摘要
针对传统单点测量不能全面监测尾矿库地表形变的不足,基于2018年6月至2023年5月的Sentinel-1升降轨数据,采用R指数模型评估InSAR技术在尾矿库形变监测中的适用性,利用SBAS-InSAR技术获取尾矿坝的整体形变信息,并结合坝顶采样点的时序形变与季节性降水进行小波分析。结果表明:InSAR数据在马家田尾矿库的堆积坝坡面、龙潭沟坝顶和阿署达沟坝顶的适用性更好;阿署达沟坝顶的形变速率持续增大,升降轨的视线向形变速率达到了22.07 mm/a和18.03 mm/a,且闭库后并未发生减缓趋势;坝顶的时序形变和季节性降水在一年左右的周期上呈现出显著的相关性。该研究有助于分析尾矿库的整体形变特征,为尾矿库的安全闭库提供重要保障。
To address the limitations of traditional single-point monitoring in comprehensively measuring surface deformation of tailings ponds,this study evaluates the applicability of InSAR technology for tailings dam deformation monitoring using Sentinel-1 ascending and descending orbit data from June 2018 to May 2023.The R-index model is employed to assess the suitability of InSAR,while the SBAS-InSAR technique is used to obtain overall deformation information of the tailings dam.Additionally,wavelet analysis is performed by integrating time-series deformation data from sampling points on the dam crest with seasonal rainfall.The results show that InSAR technology is particularly effective in monitoring the slope of the tailings dam at the Majia Tian site,as well as the dam crests at Longtan Gou and Ashuda Gou.Specifically,the deformation rate at the Ashuda Gou dam crest continues to increase,with line-of-sight deformation rates reaching 22.07 mm/a and 18.03 mm/a in the ascending and descending orbits,respectively,and no signs of deceleration after the dam’s closure.A significant correlation between time-series deformation at the dam crest and seasonal rainfall is observed with a cycle of approximately one year.This study provides valuable data for the analysis of overall tailings dam deformation characteristics and offers essential support for the safe closure of tailings dams.
作者
卢玉玺
李梦华
尹谢兵
LU Yuxi;LI Menghua;YIN Xiebing(School of Land Resources Engineering,Kunming University of Science and Technology,Kunming 650093,China;Yunnan Key Laboratory of Quantitative Remote Sensing,Kunming University of Science and Technology,Kunming 650093,China;Yunnan International Joint Laboratory for Integrated Sky-ground Intelligent Monitoring of Mountain Hazards,Kunming 650093,China)
出处
《遥感信息》
北大核心
2025年第6期158-166,共9页
Remote Sensing Information
基金
云南省基础研究专项面上项目(202301AT070436)。
