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

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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.
Funding Information
  • State Key Program of National Natural Science Foundation of China (52239008)
  • National Natural Science Foundation of China (U20A20112)
  • Project of Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone (HZQB-KCZYB-2020083)
  • Guangdong Provincial Key Laboratory of Intelligent and Resilient Structures for Civil Engineering (2023B1212010004)

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