UAV photogrammetry for riverine analysis: A systematic review of methodologies, accuracy, and challenges

Abstract

High-resolution spatial data is crucial for riverine modeling and flood mitigation. Traditional data often lacks necessary resolution or flexibility, making Unmanned Aerial Vehicles (UAVs) a transformative solution for generating precise Digital Elevation Models (DEMs). This systematic review analyzes 65 peer-reviewed studies published between 2014 and 2025. Following PRISMA guidelines, studies were selected based on specific inclusion and exclusion criteria focusing on riverine hydraulic applications to evaluate data acquisition methods, spatial accuracy, and operational challenges. The synthesis reveals a standard workflow using multirotor platforms, Structure from Motion (SfM) photogrammetry, and Ground Control Points (GCPs) to feed hydrodynamic models like HEC-RAS. While the literature consistently reports centimeter-level vertical accuracy—ideal for mapping flood inundation—critical challenges persist regarding the optical penetration of dense vegetation and submerged bathymetry. Ultimately, while UAV photogrammetry is a robust spatial analysis tool, advancing high-fidelity riverine analytics requires hybrid approaches integrating technologies like UAV-borne LiDAR and sonar. Creating these seamless topobathymetric models is essential for improving reliable flood risk management and informing effective environmental policy.