刘璐瑶, 高惠瑛. 2023. 基于证据权与Logistic回归模型耦合的滑坡易发性评价[J]. 工程地质学报, 31(1): 165-175. doi: 10.13544/j.cnki.jeg.2020-482.
    引用本文: 刘璐瑶, 高惠瑛. 2023. 基于证据权与Logistic回归模型耦合的滑坡易发性评价[J]. 工程地质学报, 31(1): 165-175. doi: 10.13544/j.cnki.jeg.2020-482.
    Liu Luyao, Gao Huiying. 2023. Landslide susceptibility assessment based on coupling of WOE model and Logistic regression model[J]. Journal of Engineering Geology, 31(1): 165-175. doi: 10.13544/j.cnki.jeg.2020-482.
    Citation: Liu Luyao, Gao Huiying. 2023. Landslide susceptibility assessment based on coupling of WOE model and Logistic regression model[J]. Journal of Engineering Geology, 31(1): 165-175. doi: 10.13544/j.cnki.jeg.2020-482.

    基于证据权与Logistic回归模型耦合的滑坡易发性评价

    LANDSLIDE SUSCEPTIBILITY ASSESSMENT BASED ON COUPLING OF WOE MODEL AND LOGISTIC REGRESSION MODEL

    • 摘要: 滑坡灾害易发性研究对地质灾害风险管理及减灾防灾有着重要的现实意义。目前,多模型耦合的评价方法在国内外应用较为广泛,但将证据权与其他方法相结合用于滑坡易发性评价的研究却较少。鉴于此,本文以浙江省永嘉县为例进行滑坡易发性评价,选取高程等9个因素作为滑坡易发性的评价因子。利用证据权模型计算得到的证据权对比度与分级栅格比、滑坡栅格比进行比较,实现各评价因子状态分级处理;再运用Logistic回归模型算得各评价因子的权重。综合两种模型确定的状态分级权重和评价因子权重,基于GIS的栅格运算功能得到各评价单元的滑坡发生概率,实现研究区滑坡易发性分级区划。研究结果表明,证据权与Logistic回归耦合模型的评价结果的合理性与精确度均优于两种单一模型;且极高易发区和高易发区主要分布在水系延展区、断层密集区、岩组软弱区。研究结果对滑坡灾害风险管理及城市防灾规划具有一定的参考价值。

       

      Abstract: The study of landslide susceptibility is of great practical significance to the risk management of geological hazards and disasters prevention. Currently,the coupling of different evaluation methods is commonly adopted worldwide,but few of them applied the combination of the weight of evidence model(WOE) and other models to assess landslides susceptibility. Taking Yongjia County of Zhejiang Province as an example,nine evaluation factors were elected as the evaluation indices. They include elevation,slope,aspect,distance to river,distance to road,distance to faults,stratum lithology,land cover,and the normalized difference vegetation index(NDVI). The state of each evaluation factor was graded based on the contrast values calculated with WOE,the grading grid ratio and landslide grid ratio. We applied logistic regression model to obtain the weight of each factor. Based on the grid operation function of GIS,we combined weight of states and weight of evaluation factors weight determined by the two models and calculated the probability of landslide occurrence in each evaluation unit obtained a zoning map of landslide susceptibility. The results indicate that the evaluation results of the coupling model is more reasonable and has higher precision. High and extremely high susceptibility of landslide areas are mainly distributed in the water extension area,fault concentration area and lithology weakness area. Landslide susceptibility mapping has a certain reference meaning to landslide risk management and urban disaster prevention planning.

       

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