Time-series surface deformation monitoring and analysis in mining area based on StaMPS technology

Guozhen Zhang; Wei Xu; Pingping Huang; Weixian Tan; Yaolong Qi

doi:10.1117/12.2667452

10 February 2023 Time-series surface deformation monitoring and analysis in mining area based on StaMPS technology

Guozhen Zhang, Wei Xu, Pingping Huang, Weixian Tan, Yaolong Qi

Proceedings Volume 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022); 125521N (2023) https://doi.org/10.1117/12.2667452
Event: International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 2022, Kunming, China

Abstract

Mining coal mines can cause large scale and extensive surface subsidence in mining areas. It not only affects the economic development of the mine, but also poses a threat to the surrounding environment and the safety of people's lives. Therefore, it is very important to carry out long time surface monitoring in mining area. For D-InSAR (Differential Interferometric Synthetic Aperture Radar) technology is vulnerable to the phenomenon of unstable monitoring results caused by temporal and spatial decoherence and atmospheric delays, this study uses the StaMPS (Stanford Method for Persistent Scatterers) technology for time-series subsidence monitoring. 22 Sentinel-1A images from June 15, 2019 to December 6, 2020 were used to monitor the subsidence of Zhangshuanglou Coal Mine. The results show that: During the monitoring period, there are three obvious subsidence funnels in Zhangshuanglou Coal Mine. The study area is sinking almost all the time with only a brief rebound. The maximum displacement velocity reached -63.9 mm/yr and maximum cumulative displacement value reached -95.8 mm. Moreover, the subsidence value and velocity are almost inversely proportional to the distance to the center of the funnel. This proves that StaMPS technology and Sentinel-1A data can be used to monitor surface subsidence in mining areas and provide a basis for the study of the subsidence pattern and causes of the target area.

Citation Download Citation

Guozhen Zhang, Wei Xu, Pingping Huang, Weixian Tan, and Yaolong Qi "Time-series surface deformation monitoring and analysis in mining area based on StaMPS technology", Proc. SPIE 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 125521N (10 February 2023); https://doi.org/10.1117/12.2667452

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KEYWORDS

Mining

Technology

Deformation

Interferograms

Picosecond phenomena

Error analysis

Environmental monitoring

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