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[1]SHI Ziyue,ZHU Haiyan,WANG Jingjing,et al.Analysis on Susceptibility Assessment of Soil Landslide in Xiangxi Prefecture from the Perspective of Coupling Model[J].Research of Soil and Water Conservation,2021,28(03):377-383.

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Analysis on Susceptibility Assessment of Soil Landslide in Xiangxi Prefecture from the Perspective of Coupling Model

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 28 Number of periods: 2021 03 Page number: 377-383 Column: Public date: 2021-04-20

Title:: Analysis on Susceptibility Assessment of Soil Landslide in Xiangxi Prefecture from the Perspective of Coupling Model

Author(s):: SHI Ziyue¹, ZHU Haiyan², WANG Jingjing³, XIN Cunlin¹; (1.College of Geography and Environmental Science,Northwest Normal University,Lanzhou730070,China;2.Guangxi Branch of China National Geological Exploration Center of Building Materials Industry,Guilin,Guangxi541002,China;3.School of Earth Sciences and Resources,China University of Geosciences,Beijing100083,China)

Keywords:: landslide; susceptibility; information method; back propagation neural network; Xiangxi Prefecture

CLC:: P642.22; S284

DOI:: -

Abstract:: The identification of landslide susceptibility spatial distribution is crucial for landslide warning and its management in China. We first focused on frequent landslide-prone of Xiangxi Prefecture residing in Wuling Mountains by applying the information method and back propagation neural network. The contributions of 9 impact factors were quantified, and the major factors and spatial distribution characteristics were studied. The results show that: hardness degree of rock, relief and annual rainfall are most closely correlated with soil landslide, whereas geomorphologic type, slope and soil erosion intensity play the minor role in soil landslide; more than 90% of the hazard sites fall into the medium and high susceptibility regions that are located in northwest and southeast of Xiangxi Prefecture; the occurrence ratio of hazards increases with the ascent of susceptibility grade, which is consistent with the principle of hazard classification and the actual situation. The further model evaluation of results had shown an accuracy with AUC value of 0.76, indicating that the information method and back propagation neural network were appropriate approaches to evaluate soil landslide susceptibility. This study demonstrates that further research on identifying and targeting landslide susceptibility assessment will be needed to improve geo-hazard risk management and thus to alleviate disaster.

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Last Update: 2021-04-20