Wavelet-Based Analysis of Subsidence Patterns and High-Risk Zone Delineation in Underground Metal Mining Areas Using SBAS-InSAR

Jiang Li, Zhuoying Tan (), Nuobei Zeng, Linsen Xu, Yinglin Yang, Aboubakar Siddique, Junfeng Dang, Jianbing Zhang and Xin Wang
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Jiang Li: School of Resources and Safety Engineering, University of Science and Technology Beijing, Beijing 100083, China
Zhuoying Tan: School of Resources and Safety Engineering, University of Science and Technology Beijing, Beijing 100083, China
Nuobei Zeng: School of Resources and Safety Engineering, University of Science and Technology Beijing, Beijing 100083, China
Linsen Xu: School of Resources and Safety Engineering, University of Science and Technology Beijing, Beijing 100083, China
Yinglin Yang: School of Resources and Safety Engineering, University of Science and Technology Beijing, Beijing 100083, China
Aboubakar Siddique: School of Resources and Safety Engineering, University of Science and Technology Beijing, Beijing 100083, China
Junfeng Dang: Zhongtiaoshan Non-Ferrous Metals Group Co., Ltd., Yuncheng 043706, China
Jianbing Zhang: Zhongtiaoshan Non-Ferrous Metals Group Co., Ltd., Yuncheng 043706, China
Xin Wang: Zhongtiaoshan Non-Ferrous Metals Group Co., Ltd., Yuncheng 043706, China

Land, 2025, vol. 14, issue 5, 1-26

Abstract: Underground metal mines operated using the natural caving method often result in significant surface collapses. Key parameters such as settlement magnitude, settlement rate, settlement extent, and the influence of underground mining on surface deformation warrant serious attention. However, due to the long operational timespan of mines and incomplete data from early collapse events, coupled with the inaccessibility of collapse zones for field measurements, it is challenging to obtain accurate displacement data, thereby posing significant difficulties for follow-up research. This study employs small baseline subset InSAR (SBAS-InSAR) technology to retrieve time series data on early-stage surface displacement and deformation rates in collapse areas, thereby compensating for the lack of historical data and eliminating the safety risks associated with on-site measurements. The 5th percentile of settlement rates across all monitoring points is used to define the severe settlement threshold, determined to be −42.1 mm/year. Continuous wavelet transform (CWT) is applied to calculate the time-series power spectrum, allowing the analysis of long-term stable and periodic settlement patterns in the collapse area. The instantaneous change rate at each point in the study area is identified. Using the 97th percentile of change rates in the time series, the number of severe change events at each point is determined. High-incidence zones of sudden surface deformation are visualized through QGIS 3.16 heat map clustering. The high-risk collapse area, identified by integrating both long-term stable settlement and sudden surface deformation patterns, accounts for multiple deformation modes. This provides robust technical support for the management of mine collapse zones and offers important theoretical guidance.

Keywords: mining subsidence; velocity threshold; SBAS-InSAR; wavelet transform (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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