Spatial Analysis of Agricultural Land Damage Caused by the July 2025 Extreme Rainfall in the Sindeungcheon Basin, South Korea

Extreme rainfall events intensified by climate change have increased the need for accurate and spatially explicit assessments of agricultural damage. Conventional flood-inundation-based analyses primarily detect the extent of water coverage and often fail to capture cultivation-infeasible damage such as sediment burial and cropland washout. To overcome this limitation, this study directly mapped severe agricultural land damage in the Sindeungcheon basin, South Korea, following the extreme rainfall event of July 19, 2025, using 10-m Sentinel-2 Level-2A imagery acquired before (July 9) and after (August 1) the event. Damaged croplands were defined as areas where more than 50% of the field surface was covered by sediment or where notable erosion and soil exposure indicated physical loss of arable land. A random forest classifier using four multispectral bands (blue, green, red, near-infrared) achieved high performance, with an overall accuracy of 99.1% and a kappa coefficient of 0.93 based on independent field-verified samples. Of the 2,743.41 ha of agricultural land in the basin, 65.56 ha (2.39%) were classified as severely damaged. Field crops experienced the largest impact (34.92 ha, 2.79%), followed by paddy fields (25.02 ha, 2.35%). Damage exhibited a clear spatial gradient, with the highest damage ratio (3.64%) occurring within 100 m of the river, highlighting the dominance of flood-driven sediment transport. Numerous micro-scale (<0.05 ha) damage patches also indicated highly localized and heterogeneous disturbance patterns. The resulting dataset provides a detailed representation of extreme-event-induced agricultural loss and addresses the key limitations of inundation-only damage assessments by identifying actual cultivation- infeasible areas. This dataset can support economic loss estimation, post-disaster recovery planning, and spatial mitigation strategies aimed at reducing agricultural vulnerability to future extreme rainfall events.