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Article

A New Strategy for Extracting 3D Deformation of Mining Areas from a Single-Geometry Synthetic Aperture Radar Dataset

1
College of Mining and Technology, Ural State Mining University, Ekaterinburg 620000, Russia
2
Chinese-Russian Institute, Ural Federal University, Ekaterinburg 620000, Russia
3
College of Civil Engineering, Saint Petersburg State University of Architecture and Civil Engineering, St. Petersburg 190005, Russia
4
School of Environment Science and Spatial Informatics, China University of Mining and Technology (CUMT), Xuzhou 221116, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2023, 15(21), 5244; https://doi.org/10.3390/rs15215244
Submission received: 18 September 2023 / Revised: 31 October 2023 / Accepted: 3 November 2023 / Published: 4 November 2023

Abstract

This paper presents a strategy for extracting three-dimensional (3D) mining deformation from a single-geometry synthetic aperture radar (SAR) dataset. In light of the directionality of horizontal displacement caused by underground mining, we first re-model the proportional relationship between horizontal displacement and horizontal gradient of subsidence. Afterward, to improve the stability of the re-model, a solution strategy is proposed by setting different solution starting points and directions. The proposed method allows hiring of arbitrary single-geometry SAR data (e.g., air-borne, space-borne, and ground-borne SAR data) to reconstruct 3D displacements of mining areas. The proposed method has been validated through simulation and in-site data. The simulation data monitoring results indicate that the root mean square errors (RMSE) of the 3D displacements extracted by the proposed strategy are 0.45, 0.5, and 2.98 mm for the vertical subsidence, east–west, and north–south horizontal displacements, respectively. The in-site data monitoring results indicate that the RMSE of vertical subsidence compared with the leveling data are 7.3 mm. Furthermore, the MSBAS method was employed to further validate the reliability of the proposed method, the results show that the proposed method is effective to obtain the 3D deformation of the mining area, which greatly improves the applicability of SAR interferometry in the 3D deformation monitoring of the mining areas.
Keywords: synthetic aperture radar (SAR) interferometry (InSAR); three-dimensional (3D) deformation; mining subsidence; single-geometry SAR dataset synthetic aperture radar (SAR) interferometry (InSAR); three-dimensional (3D) deformation; mining subsidence; single-geometry SAR dataset

Share and Cite

MDPI and ACS Style

Zhao, R.; Viktorovich, Z.A.; Li, J.; Chen, C.; Zheng, M. A New Strategy for Extracting 3D Deformation of Mining Areas from a Single-Geometry Synthetic Aperture Radar Dataset. Remote Sens. 2023, 15, 5244. https://doi.org/10.3390/rs15215244

AMA Style

Zhao R, Viktorovich ZA, Li J, Chen C, Zheng M. A New Strategy for Extracting 3D Deformation of Mining Areas from a Single-Geometry Synthetic Aperture Radar Dataset. Remote Sensing. 2023; 15(21):5244. https://doi.org/10.3390/rs15215244

Chicago/Turabian Style

Zhao, Ruonan, Zhabko Andrey Viktorovich, Junfeng Li, Chuang Chen, and Meinan Zheng. 2023. "A New Strategy for Extracting 3D Deformation of Mining Areas from a Single-Geometry Synthetic Aperture Radar Dataset" Remote Sensing 15, no. 21: 5244. https://doi.org/10.3390/rs15215244

APA Style

Zhao, R., Viktorovich, Z. A., Li, J., Chen, C., & Zheng, M. (2023). A New Strategy for Extracting 3D Deformation of Mining Areas from a Single-Geometry Synthetic Aperture Radar Dataset. Remote Sensing, 15(21), 5244. https://doi.org/10.3390/rs15215244

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