Bulletin of Surveying and Mapping ›› 2025, Vol. 0 ›› Issue (3): 15-20.doi: 10.13474/j.cnki.11-2246.2025.0303

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Application of time series InSAR technology in surface subsidence monitoring and spatio-temporal evolution analysis in mining area

ZHANG Yuxin1, YUAN Xiping2,3, GAN Shu1,2, PENG Xiang1, WANG Song4   

  1. 1. College of Land and Resources Engineering, Kunming University of Science and Technology, Kunming 650000, China;
    2. Engineering Research Center of Plateau and Mountain Spatial Information Mapping Technology Application, Yunnan University, Kunming 650000, China;
    3. School of Earth Science and Engineering, West Yunnan University of Applied Technology, Dali 671000, China;
    4. Huili Caitong Iron and Titanium Co., Ltd., Liangshan 615000, China
  • Received:2024-05-07 Published:2025-04-03

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Abstract: In view of the hazards caused by surface subsidence to the safety, environment, socio-economic development and sustainability of resource utilization in the mining area, 63 Sentinel-1A data from December 31, 2021 to March 2, 2024 were first obtained, and SBAS-InSAR (time series interferometry) technology was adopted to monitor the surface deformation of Baicao mining area. The results of surface settlement rate and cumulative settlement in the mine area are obtained, and then the reliability analysis of the monitoring results is carried out by using the measured data. Finally, the settlement of the mine area is predicted based on the LSTM model, and the spatiotemporal variation characteristics and evolution rules of the settlement of the mine area are analyzed in detail.The final conclusions are as follows: ① Spatially, the surface subsidence of Baichuang Mining area is mainly concentrated in the west of the mining area, with the maximum subsidence of -316.86mm and the maximum annual average subsidence rate of -148.4mm/a, and the total subsidence area of 0.6236km2, of which the heavy and extremely heavy subsidence area of 0.2804km2 needs to be monitored.②In time series, the area with severe subsidence starts to settle from the monitoring starting point, and the subsidence rate tends to be uniform. If no protection is taken, the area will continue to settle in the future, and the settlement may be intensified.③The fitting degree of measured data and monitoring data is high, and the coefficient of determination R2 is up to 0.994. The prediction effect of LSTM prediction model on monitoring data is good, and the linear fitting coefficient of determination R2 of predicted value and monitoring value can reach more than 0.946, indicating that the prediction of surface settlement by LSTM model can meet the requirement of accuracy. The experimental results can provide technical support for disaster prevention and control in mining areas, and provide strong support for more accurate surface deformation evaluation in mining areas.

Key words: temporal InSAR, SBAS-InSAR, surface deformation monitoring, spatio-temporal evolution, LSTM model

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