Multi-Temporal UAV Photogrammetry and DEM Differencing for Landslide Deformation Monitoring in a Mining Area, Inner Mongolia

This study investigates slope deformation in Baiyinhu No. 2 open-pit mine (Inner Mongolia Plateau) using multi-temporal UAV photogrammetric surveys conducted in June and September 2024. High-resolution full-frame imagery (GSD ~6.3 cm) and precise POS data (GNSS/IMU, horizontal ±3 cm, vertical ±5 cm) were processed in Pix4D Mapper to generate orthoimages and DEMs. Model re-projection error (~0.1 px), point cloud density (512 pts/m²), and GCP-based RMSE (horizontal 0.091 m, vertical 0.080 m) demonstrate robust geometric accuracy. DEM differencing revealed localized subsidence up to ~0.9 m at the midsection and toe of the landslide. Additional analysis of four deformation bodies (April–September 2023) showed vertical displacements of 0.2–0.6 m. The observed deformation patterns are structurally controlled, aligning with bedding and fault orientation. UAV-based monitoring significantly reduces cost (~70% per point) and enables centimeter to decimeter detection of micro-deformation, providing a reliable basis for slope stability assessment in mining areas. The methodology offering an effective framework for deformation mapping and hazard evaluation.

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Publication Details

Journal
Journal of Progress in Civil Engineering
Published
2025-08-31
DOI
https://doi.org/10.53469/jpce.2025.07(08).03
Primary Topic
Landslides and related hazards
Type
article
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article

Multi-Temporal UAV Photogrammetry and DEM Differencing for Landslide Deformation Monitoring in a Mining Area, Inner Mongolia

Chen Cao, Jiayi Hu
Journal of Progress in Civil Engineering
Landslides and related hazards
article

Multi-Temporal UAV Photogrammetry and DEM Differencing for Landslide Deformation Monitoring in a Mining Area, Inner Mongolia

Chen Cao, Jiayi Hu
article en

Abstract

This study investigates slope deformation in Baiyinhu No. 2 open-pit mine (Inner Mongolia Plateau) using multi-temporal UAV photogrammetric surveys conducted in June and September 2024. High-resolution full-frame imagery (GSD ~6.3 cm) and precise POS data (GNSS/IMU, horizontal ±3 cm, vertical ±5 cm) were processed in Pix4D Mapper to generate orthoimages and DEMs. Model re-projection error (~0.1 px), point cloud density (512 pts/m²), and GCP-based RMSE (horizontal 0.091 m, vertical 0.080 m) demonstrate robust geometric accuracy. DEM differencing revealed localized subsidence up to ~0.9 m at the midsection and toe of the landslide. Additional analysis of four deformation bodies (April–September 2023) showed vertical displacements of 0.2–0.6 m. The observed deformation patterns are structurally controlled, aligning with bedding and fault orientation. UAV-based monitoring significantly reduces cost (~70% per point) and enables centimeter to decimeter detection of micro-deformation, providing a reliable basis for slope stability assessment in mining areas. The methodology offering an effective framework for deformation mapping and hazard evaluation.

Journal of Progress in Civil EngineeringVol. 7(8)
Jilin University (CN)
Openalex Percentile: Top 69%
Landslides and related hazards
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Multi-Temporal UAV Photogrammetry and DEM Differencing for Landslide Deformation Monitoring in a Mining Area, Inner Mongolia — Chen Cao, Jiayi Hu · Journal of Progress in Civil Engineering (2025) | TGRS Research Map | TGRS