期刊
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
卷 60, 期 -, 页码 -出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2022.3226216
关键词
3-D deformations; Gompertz probability integral model (GPIM); interferometric synthetic aperture radar (InSAR); mining subsidence; progressive deformations
类别
资金
- National Natural Science Foundation of China [41971401]
- Fundamental Research Funds for the Central Universities [2022YJSDC22]
- National Key Research and Development Program of China [2020YFD1100203]
This study proposes a novel method based on InSAR to accurately estimate mining-induced 3-D surface deformations. The method integrates single InSAR interferogram, the Gompertz time function, and the probability integral model to derive the deformations at any moment. Experimental results demonstrate the accuracy of the method in subsidence, tilt, curvature, displacement, and strain, and its ability to accurately estimate deformations under different geological conditions.
It is necessary to timely and accurately estimate the surface deformations in mining areas, especially the 3-D deformations during surface movement. At present, nearly all mining-induced 3-D deformations retrieved by interferometric synthetic aperture radar (InSAR) pertain to the SAR imaging interval. Research on progressive 3-D deformations during surface movement is limited, and the existing approaches are unsatisfactory in practical engineering. Aiming at these challenges, we proposed a novel method for deriving mining-induced 3-D surface deformations at any moment by integrating single InSAR interferogram (SII), the Gompertz time function, and the probability integral model (PIM), named the SII-GPIM method. We established an inversion approach for GPIM parameters and derived the mining-induced 3-D surface deformations at any moment. Subsequently, we conducted experiments considering two ALOS PALSAR images in the Huaibei mining area. The accuracy of the proposed method was evaluated in subsidence, tilt, curvature, horizontal displacement, and horizontal strain. Compared with existing methods, the SII-GPIM method is the state of the art. Additionally, we assessed the building damage, performance of parameter inversion, and method generality. The results demonstrated that the proposed method can accurately determine the mining-induced 3-D surface deformations and deformation level at any moment under different geological mining conditions. Moreover, accurate GPIM parameters can be acquired with only two SAR images and traditional measurement is nearly not required. Consequently, the SII-GPIM method owns great value for improving economic efficiency, assessing building damage, and restoring the ecological environment in the mining area.
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