Construction of Mining Subsidence Basin and Inversion of Predicted Subsidence Parameters Based on UAV Photogrammetry Products Considering Horizontal Displacement
Constructing high-precision subsidence basins is of paramount importance for mining subsidence monitoring. Traditional unmanned aerial vehicle (UAV) photogrammetry techniques typically construct subsidence basins by directly differencing digital elevation models (DEMs) from different monitoring peri...
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MDPI AG
2024-11-01
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| author | Jinqi Zhao Yufen Niu Zhengpei Zhou Zhong Lu Zhimou Wang Zhaojiang Zhang Yiyao Li Ziheng Ju |
| author_facet | Jinqi Zhao Yufen Niu Zhengpei Zhou Zhong Lu Zhimou Wang Zhaojiang Zhang Yiyao Li Ziheng Ju |
| author_sort | Jinqi Zhao |
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| description | Constructing high-precision subsidence basins is of paramount importance for mining subsidence monitoring. Traditional unmanned aerial vehicle (UAV) photogrammetry techniques typically construct subsidence basins by directly differencing digital elevation models (DEMs) from different monitoring periods. However, this method often neglects the influence of horizontal displacement on the accuracy of the subsidence basin. Taking a mining area in Ordos, Inner Mongolia, as an example, this study employed the normalized cross-correlation (NCC) matching algorithm to extract horizontal displacement information between two epochs of a digital orthophoto map (DOM) and subsequently corrected the horizontal position of the second-epoch DEM. This ensured that the planar positions of ground feature points remained consistent in the DEM before and after subsidence. Based on this, the vertical displacement in the subsidence area (the subsidence basin) was obtained via DEM differencing, and the parameters of the post-correction subsidence basin were inverted using the probability integral method (PIM). The experimental results indicate that (1) the horizontal displacement was influenced by the gully topography, causing the displacement within the working face to be segmented on both sides of the gully; (2) the influence of the terrain on the subsidence basin was significantly reduced after correction; (3) the post-correction surface subsidence curve was smoother than the pre-correction curve, with abrupt error effects markedly diminished; (4) the accuracy of the post-correction subsidence basin increased by 43.12% compared with the total station data; and (5) comparing the measured horizontal displacement curve with that derived using the probability integral method revealed that the horizontal displacement on the side of an old goaf adjacent to the newly excavated working face shifted toward the advancing direction of the new working face as mining progressed. This study provides a novel approach and insights for using low-cost UAVs to construct high-precision subsidence basins. |
| format | Article |
| id | doaj-art-a673e76a036247c9b0fa04fdbe96124f |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj-art-a673e76a036247c9b0fa04fdbe96124f2025-08-20T01:53:56ZengMDPI AGRemote Sensing2072-42922024-11-011622428310.3390/rs16224283Construction of Mining Subsidence Basin and Inversion of Predicted Subsidence Parameters Based on UAV Photogrammetry Products Considering Horizontal DisplacementJinqi Zhao0Yufen Niu1Zhengpei Zhou2Zhong Lu3Zhimou Wang4Zhaojiang Zhang5Yiyao Li6Ziheng Ju7School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221008, ChinaSchool of Mining and Geomatics Engineering, Hebei University of Engineering, Handan 056038, ChinaSchool of Mining and Geomatics Engineering, Hebei University of Engineering, Handan 056038, ChinaSchool of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221008, ChinaSchool of Mining and Geomatics Engineering, Hebei University of Engineering, Handan 056038, ChinaSchool of Mining and Geomatics Engineering, Hebei University of Engineering, Handan 056038, ChinaSchool of Mining and Geomatics Engineering, Hebei University of Engineering, Handan 056038, ChinaSchool of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, ChinaConstructing high-precision subsidence basins is of paramount importance for mining subsidence monitoring. Traditional unmanned aerial vehicle (UAV) photogrammetry techniques typically construct subsidence basins by directly differencing digital elevation models (DEMs) from different monitoring periods. However, this method often neglects the influence of horizontal displacement on the accuracy of the subsidence basin. Taking a mining area in Ordos, Inner Mongolia, as an example, this study employed the normalized cross-correlation (NCC) matching algorithm to extract horizontal displacement information between two epochs of a digital orthophoto map (DOM) and subsequently corrected the horizontal position of the second-epoch DEM. This ensured that the planar positions of ground feature points remained consistent in the DEM before and after subsidence. Based on this, the vertical displacement in the subsidence area (the subsidence basin) was obtained via DEM differencing, and the parameters of the post-correction subsidence basin were inverted using the probability integral method (PIM). The experimental results indicate that (1) the horizontal displacement was influenced by the gully topography, causing the displacement within the working face to be segmented on both sides of the gully; (2) the influence of the terrain on the subsidence basin was significantly reduced after correction; (3) the post-correction surface subsidence curve was smoother than the pre-correction curve, with abrupt error effects markedly diminished; (4) the accuracy of the post-correction subsidence basin increased by 43.12% compared with the total station data; and (5) comparing the measured horizontal displacement curve with that derived using the probability integral method revealed that the horizontal displacement on the side of an old goaf adjacent to the newly excavated working face shifted toward the advancing direction of the new working face as mining progressed. This study provides a novel approach and insights for using low-cost UAVs to construct high-precision subsidence basins.https://www.mdpi.com/2072-4292/16/22/4283subsidence basinUAV photogrammetryDOMDEMhorizontal displacementparameter inversion |
| spellingShingle | Jinqi Zhao Yufen Niu Zhengpei Zhou Zhong Lu Zhimou Wang Zhaojiang Zhang Yiyao Li Ziheng Ju Construction of Mining Subsidence Basin and Inversion of Predicted Subsidence Parameters Based on UAV Photogrammetry Products Considering Horizontal Displacement Remote Sensing subsidence basin UAV photogrammetry DOM DEM horizontal displacement parameter inversion |
| title | Construction of Mining Subsidence Basin and Inversion of Predicted Subsidence Parameters Based on UAV Photogrammetry Products Considering Horizontal Displacement |
| title_full | Construction of Mining Subsidence Basin and Inversion of Predicted Subsidence Parameters Based on UAV Photogrammetry Products Considering Horizontal Displacement |
| title_fullStr | Construction of Mining Subsidence Basin and Inversion of Predicted Subsidence Parameters Based on UAV Photogrammetry Products Considering Horizontal Displacement |
| title_full_unstemmed | Construction of Mining Subsidence Basin and Inversion of Predicted Subsidence Parameters Based on UAV Photogrammetry Products Considering Horizontal Displacement |
| title_short | Construction of Mining Subsidence Basin and Inversion of Predicted Subsidence Parameters Based on UAV Photogrammetry Products Considering Horizontal Displacement |
| title_sort | construction of mining subsidence basin and inversion of predicted subsidence parameters based on uav photogrammetry products considering horizontal displacement |
| topic | subsidence basin UAV photogrammetry DOM DEM horizontal displacement parameter inversion |
| url | https://www.mdpi.com/2072-4292/16/22/4283 |
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