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

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.

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Publication Details

Journal
Land
Published
2025-05-04
DOI
https://doi.org/10.3390/land14050992
Citations
4
Primary Topic
Synthetic Aperture Radar (SAR) Applications and Techniques
Type
article
Field-Weighted Citation Impact
19.97
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Wavelet-Based Analysis of Subsidence Patterns and High-Risk Zone Delineation in Underground Metal Mining Areas Using SBAS-InSAR

Ni Zeng, Zhuoying Tan, Aboubakar Siddique, Linsen Xu et al.
4 citations
Land
Synthetic Aperture Radar (SAR) Applications and Techniques
19.97
article

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

Ni Zeng, Zhuoying Tan, Aboubakar Siddique, Linsen Xu, Xin Wang, Jiang Li, Jianbing Zhang, Yinglin Yang, Jintao Dang
article en
4 citations

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.

LandVol. 14(5)
Tongling Nonferrous Metals Group Holding (China) (CN), University of Science and Technology Beijing (CN)
Openalex Percentile: Top 1%
Synthetic Aperture Radar (SAR) Applications and Techniques
19.97
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