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基于D-InSAR、SBAS和无人机技术的矿区地表沉降综合高精度监测方法

Integrated high-precision monitoring method for surface subsidence in mining areas using D-InSAR, SBAS, and UAV technologies.

作者信息

Zhu Mingfei, Yu Xuexiang, Tan Hao, Yuan Jiajia

机构信息

School of Earth and Environment, Anhui University of Science and Technology, Huainan, 232001, China.

School of Geomatics, Anhui University of Science and Technology, Huainan, 232001, China.

出版信息

Sci Rep. 2024 May 30;14(1):12445. doi: 10.1038/s41598-024-63400-5.

DOI:10.1038/s41598-024-63400-5
PMID:38822112
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11143354/
Abstract

The use of unmanned operations to monitor mining induced land subsidence is increasing. This study conducts a detailed comparative analysis of accuracy of measured ground deformation provided by Differential Interferometric Synthetic Aperture Radar (D-InSAR), Small Baseline Subset (SBAS), and Unmanned Aerial Vehicle (UAV) tilt photogrammetry with respect to levelling measurements. Based on such analysis we propose an integrated approach that combines multiple remote sensing methods to achieve a better global accuracy in the land subsidence monitoring in mining areas. Conducted at the Banji Coal Mine, this study collected subsidence data from April 10, 2021, to June 28, 2022, through D-InSAR, SBAS, and UAV techniques. After segmenting the subsidence basin into distinct zones, we qualitatively assessed each area with UAV-derived 3D models and quantitatively evaluated the precision of all applied techniques, benchmarking against leveling data. Our findings indicate that integrating D-InSAR, SBAS, and UAV technologies significantly enhances monitoring accuracy over any single method, demonstrating their combined effectiveness in different subsidence areas. Consequently, the synergistic integration of D-InSAR, SBAS, and UAV technologies, capitalizing on their complementary strengths, enables the achievement of intuitive, comprehensive, and high-precision monitoring of subsidence basins in mining areas.

摘要

利用无人作业监测采矿引起的地面沉降的情况正在增加。本研究对差分干涉合成孔径雷达(D-InSAR)、小基线子集(SBAS)和无人机(UAV)倾斜摄影测量所提供的实测地面变形精度与水准测量进行了详细的对比分析。基于该分析,我们提出了一种综合方法,该方法结合多种遥感方法,以在矿区地面沉降监测中实现更高的整体精度。本研究在板集煤矿开展,通过D-InSAR、SBAS和无人机技术收集了2021年4月10日至2022年6月28日期间的沉降数据。在将沉降盆地划分为不同区域后,我们利用无人机生成的三维模型对每个区域进行了定性评估,并对照水准数据定量评估了所有应用技术的精度。我们的研究结果表明,整合D-InSAR、SBAS和无人机技术可显著提高监测精度,优于任何单一方法,证明了它们在不同沉降区域的综合有效性。因此,D-InSAR、SBAS和无人机技术的协同整合,利用它们的互补优势,能够实现对矿区沉降盆地直观、全面且高精度的监测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/549a/11143354/f6a289d615f7/41598_2024_63400_Fig9_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/549a/11143354/af12b2fd4534/41598_2024_63400_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/549a/11143354/f6a289d615f7/41598_2024_63400_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/549a/11143354/36cbd9ed913e/41598_2024_63400_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/549a/11143354/d834090e4841/41598_2024_63400_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/549a/11143354/a6c5c3032c44/41598_2024_63400_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/549a/11143354/6d5ee6fac143/41598_2024_63400_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/549a/11143354/114b17d83b03/41598_2024_63400_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/549a/11143354/c492e4c002e9/41598_2024_63400_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/549a/11143354/a548cf9bcfa1/41598_2024_63400_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/549a/11143354/af12b2fd4534/41598_2024_63400_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/549a/11143354/f6a289d615f7/41598_2024_63400_Fig9_HTML.jpg

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本文引用的文献

1
Monitoring and Analysis of Ground Surface Settlement in Mining Clusters by SBAS-InSAR Technology.基于SBAS-InSAR技术的矿区地表沉降监测与分析
Sensors (Basel). 2022 May 13;22(10):3711. doi: 10.3390/s22103711.