Spatiotemporal Evolution of Mining-Induced Surface Subsidence in Thick Unconsolidated-Layer Coal–Cropland Overlapping Areas Using Multi-Temporal UAV LiDAR and Leveling Measurements

Mining-induced subsidence affects cropland use and land management in coal–cropland overlapping areas. Leveling provides high-precision subsidence time series but limited spatial sampling, whereas multi-temporal unmanned aerial vehicle light detection and ranging (UAV LiDAR) provides spatially continuous terrain-change information, although the uncertainty of digital elevation model (DEM) differencing must be assessed. Three UAV LiDAR surveys (30 May 2025, 25 December 2025, and 14 June 2026) and leveling measurements (March 2025–April 2026) were combined to analyze subsidence at the 32311 working face of Xutuan Coal Mine, Anhui Province, China, during working-face advance and after mining cessation. The level of detection at the 95% confidence level (LoD95) was calculated from elevation residuals in stable areas, and LiDAR-derived subsidence was validated against leveling measurements at 12 points. The LoD95 values of the two cross-sensor differencing periods were 131.9 and 148.8 mm, indicating that changes smaller than approximately 0.13–0.15 m could not be reliably distinguished from measurement error in this study. Leveling-derived cumulative subsidence at these points ranged from 19.76 to 392.95 mm during 30 May–19 December 2025, comprising 19.76–69.75 mm at the six weak-subsidence points and 185.13–392.95 mm at the six strong-subsidence points. LiDAR-derived subsidence showed a strong relationship with leveling measurements at the six strong-subsidence points (R2 = 0.87, RMSE = 29.9 mm), whereas the relationship was weak at the six weak-subsidence points (R2 = 0.15). At seven representative leveling points, post-cessation residual subsidence accounted for 15.9–31.2% (mean 20.8%) of the final cumulative subsidence recorded during the leveling period. Relative to 30 May 2025, the area with subsidence exceeding 150 mm increased from 15.31 ha on 25 December 2025 to 16.73 ha on 14 June 2026. The two techniques thus provide complementary temporal and spatial information: leveling measurements reveal the persistence of post-cessation subsidence, while UAV LiDAR characterizes changes in the spatial distribution of cumulative subsidence. Continued monitoring after mining cessation is therefore necessary to capture ongoing surface movement and its spatial characteristics.

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Publication Details

Journal
Remote Sensing
Published
2026-11-11
DOI
https://doi.org/10.3390/rs18223883
Primary Topic
Geotechnical and Mining Engineering
Type
article
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article

Spatiotemporal Evolution of Mining-Induced Surface Subsidence in Thick Unconsolidated-Layer Coal–Cropland Overlapping Areas Using Multi-Temporal UAV LiDAR and Leveling Measurements

Chuangang Gong, Song Ziheng, Geng Jijun, Boxuan Du et al.
Remote Sensing
Geotechnical and Mining Engineering
article

Spatiotemporal Evolution of Mining-Induced Surface Subsidence in Thick Unconsolidated-Layer Coal–Cropland Overlapping Areas Using Multi-Temporal UAV LiDAR and Leveling Measurements

Chuangang Gong, Song Ziheng, Geng Jijun, Boxuan Du, Qingmei Huang, Ruimin He
article en

Abstract

Mining-induced subsidence affects cropland use and land management in coal–cropland overlapping areas. Leveling provides high-precision subsidence time series but limited spatial sampling, whereas multi-temporal unmanned aerial vehicle light detection and ranging (UAV LiDAR) provides spatially continuous terrain-change information, although the uncertainty of digital elevation model (DEM) differencing must be assessed. Three UAV LiDAR surveys (30 May 2025, 25 December 2025, and 14 June 2026) and leveling measurements (March 2025–April 2026) were combined to analyze subsidence at the 32311 working face of Xutuan Coal Mine, Anhui Province, China, during working-face advance and after mining cessation. The level of detection at the 95% confidence level (LoD95) was calculated from elevation residuals in stable areas, and LiDAR-derived subsidence was validated against leveling measurements at 12 points. The LoD95 values of the two cross-sensor differencing periods were 131.9 and 148.8 mm, indicating that changes smaller than approximately 0.13–0.15 m could not be reliably distinguished from measurement error in this study. Leveling-derived cumulative subsidence at these points ranged from 19.76 to 392.95 mm during 30 May–19 December 2025, comprising 19.76–69.75 mm at the six weak-subsidence points and 185.13–392.95 mm at the six strong-subsidence points. LiDAR-derived subsidence showed a strong relationship with leveling measurements at the six strong-subsidence points (R2 = 0.87, RMSE = 29.9 mm), whereas the relationship was weak at the six weak-subsidence points (R2 = 0.15). At seven representative leveling points, post-cessation residual subsidence accounted for 15.9–31.2% (mean 20.8%) of the final cumulative subsidence recorded during the leveling period. Relative to 30 May 2025, the area with subsidence exceeding 150 mm increased from 15.31 ha on 25 December 2025 to 16.73 ha on 14 June 2026. The two techniques thus provide complementary temporal and spatial information: leveling measurements reveal the persistence of post-cessation subsidence, while UAV LiDAR characterizes changes in the spatial distribution of cumulative subsidence. Continued monitoring after mining cessation is therefore necessary to capture ongoing surface movement and its spatial characteristics.

Remote SensingVol. 18(22)
Sun Yat-sen University (CN), Anhui University of Science and Technology (CN)
Geotechnical and Mining Engineering
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