我国是世界上煤炭资源最丰富的国家之一，煤炭资源的开采推动了我国经济的快速发展。然而大量井工开采引起的煤矿地表沉降对矿区环境有着严重的影响和危害。因而，开展矿区地表沉降监测研究对于“三下采煤”及制定科学合理的环境保护措施具有重要的理论和应用价值。

       传统的矿区地表沉降监测方法虽然测量精度较高，但通过布设观测线进行测量的方法对于大范围的形变监测需要耗费大量的人力、物力，并且对于测点的长期维护较为困难。合成孔径雷达干涉测量（Interferometric Synthetic Aperture Radar, InSAR）技术因其具有全天时、全天候、精度高、范围广等特点，已经成为监测地表沉降的常用方法之一，在世界范围内得到普遍应用。通过InSAR技术进行干涉测量的结果具有高时空分辨率，可以达到厘米甚至毫米级精度，能够满足矿区地表沉降监测的精度要求。

       本文针对InSAR技术在矿区地表沉降监测中的相关问题开展研究，主要研究内容和成果如下：

    （1）探讨DEM（Digital Elevation Model）对DInSAR（Differential InSAR）地表沉降监测的影响。以彬长矿区为研究对象，选取4种DEM为参考高程数据，分别基于DInSAR技术对两组Sentinel-1A数据进行处理。对不同DEM数据、DInSAR监测结果、GPS（Global Positioning System）实测数据与监测结果进行对比分析，结果表明，NASA DEM作为参考高程数据，DInSAR监测结果的精度最高。

    （2）探讨不同时序InSAR在矿区地表沉降监测中的适用性。以彬长矿区孟村煤矿为研究对象，分别采用PS DInSAR（Persistent Scatterers DInSAR）、SBAS DInSAR（Small Baseline Subset DInSAR）、优化GCP（Ground Control Point）点选取的SBAS DInSAR共3种时序InSAR技术对研究区2018年1月11日至2018年12月25日的30景Sentinel-1A数据进行处理。通过对不同时序InSAR技术的监测结果进行分析，并选取时间跨度为2018年6月9日至2018年11月29日的5个GPS实测数据对不同时序InSAR方法的监测结果进行验证。结果表明，优化GCP点选取的SBAS DInSAR技术监测结果的精度最高。

    （3）深入探讨基于优化GCP点选取的SBAS DInSAR矿区地表沉降监测方法。基于优化GCP点选取的SBAS DInSAR对彬长矿区2014年10月23日至2019年5月6日的98景Sentinel-1A数据进行处理，获取了研究区的年平均沉降速率图及时间序列累积沉降量。选取时间跨度为2018年6月29日至2019年3月9日共6个GPS实测数据与对应时段的监测结果进行对比。结果显示：矿区的最大年平均沉降速率和最大累积沉降量分别为-97 mm/a和-387 mm；GPS与监测结果的平均均方根误差（Root Mean Squared Error, RMSE）和平均相关性系数（correlation coefficient, r）分别为2.3 cm和0.944，验证了优化GCP点选取的SBAS DInSAR技术在研究区应用的可行性及监测结果的准确性。

    China is one of the countries with the richest coal resources in the world. The exploitation of coal resources promotes the rapid development of China's economy. However, the surface subsidence caused by a large number of underground mining has a serious impact and harm on the mining environment. Therefore, it is of great theoretical and practical value to carry out the research on surface subsidence monitoring in mining areas for “coal mining under buildings, railways and water-bodies” and to formulate scientific and reasonable environmental protection measures.

    Although the traditional mining area surface subsidence monitoring method has high measurement accuracy, it needs a lot of manpower and material resources for large-scale deformation monitoring by laying observation lines, and it is difficult for long-term maintenance of measuring points. Interferometric synthetic aperture radar (InSAR) technology has become one of the common methods for monitoring land subsidence because of its all-day, all-weather, high accuracy, and wide range. The results of InSAR interferometry have a high spatial and temporal resolution, which can reach centimeter or even millimeter level accuracy and can meet the accuracy requirements of surface subsidence monitoring in the mining area.

    In this paper, the related problems of InSAR technology in mining area surface subsidence monitoring are studied. The main research contents and achievements are as follows:

    (1) Discusses the influence of DEM (Digital Elevation Model) on the surface subsidence monitoring of DInSAR (Differential InSAR). Taking the Binchang mining area as the research object, four kinds of DEM are selected as reference elevation data, and two groups of sentinel-1A data are processed based on DInSAR technology. The comparison and analysis of different DEM data, DInSAR monitoring results, GPS (Global Positioning System) measured data, and monitoring results show that the accuracy of DInSAR monitoring results is the highest when NASA DEM is used as reference elevation data.

     (2) Discusses the applicability of different time series InSAR in mining area surface subsidence monitoring. Taking Mengcun coal mine in Binchang mining area as the research object, three kinds of time series InSAR technologies including PS DInSAR (Persistent Scatterers DInSAR), SBAS DInSAR (Small Baseline Subset DInSAR), and SBAS DInSAR selected by optimized GCP points were used to process the 30 Sentinel-1A data in the study area from January 11, 2018, to December 25, 2018. Through the analysis of the monitoring results of different time series InSAR technology, five GPS measured data from June 9, 2018, to November 29, 2018, are selected to verify the monitoring results of different time series InSAR methods. The results show that the SBAS DInSAR technology, which optimizes the selection of GCP points, has the highest accuracy.

    (3) In-depth discussion of the SBAS DInSAR mining area surface subsidence monitoring method based on optimized GCP point selection. SBAS DInSAR based on optimized GCP point selection processed 98 Sentinel-1A data of Binchang mining area from October 23, 2014, to May 6, 2019, and obtained the annual average settlement rate map and time series cumulative settlement of the study area amount. The selected time span is from June 29, 2018, to March 9, 2019, and a total of 6 GPS measured data are compared with the monitoring results of the corresponding time period. The results show that the maximum annual average settlement rate and maximum cumulative settlement of the mining area are -97 mm/a and -387 mm, respectively; the average root means square error (RMSE) and average correlation coefficient(r) between GPS and monitoring results are 2.3 cm and 0.944, respectively. The feasibility of the application of the SBAS DInSAR technology, which optimizes the selection of GCP points, in the study area, and the accuracy of the monitoring results are verified.

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