Analysis of landslide on Meizhou-Dapu expressway based on satellite remote sensing

Abstract Background On May 1, 2024, a landslide occurred on the embankment slope of the Meizhou-Dapu (Meida) Expressway in Guangdong Province, China, resulting in the collapse of a section of pavement, 23 vehicle crashes, 48 deaths, and 30 injuries. This study utilized the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) in conjunction with Sentinel-1 A radar remote sensing images to compile the temporal and spatial distributions of surface displacement of the Meida embankment slope. By integrating satellite remote sensing images, site conditions, rainfall records, and digital elevation model (DEM), the displacement pattern of the embankment slope was analyzed, and the mechanism of the landslide was revealed. Results The results show that there is an obvious cumulative displacement concentration in the landslide area before the landslide, cumulative displacement progressively increased towards the slope toe, and an obvious separation trend is observed between the slope crest and the slope toe. In addition, the temporal displacement results show the consistent relationship between surface displacement and rainfall. Conclusions The research results indicate a slowly progressive separation trend between the slope crest and the toe long before the accident, indicating a traction-type landslide mode. The surface displacement is significantly correlated with seasonal rainfall, which validates the conclusion that the abnormally heavy rainfall is the main triggering factor of this landslide. This study demonstrates the effectiveness of integrated remote sensing technologies in monitoring the slowly changing traction landslide, like the Meida landslide, which could be a promising approach for the monitoring and early warning of landslide hazards in the future.

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Publication Details

Journal
Geoenvironmental Disasters
Published
2025-07-14
DOI
https://doi.org/10.1186/s40677-025-00331-x
Citations
7
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
16.95

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article

Analysis of landslide on Meizhou-Dapu expressway based on satellite remote sensing

Xiao-bin Zheng, Wenjun Lu, Limin Zhang, J.H. Li et al.
7 citations
Geoenvironmental Disasters
Landslides and related hazards
16.95
article

Analysis of landslide on Meizhou-Dapu expressway based on satellite remote sensing

Xiao-bin Zheng, Wenjun Lu, Limin Zhang, J.H. Li, Ruochen Jiang
article en
7 citations

Abstract

Abstract Background On May 1, 2024, a landslide occurred on the embankment slope of the Meizhou-Dapu (Meida) Expressway in Guangdong Province, China, resulting in the collapse of a section of pavement, 23 vehicle crashes, 48 deaths, and 30 injuries. This study utilized the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) in conjunction with Sentinel-1 A radar remote sensing images to compile the temporal and spatial distributions of surface displacement of the Meida embankment slope. By integrating satellite remote sensing images, site conditions, rainfall records, and digital elevation model (DEM), the displacement pattern of the embankment slope was analyzed, and the mechanism of the landslide was revealed. Results The results show that there is an obvious cumulative displacement concentration in the landslide area before the landslide, cumulative displacement progressively increased towards the slope toe, and an obvious separation trend is observed between the slope crest and the slope toe. In addition, the temporal displacement results show the consistent relationship between surface displacement and rainfall. Conclusions The research results indicate a slowly progressive separation trend between the slope crest and the toe long before the accident, indicating a traction-type landslide mode. The surface displacement is significantly correlated with seasonal rainfall, which validates the conclusion that the abnormally heavy rainfall is the main triggering factor of this landslide. This study demonstrates the effectiveness of integrated remote sensing technologies in monitoring the slowly changing traction landslide, like the Meida landslide, which could be a promising approach for the monitoring and early warning of landslide hazards in the future.

Geoenvironmental DisastersVol. 12(1)
Hong Kong University of Science and Technology (HK), Harbin Institute of Technology (CN), HKUST Shenzhen Research Institute (CN), Key Laboratory of Guangdong Province (CN), Guangdong Institute of Intelligent Manufacturing (CN), University of Hong Kong (HK)
National Natural Science Foundation of China
Openalex Percentile: Top 1%
Landslides and related hazards
16.95
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