Database development and geometric characterization of the shallow landslides triggered bythe 16 June 2024 extreme rainfall event in Meizhou, Guangdong (China)
摘要
In recent years, climate change has increased the frequency of extreme rainfall events. As a result, rainfall-induced landslides have become one of the most widespread and severe geological hazards worldwide. This study focuses on the widespread shallow landslides triggered by an extreme rainstorm on 16 June 2024 in Meizhou, Guangdong Province. Using high-resolution pre- and post-event remote sensing imagery, we employed manual visual interpretation methods, combined with existing landslide records, to construct a detailed landslide catalog database. We quantitatively analyzed landslide geometric properties from this inventory, including the length–width ratio (ΛL), ellipticity index (e), and roundness. The results reveal that: (1) the inventory for this event consists of 14,958 landslides, covering 34.48 km2, the most extensive landslide dataset for the region. The spatial impact of the event was predominated by a high number of landslides with relatively small individual sizes. (2) Landslide geometry shows a clear dependence on area. When the landslide area exceeds 5000 m2, roundness sharply decreases by 37%, while the ΛL increases by a factor of 2.4. Landslides exceeding 10,000 m2 exhibit higher ΛL values (ΛL = 3.8 ± 0.6) and lower ellipticity (e = − 0.32 ± 0.15), indicating more elongated and complex morphologies. This study provides a solid data foundation and theoretical support for addressing landslide disasters triggered by short-duration heavy rainfall in southeastern coastal China, with significant practical importance for enhancing regional landslide early warning capabilities and disaster risk management.