![]() ![]() In this study, we propose a two-step method for the detection of whitecaps under various illumination conditions. The poor performance caused by using images degraded with light pollution is not conducive to automated long-term whitecap measurement. Under various illumination conditions, significant light pollution may be introduced into images. However, traditional detection methods are highly sensitive to illumination. The long-term measurement of whitecaps is necessary to deepen our understanding of the mechanisms of ocean surface motion. Whitecap formation is an important factor in the exchange of momentum, heat, and gas on the ocean surface. These results indicated that the parameters of oceanic whitecaps derived from high‐spatial resolution optical images can be used to estimate wind speed and provide a new approach for monitoring marine dynamic environments in the future. The reflectance of whitecap‐affected pixels in MSI images increased obviously with wind speed compared with background seawater in weak sunglint reflection area. Moreover, the influence of sunglint on whitecap recognition and whitecap coverage was also analyzed. MSI images were used to estimate regional high‐spatial resolution (4 km) wind speeds, and the merged results (0.25°) were verified with the hourly wind products of the fifth generation European ECMWF (Centre for Medium‐Range Weather Forecasts) atmospheric reanalysis (ERA5). The whitecap‐wind model demonstrates that MSI images can improve the quantification of sea surface wind speed with high spatial resolution. In addition, the differences between the MSI‐derived model and in situ measurement‐derived models which are mainly caused by the scale effect of optical remote sensing, are discussed. We established a power‐law model of MSI‐estimated whitecap coverage (W) and whitecap number density with buoy‐measured wind speed at a height of 10 m above the sea surface (U10). A curvature image processing method was employed to successfully identify oceanic whitecaps in MSI images and the whitecap coverage was estimated based on the whitecap recognition results. In this study, more than 100 Sentinel‐2 Multi‐Spectral Instrument (MSI) images and corresponding synchronous buoy wind speed data were collected to investigate oceanic whitecaps. The use of spaceborne optical sensors to capture oceanic whitecaps could provide more spatial distribution and dynamic marine environment information. The observational data of oceanic whitecap coverage are generally in situ photographs or videos. Oceanic whitecaps, as a manifestation of the wind‐wave breaking process and the medium of air‐sea exchange, play an important role in sea surface research.
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