Paper
21 June 2024 Analysis of surface subsidence in Shenmu City based on SBAS-InSAR
Yibo Peng, Weifang Yang, Delong Zhang, Xiangrong Yan, Yuhao Hou, Motong Gao
Author Affiliations +
Proceedings Volume 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024); 131671A (2024) https://doi.org/10.1117/12.3029752
Event: International Conference on Remote Sensing, Mapping and Image Processing (RSMIP 2024), 2024, Xiamen, China
Abstract
Shenmu City, Yulin City, Shaanxi Province, is the largest coal-producing city (county) in China, and the rapid development of the mining industry has led to the problem of large-scale regional ground subsidence, which has become a major problem for the city. According to statistics, there are more than 200 disaster hazards in the city, including collapse and landslides, but the monitoring of ground deformation in the city is still blank. In this context, this paper uses SBAS-InSAR (small baseline subset InSAR) technology to monitor and analyze the ground deformation in Shenmu City. The results show that there are three main subsidence zones in Shenmu City, and there are several discrete subsidence zones within the main subsidence zones, and the maximum cumulative subsidence in the subsidence zones reaches -105 mm/a between January 2020 and December 2021. In addition, seven typical mining areas were selected from the three major subsidence zones, and the spatial and temporal variations of subsidence were analyzed for the seven mining areas. The results can provide a basis for the municipal construction of Shenmu City and the planning of safe production in each mining area, and make up for the gap in monitoring data of ground subsidence in large areas of the region.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yibo Peng, Weifang Yang, Delong Zhang, Xiangrong Yan, Yuhao Hou, and Motong Gao "Analysis of surface subsidence in Shenmu City based on SBAS-InSAR", Proc. SPIE 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024), 131671A (21 June 2024); https://doi.org/10.1117/12.3029752
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KEYWORDS
Mining

Deformation

Analytical research

Interferometry

Interferometry

Interferometric synthetic aperture radar

Interferometric synthetic aperture radar

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