Optimized UAV-LiDAR Workflows for Fine-Scale Stream Network Mapping in Low-Gradient Wetlands: A Case Study of the Kushiro Wetland, Japan

Accurate delineation of stream networks in low-gradient wetlands remains challenging due to subtle topographic variation and dense vegetation cover. This study systematically evaluated 48 Unmanned Aerial Vehicle Light Detection and Ranging (UAV-LiDAR) processing workflows through 1128 pairwise comparisons to identify optimal approaches for mapping fine-scale channels in Japan’s Kushiro Wetland, a Ramsar-designated ecosystem. The workflows combined three ground filtering methods (Progressive Morphological Filter, Cloth Simulation Filter, Multiscale Curvature Classification), four interpolation techniques (Inverse Distance Weighting, Triangulated Irregular Network, Kriging, Multilevel B-spline Approximation), two sink-filling algorithms (Planchon & Darboux; Wang & Liu), and two flow direction models (D8, D-infinity). Performance was first assessed using pixel-based Intersection over Union (IoU) metrics to quantify inter-method consensus. Independent plausibility-based validation was then conducted using near-contemporaneous Sentinel-2 imagery. Although pairwise statistical analysis identified workflows that achieved high inter-method consensus (median IoU = 0.90), external validation demonstrated that the CSF-MBA-Planchon-D8 workflow provided the most realistic presentation of optically observable channel corridors (validation IoU ≈ 0.85). These findings reveal that high inter-method agreement does not necessarily imply accurate landscape representation; multiple workflows may converge on systematically biased solutions. Ground filtering exerted the strongest influence on pairwise consensus, whereas plausibility-based validation highlighted the importance of selecting workflow combinations that preserve subtle channel morphology. Sink-filling and flow direction choices exerted comparatively minor effects in this low-gradient setting. The proposed dual-validation framework provides methodological guidance for wetland restoration planning and highlights the necessity of external validation in LiDAR-derived hydrological feature extraction.