Abstract: On June 16, 2024, an extreme rainfall event occurred in the Fujian-Guangdong-Jiangxi junction area, triggering tens of thousands of landslides and causing significant casualties and property losses. This study aims to rapidly identify the characteristics and driving factors of landslides to provide data support for disaster forecasting, early warning, and risk management. Post-disaster optical imagery was used for intelligent landslide identification, supplemented by on-site validation, to analyze the spatial distribution and developmental characteristics of the landslides. The study further investigated the driving factors by integrating the meteorological, ecological factors, geological conditions topographic features. The results revealed a total of 35,407 landslides, covering an area of approximately 41.27 km², predominantly small-scale and concentrated in mountainous areas where rainfall exceeded 250 mm. Natural landslides exhibited relatively regular shapes and higher mobility, while landslides induced by engineering activities showed more complex shapes and lower mobility. The distribution of landslides was significantly influenced by the meteorological, ecological factors, geological conditions and topographic characteristics. Natural landslides were primarily controlled by topography, whereas engineering-induced landslides displayed greater randomness. This study deepens the understanding of the characteristics and driving mechanisms of clustered landslides, providing valuable scientific guidance for disaster prevention, mitigation, and relief efforts.