Combining low-cost drone surveys and citizen science to identify flood-prone areas

Introduction Natural disasters are becoming increasingly frequent, highlighting the need for accessible and reliable tools to support flood risk assessment, particularly in data-scarce regions. Methods This study evaluated the accuracy of Digital Elevation Models (DEMs) generated from UAV-based photogrammetry at two sites in the Upper Paranapanema River Basin (São Paulo State, Brazil). Surveys were conducted using Phantom 4 Pro and Mavic 3E RTK drones and validated against GNSS RTK geodetic measurements. UAV-derived DEMs were compared with freely available satellite datasets (SRTM and ANADEM) using RMSE, MAE, and PBIAS metrics. To assess practical implications, historical flood extents were reconstructed by combining DEMs with flood watermarks observed on utility poles, while resident interviews were used as an independent validation dataset. Results UAV-derived DEMs exhibited higher accuracy than satellite-based DEMs and showed improved agreement with citizen-reported flood limits. High-resolution UAV data better captured flood-relevant microtopography, particularly in urban areas, leading to more realistic flood inundation reconstructions. Discussion The proposed framework advances beyond conventional DEM-topographic survey comparisons by integrating low-cost UAV data with local flood observations, enabling operationally robust flood extent mapping. The results demonstrate that UAV-based DEMs represent an effective and affordable alternative to costly LiDAR or extensive GNSS surveys, reinforcing their potential for flood risk mapping in isolated and data-limited regions.