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基于时序InSAR的矿区滑坡前地表运动特征分析
引用本文:贺黎明,裴攀科,吴立新,张香凝. 基于时序InSAR的矿区滑坡前地表运动特征分析[J]. 东北大学学报(自然科学版), 2022, 43(9): 1314-1322. DOI: 10.12068/j.issn.1005-3026.2022.09.014
作者姓名:贺黎明  裴攀科  吴立新  张香凝
作者单位:(1. 东北大学 资源与土木工程学院, 辽宁 沈阳110819; 2. 中南大学 地球科学与信息物理学院, 湖南 长沙410083)
基金项目:国家自然科学基金资助项目(41974028); 中央高校基本科研业务费专项资金资助项目(N180104014).
摘    要:根据矿区滑坡前地表变形的遥感监测方法,提出了不同轨道SAR(synthetic aperture radar)数据集监测结果可靠性的判别依据,并对诱发矿区滑坡的因素进行分析.以鞍山市鞍千哑巴岭露天采场边坡为研究对象,基于44景Sentinel-1雷达影像(两组升轨和一组降轨),利用时间序列InSAR方法分析了采场边坡在2019年11月25日滑坡前约6个月的地表运动特征.结果表明,不同轨道数据集针对同一研究区域所获取的监测结果具有差异性,滑坡区域顶部后缘位置在发生滑坡前的一段时间范围内(约45d)呈异常强烈的加速变形现象.研究成果将为今后利用InSAR技术早识别矿区易滑坡危险区提供新的思路.

关 键 词:滑坡;露天矿;InSAR;地表变形;早识别  

Analysis on Characteristics of Ground Surface Movement Before Landslide in Mining Area Based on Time Series InSAR
HE Li-ming,PEI Pan-ke,WU Li-xin,ZHANG Xiang-ning. Analysis on Characteristics of Ground Surface Movement Before Landslide in Mining Area Based on Time Series InSAR[J]. Journal of Northeastern University(Natural Science), 2022, 43(9): 1314-1322. DOI: 10.12068/j.issn.1005-3026.2022.09.014
Authors:HE Li-ming  PEI Pan-ke  WU Li-xin  ZHANG Xiang-ning
Affiliation:1. School of Resources & Civil Engineering, Northeastern University, Shenyang 110819, China; 2. School of Geosciences and Info-Physics, Central South University, Changsha 410083, China.
Abstract:According to the remote sensing monitoring method of the ground deformation before mine landslide, the discrimination basis of the reliability of different orbit SAR data sets was proposed, and the inducing factors of landslide were analyzed. Taking the slope of the Anqian Yabaling open-pit mine in Anshan city as an example, using 44 Sentinel-1 radar images(two groups of ascending orbits and one group of descending orbit), the time series InSAR method was used to analyze the surface movement characteristics of the slope 6 months before the landslide occurred on November 25, 2019. The results show that the monitoring results obtained by different orbit data sets in the same studied area are different. The position of the top and rear edge of the landslide area showed an unusually strong acceleration within a period of time(approximately 45 days) before the landslide. The research results can provide new ideas for early identification of landslide hazard in mining areas using InSAR technology in the future.
Keywords:landslide   open-pit mine   InSAR   ground deformation   early identification,
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