Development of an Optical–Radar Fusion Method for Riparian Vegetation Monitoring and Its Application to Representative Rivers in Japan

Riparian vegetation plays a critical role in maintaining ecosystem function, ensuring drainage capacity, and enhancing disaster prevention and mitigation. However, existing ground-based survey methods are limited in both spatial coverage and temporal resolution, which increases the difficulty of meeting the growing demand for rapid, dynamic, and fine-scale monitoring of riverine vegetation. To address this challenge, this study proposes a remote sensing approach that integrates Sentinel-1 synthetic aperture radar imagery with Sentinel-2 optical data. A composite vegetation index was developed by combining the normalized difference vegetation index and synthetic aperture radar backscatter coefficients, thereby enabling the joint characterization of horizontal and vertical vegetation activity. The method was first tested in the Kuji River Basin in Japan and subsequently validated across eight representative river systems nationwide using 16 sets of satellite images acquired between 2016 and 2023. The results demonstrate that the proposed method achieves an average geometric correction error of less than three pixels and yields a spatial distribution of the composite index that closely aligns with the actual vegetation conditions. Moreover, the difference rate between sparse and dense vegetation exceeded 90% across all rivers, indicating a strong discriminative capability and temporal sensitivity. Overall, this method is well-suited for the multiregional and multitemporal monitoring of riparian vegetation and offers a reliable quantitative tool for water environment management and ecological assessment.