Pre-, Co-, and Post-Failure Deformation Analysis of the Catastrophic Xinjing Open-Pit Coal Mine Landslide, China, from Optical and Radar Remote Sensing Observations

Landslide risks in open-pit mine areas are heightened by artificial slope modifications necessary for mining operations, endangering human life and property. On 22 February 2023, a catastrophic landslide occurred at the Xinjing Open-Pit Coal Mine in Inner Mongolia, China, resulting in 53 fatalities and economic losses totaling 28.7 million USD. Investigating the pre-, co-, and post-failure deformation processes and exploring the potential driving mechanisms are crucial to preventing similar tragedies. In this study, we used multi-source optical and radar images alongside satellite geodetic methods to analyze the event. The results revealed pre-failure acceleration at the slope toe, large-scale southward displacement during collapse, and ongoing deformation across the mine area due to mining operations and waste accumulation. The collapse was primarily triggered by an excessively steep, non-compliant artificial slope design and continuous excavation at the slope’s base. Furthermore, our experiments indicated that the commonly used Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) significantly underestimated landslide deformation due to the maximum detectable deformation gradient (MDDG) limitation. In contrast, the high-spatial-resolution Fucheng-1 provided more accurate monitoring results with a higher MDDG. This underscores the importance of carefully assessing the MDDG when employing InSAR techniques to monitor rapid deformation in mining areas.

Authors

Institutions

Publication Details

Journal
Remote Sensing
Published
2024-12-25
DOI
https://doi.org/10.3390/rs17010019
Citations
10
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
7.10

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Pre-, Co-, and Post-Failure Deformation Analysis of the Catastrophic Xinjing Open-Pit Coal Mine Landslide, China, from Optical and Radar Remote Sensing Observations

Fengnian Chang, Hongwei Yin, H. S. Li, Shaochun Dong
10 citations
Remote Sensing
Landslides and related hazards
7.10
article

Pre-, Co-, and Post-Failure Deformation Analysis of the Catastrophic Xinjing Open-Pit Coal Mine Landslide, China, from Optical and Radar Remote Sensing Observations

Fengnian Chang, Hongwei Yin, H. S. Li, Shaochun Dong
article en
10 citations

Abstract

Landslide risks in open-pit mine areas are heightened by artificial slope modifications necessary for mining operations, endangering human life and property. On 22 February 2023, a catastrophic landslide occurred at the Xinjing Open-Pit Coal Mine in Inner Mongolia, China, resulting in 53 fatalities and economic losses totaling 28.7 million USD. Investigating the pre-, co-, and post-failure deformation processes and exploring the potential driving mechanisms are crucial to preventing similar tragedies. In this study, we used multi-source optical and radar images alongside satellite geodetic methods to analyze the event. The results revealed pre-failure acceleration at the slope toe, large-scale southward displacement during collapse, and ongoing deformation across the mine area due to mining operations and waste accumulation. The collapse was primarily triggered by an excessively steep, non-compliant artificial slope design and continuous excavation at the slope’s base. Furthermore, our experiments indicated that the commonly used Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) significantly underestimated landslide deformation due to the maximum detectable deformation gradient (MDDG) limitation. In contrast, the high-spatial-resolution Fucheng-1 provided more accurate monitoring results with a higher MDDG. This underscores the importance of carefully assessing the MDDG when employing InSAR techniques to monitor rapid deformation in mining areas.

Remote SensingVol. 17(1)
Nanjing University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 3%
Landslides and related hazards
7.10
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.