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Investigating Mining-Induced Surface Subsidence in Mountainous Areas Using Integrated InSAR and GNSS Monitoring.

Qingfeng Hu1, Runjin Hou1, Yingchao Kou2

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Summary
This summary is machine-generated.

This study integrates Interferometric Synthetic Aperture Radar (InSAR) and Global Navigation Satellite System (GNSS) to enhance mining subsidence monitoring. The combined method significantly improves accuracy, providing more reliable surface deformation data.

Keywords:
GNSSInSARPPPmining area monitoringmining-induced subsidence

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Area of Science:

  • Geodesy
  • Remote Sensing
  • Mining Engineering

Background:

  • Mining activities cause significant surface subsidence, posing risks to infrastructure and the environment.
  • Traditional monitoring methods like InSAR and GNSS have limitations when used individually for mining subsidence.
  • Accurate monitoring of mining-induced surface deformation is crucial for risk assessment and mitigation.

Purpose of the Study:

  • To develop and validate an integrated InSAR and GNSS method for precise monitoring of mining-induced surface subsidence.
  • To overcome the limitations of individual InSAR and GNSS techniques in capturing complex subsidence patterns.
  • To provide comprehensive and reliable surface deformation data in mining areas.

Main Methods:

  • Time-series cumulative subsidence basin calculation using InSAR.
  • Identification of large-gradient deformation zones to distinguish subsidence edges and centers.
  • Integration of InSAR and GNSS models for reconstructing subsidence basins, especially in high-gradient areas.
  • Spatial interpolation for continuous surface deformation information in a geographic coordinate system.

Main Results:

  • The integrated method achieved a maximum surface subsidence rate of -186.68 mm/year and a maximum subsidence amount of 248 mm in the study area.
  • Root mean square error was reduced by 96.8% compared to InSAR alone and 64.4% compared to the GNSS probability integral method.
  • The results demonstrated high consistency with actual ground conditions, validating the method's effectiveness.

Conclusions:

  • The proposed integrated InSAR and GNSS approach significantly enhances the accuracy and reliability of mining subsidence monitoring.
  • This method effectively compensates for the individual limitations of InSAR and GNSS, offering superior monitoring capabilities.
  • The findings provide a more comprehensive understanding of surface deformation in mining areas, supporting better management and safety.