land use, distance from faults, lithology, and normalized difference vegetation index (NDVI). The minimum and maximum landslide susceptible probabilities in Boshan district are 0.136 and 0.841, respectively. The extremely high susceptibility, high susceptibility, medium susceptibility, low susceptibility, and extremely low susceptibility zones account for 8.08% (56.4 km2), 17.62% (123.0 km2), 25.33% (176.8 km2), 32.87% (229.4 km2) and 16.10% (112.4 km2) of the total area. The extreme high susceptibility zones are primarily distributed in the northwest, south, northeast and other areas. Natural landslides are mainly concentrated in the extremely high susceptibility zones, while engineering landslides are mainly found in the extremely high susceptibility zones in the northeast.
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