煤炭资源是支撑我国经济快速发展的重要能源，煤炭资源的大量开采会导致矿区地表沉陷、水平形变，开展高效准确的矿区地表形变监测，能够为矿山地质灾害的预防和治理提供数据基础和科学依据。传统的矿区地表形变监测方法大多是基于点的监测，存在成本高、效率低下、监测面有限等不足之处，很难满足矿区地表形变监测的要求。近年来随着空间对地观测技术的不断发展，InSAR作为一种成熟的地表形变监测技术，具有不受云雨天气和时间影响的优势，能够实现全天候的对地观测。由于传统D-InSAR技术在监测时易存在大气延迟误差且易受时空失相干影响，本文基于时序InSAR技术和多源InSAR数据对矿区地表形变监测展开研究，并利用矿区地表三维解算模型提取地表三维形变场，将InSAR监测结果与改进后的SVR模型结合进行矿区开采沉陷预测，论文主要研究工作和成果如下：
（1）以贵州省盘州市北部松河矿区为研究区，选取2017年—2018年的29景哨兵1号升轨影像、29景哨兵1号降轨影像以及7景ALOS-2升轨影像，对研究区内的地表形变进行监测。基于SBAS-IPTA技术处理多源InSAR数据，探测研究区内形变位置及范围，获得研究区内沿雷达视线向的年平均形变速率和时序累积形变量，多源数据结果显示研究区最大形变速率和时序累积形变量分别为823mm/a、690mm/a。通过查阅资料获得松河煤矿矿井分布范围以及贵州省煤矿资源分布情况，SBAS-IPTA技术探测到的形变区域与松河矿井以及煤矿资源分布位置具有较好的一致性。多源InSAR数据的监测结果交叉验证进一步证实了SBAS-IPTA技术应用于松河矿区地表形变监测的可靠性，为下一步矿区地表三维形变解算提供数据基础。
（2）基于多源InSAR数据的LOS向形变监测结果，选取一处地表形变程度较严重的形变区，进行矿区地表三维形变解算。将数据进行重采样，建立地表三维形变解算模型，分别融合三个不同轨道数据所得到的LOS向年平均形变速率、时序累积形变量，得到研究区域的地表在垂直方向、东西方向和南北方向上的年平均形变速率和时序累积形变量。研究区域在垂直、东西以及南北方向上最大形变速率分别为865mm/a、107mm/a、604mm/a。分析矿区地表三维形变监测结果得知，通过本文方法获得的三维形变场的形变规律与矿区地表开采形变规律一致，即符合开采沉陷规律，三维地表形变能够更加全面的反映矿区开采后的地表形变特征。
（3）选取覆盖研究区的32景哨兵1号升轨影像（2020年-2021年），利用SBAS-InSAR技术获取地表时序累积沉降量，实验发现在2020年-2021年间研究区内地表仍在继续沉降。将SBAS-InSAR技术获取的32期沉降数据作为样本与改进后的SVR算法相结合，对研究区地表开采沉降量进行预测，实验结果表明与SBAS-InSAR技术相结合的WOA-SVR模型在松河矿区的开采沉陷预测中具有良好的表现，模型预测精度较高，为该矿区的地表沉降预测提供一种可靠方法。

Coal resources are an important energy source to support rapid economic development. Extensive mining of coal resources will lead to surface subsidence and horizontal deformation in mining areas. Carrying out efficient and accurate monitoring of surface deformation in mining areas can provide a data basis and scientific basis for the prevention and management of geological disasters in mining areas. Most of the traditional monitoring methods of surface deformation in mining areas are based on point monitoring, which have disadvantages such as high cost, low efficiency, and limited monitoring surface, making it difficult to meet the requirements of surface deformation monitoring in mining areas. In recent years, with the continuous development of space earth observation technology, InSAR as a mature surface deformation monitoring technology, has the advantage of not being affected by cloud and rain weather and time, and can realize all-weather earth observation. Since traditional D-InSAR technology is susceptible to decoherence and atmospheric delay during monitoring, this paper studies the surface deformation monitoring of mining areas based on time-series InSAR technology and multi-source InSAR data. The three-dimensional deformation field of the surface is extracted by using the three-dimensional solution model of the mining area, and the InSAR monitoring results are combined with the improved SVR model to predict the mining subsidence of the mining area. The main research work of the paper is as follows:

(1) The study area is the Songhe mining area in the north of Panzhou City, Guizhou Province. Selected 29 scenes of Sentinel-1 ascending images (2017-2018), 29 scenes of Sentinel-1 descending images (2017-2018) and 7 scenes of ALOS-2 ascending images (2017-2018) for research monitoring of surface deformation in the area. Based on SBAS-IPTA technology, the multi-source InSAR data is processed to detect the deformation position and range in the study area, and obtain the annual average deformation rate and time series cumulative deformation along the radar line-of-sight in the study area. The multi-source data results show that the maximum deformation rate and time series cumulative deformation in the study area are 823mm/a and 690mm/a, respectively. By consulting the data, the distribution range of Songhe coal mine and the distribution of coal mine resources in Guizhou Province are obtained. The deformation area detected by SBAS-IPTA technology is in good agreement with the distribution location of Songhe mine and coal mine resources. The cross-validation of the monitoring results of the multi-source InSAR data further confirmed the reliability of the SBAS-IPTA technology applied to the surface deformation monitoring of the Songhe mining area, and provided a data basis for the next step in the calculation of the three-dimensional surface deformation of the mining area.

(2) Based on the deformation monitoring results of multi-source InSAR data, a surface deformation area with severe deformation is selected to carry out 3D surface deformation calculation. The data is resampled to establish a three-dimensional deformation solution model of the surface. The annual average deformation rate and time series cumulative deformation value of the LOS direction obtained from the multi-source data are used to obtain the annual average deformation rate and time series cumulative deformation value of the surface of the mining area in the study area in the vertical, east-west and north-south directions. The maximum deformation rates of the study area in the vertical, east-west and north-south directions are 865mm/a, 107mm/a, and 604mm/a. By analyzing the monitoring results of the three-dimensional surface deformation in the mining area, it is known that the deformation law of the three-dimensional deformation field obtained by the method in this paper is consistent with the mining deformation law of the mining area, that is, it conforms to the mining subsidence law. The three-dimensional surface deformation can reflect the surface deformation characteristics of the mining area more comprehensively.

(3) The 32 scenes Sentinel-1 ascending images (2020-2021) covering the study area were selected, and the SBAS-InSAR technology was used to obtain the cumulative surface subsidence in time series. The 32-period subsidence data obtained by SBAS-InSAR technology was used as a sample set, combined with the improved SVR algorithm to predict the surface mining subsidence in the mining area. The experimental results show that the WOA-SVR prediction model combined with SBAS-InSAR technology has a good performance in the prediction of mining subsidence in the Songhe mining area, and the model prediction accuracy is high, which provides a reliable method for the prediction of surface subsidence in this mining area.

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