孙剑锋, 马超, 胡金树, 等. 2023. 基于灰色关联度与层次分析法耦合的地质灾害易发性评价——以浙江省云和县崇头镇为例[J]. 工程地质学报, 31(2): 538-551. doi: 10.13544/j.cnki.jeg.2022-0542.
    引用本文: 孙剑锋, 马超, 胡金树, 等. 2023. 基于灰色关联度与层次分析法耦合的地质灾害易发性评价——以浙江省云和县崇头镇为例[J]. 工程地质学报, 31(2): 538-551. doi: 10.13544/j.cnki.jeg.2022-0542.
    Sun Jianfeng, Ma Chao, Hu Jinshu, et al. 2023. Susceptibility evaluation of geological hazard by coupling grey relational degree and analytic hierarchy process: A case of Chongtou Town, Yunhe County, Zhejiang Province[J]. Journal of Engineering Geology, 31(2): 538-551. doi: 10.13544/j.cnki.jeg.2022-0542.
    Citation: Sun Jianfeng, Ma Chao, Hu Jinshu, et al. 2023. Susceptibility evaluation of geological hazard by coupling grey relational degree and analytic hierarchy process: A case of Chongtou Town, Yunhe County, Zhejiang Province[J]. Journal of Engineering Geology, 31(2): 538-551. doi: 10.13544/j.cnki.jeg.2022-0542.

    基于灰色关联度与层次分析法耦合的地质灾害易发性评价——以浙江省云和县崇头镇为例

    SUSCEPTIBILITY EVALUATION OF GEOLOGICAL HAZARD BY COUPLING GREY RELATIONAL DEGREE AND ANALYTIC HIERARCHY PROCESS: A CASE OF CHONGTOU TOWN, YUNHE COUNTY, ZHEJIANG PROVINCE

    • 摘要: 面向高精度地质灾害易发性评价研究中,历史灾害样本数据少而造成的预测准确度低等问题,本文提出基于灰色关联度与层次分析法耦合的地质灾害易发性评价模型。本文以浙江省丽水市云和县崇头镇为工程背景,结合该地区致灾机理,利用现场调查和遥感解释等手段,获取9项地质灾害评价因子。分析了9项评价因子与历史灾害点的关联度,分别以关联度数值、关联度数值指数标度和关联度排名构建了层次分析法的3种判别矩阵,建立了3种类型的灰色关联度与层次分析法耦合评价模型(G-A1、G-A2和G-A3),以及单独灰色关联度评价模型(G),最后对评价结果进行了可靠性分析。结果表明:(1)在易发性综合指数分布方面,耦合模型G-A1和单独模型G较为合理;(2)在预测准确度方面,耦合模型G-A1的ROC曲线AUC指标最大;(3)在易发性分区合理性方面,耦合模型G-A1的高易发区域面积所占比例最小、高易发性强度指数最大,工程适用性强。最终,推荐耦合模型G-A1作为丽水市云和县崇头镇地质灾害易发性评价模型。本文研究成果对浙西南地区地质灾害易发性评价具有重要参考价值,为高精度地质灾害评价和防控工作提供有效的耦合评价模型。

       

      Abstract: To address the lack of historical disaster data in high-precision geological disaster research,we proposed a geological disaster susceptibility evaluation model. This model couples grey relational degree(GRD) and analytic hierarchy process(AHP). We obtained and classified the states of 9 factors by engineering survey and remote sensing interpretation according to the disaster mechanism. We analyzed the relational degrees between 9 factors and historical disasters and constructed three discriminant matrices of AHP based on the values,the index scale values,and the ranking of the relational degrees,respectively. Three GRD-AHP coupling models(G-A1,G-A2,and G- A3) and a classical GRD model(G)were established. The coupling model G-A1 shows a more reasonable susceptibility index distribution,a higher prediction accuracy,and a larger high-susceptibility intensity index. This new model is recommended as the evaluation model of geological hazard susceptibility in Chongtou Town and southwest Zhejiang Province. This work provides an effective coupled model for high-precision geological disaster research.

       

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