Time-Series InSAR Technology for Monitoring and Analyzing Surface Deformations in Mining Areas Affected by Fault Disturbances

Faults, as unique geological structures, disrupt the mechanical connections between rock masses. During coal mining, faults in the overlying strata can disturb the original stress balance, leading to fault activation and altering the typical subsidence patterns. This can result in abnormal ground de...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2024-12, Vol.16 (24), p.4811
Main Authors: He, Kuan, Zou, Youfeng, Han, Zhigang, Huang, Jilei
Format: Article
Language:English
Subjects:
abnormal deformation
Coal mining
Damage patterns
Deformation
Deformation effects
Environmental impact
fault
Fault lines
Geological hazards
Geological structures
Geology
Methods
mining subsidence
Monitoring
Subsidence
Technology assessment
Time series
time-series InSAR
Topography
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Summary:Faults, as unique geological structures, disrupt the mechanical connections between rock masses. During coal mining, faults in the overlying strata can disturb the original stress balance, leading to fault activation and altering the typical subsidence patterns. This can result in abnormal ground deformation and significant damage to surface structures, posing a serious geological hazard in mining areas. This study examines the influence of a known fault (F13 fault) on ground subsidence in the Wannian Mine of the Fengfeng Mining Area. We utilized 12 Sentinel-1A images and applied SBAS-InSAR, StaMPS-InSAR, and DS-InSAR time-series InSAR methods, alongside the D-InSAR method, to investigate surface deformations caused by the F13 fault. The monitoring accuracy of these methods was evaluated using leveling measurements from 28 surface movement observation stations. In addition, the density of effective monitoring points and the relative strengths and limitations of the three time-series methods were compared. The findings indicate that, in low deformation areas, DS-InSAR has a monitoring accuracy of 7.7 mm, StaMPS-InSAR has a monitoring accuracy of 16.4 mm, and SBAS-InSAR has an accuracy of 19.3 mm.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs16244811