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作 者:丁丽 宋鹏飞 丁超 Ding Li;Song Pengfei;Ding Chao(Mineral Resources Exploration Center of Henan Geological Bureau,Zhengzhou 450000,China)
机构地区:[1]河南省地质局矿产资源勘查中心,郑州450000
出 处:《黑龙江科技大学学报》2024年第4期531-536,共6页Journal of Heilongjiang University of Science And Technology
基 金:中央财政自然灾害防治体系建设补助资金项目(2021410036)。
摘 要:针对义马市目前存在的采空塌陷区变形破坏问题,利用时序InSAR技术对2018-2021年期间的Sentinel-1A数据开展遥感解译,获取了义马市的地面塌陷的分布情况。在采空塌陷孕灾因子分析的基础上,筛选出与采空塌陷相关性较强的评价因子,构建了义马市采空塌陷易发性评价指标体系,利用层次分析法确定出各个因子的权重,采用加权综合指数法对义马市进行了采空塌陷易发性评价。结果表明,采煤区采煤塌陷易发性评价ROC曲线评价结果精度为0.82,将遥感解译获得的地面沉降数据与数学模型计算得到的数据相结合的手段可有效评价采空塌陷的易发性。This paper aims to address the deformation and failure problem in goafcollapse area in Yima City.The study is performed by conducting the remote sensing interpretation of Sentinel-1A data from 2018 to 2021 by using time-series InSAR technology to obtain the distribution of the collapse ground in Yima City,selecting the evaluation factors correlated strongly with goafcollapse on the basis of the analysis of the hazard factors,constructing the evaluation index system of goafcollapse susceptibility of Yima City;detemining the weights of each factor by AHP,and conducting the goafcollapse susceptibility assessment with weighted composite index method in Yima City.The result shows that the accuracy of ROC curve for mining subsidence susceptibility assessment in coal mining area is 0.82,which indicates that the combination of land subsidence data obtained by remote sensing interpretation and calculating with mathematical model can effectively evaluate the mining subsidence susceptibility.
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