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The recurring occurrence of green tides as an ecological disaster has been reported annually in the Yellow Sea. While remote sensing technology effectively tracks the scale, extent, and duration of green tide outbreaks, there is limited research on the underlying driving mechanisms of green tide drift transport and the determination of the leeway coefficient. This study investigates the green tide transport mechanism and evaluates the feasibility of estimating the leeway coefficient by analyzing green tide drift velocities obtained from Geostationary Ocean Color Imager-II (GOCI-II) images using the maximum cross-correlation (MCC) technique and leeway method across various time intervals alongside ocean current and wind speed data. The results reveal the following: (1) Significant spatial variations in green tide movement, with a distinct boundary at 34°40′N. (2) Short-term green tide transport is primarily influenced by tidal forces, while wind and ocean currents, especially the combined Ekman and geostrophic current component, predominantly govern net transport. (3) Compared to 1, 3, and 7 h intervals, estimating the leeway coefficient with a 25 h interval is feasible for moderate-resolution geostationary images, yielding values consistent with previous studies. This study offers new insights into exploring the transport mechanisms of green tides through remote sensing-driven velocity. [ABSTRACT FROM AUTHOR]

The green tides outbreak events seriously threaten the ecological balance of the coastal areas. Quickly and accurately obtaining the spatial distribution and drift state of green tides is key to early warning. Based on Landsat 8 (L8) and Sentinel-2 (S2) image pair, the green tides drift velocity was extracted using the maximum cross-correlation (MCC) method, and windage was calculated by combining ocean current and wind data. The results of the MCC method were validated. Ulva's drift in the Yellow Sea is shaped by both ocean currents and wind, closely aligning with the direction of the currents. Notably, the northward drift velocity of Ulva exhibits a clear boundary around 34°40′N. Windage shows similar characteristics with the Ulva drift velocity, as its values vary with time and space. This study will enhance our comprehension of the dynamic mechanism of green tides drift. • Automated extraction of Ulva drift velocity from medium-resolution imagery pair • The northward drift velocity of Ulva exhibits a distinct boundary around 34°40′N. • Ulva's drift in the Yellow Sea is shaped by both ocean currents and wind. [ABSTRACT FROM AUTHOR]