Observation of sea surface roughness at a pixel scale using multi-angle sun glitter images acquired by the ASTER sensor

Sea surface roughness (SSR) is commonly used to describe the state of the sea surface. Sun glitter (SG), caused by direct specular reflection of sunlight from the sea surface, and its intensity are strongly affected by SSR. Here, we propose a new model for estimating SSR at a pixel scale using multi-angle SG images. To test our model, high-resolution multi-angle SG images acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor were used to estimate SSR. The modal value of SSR was more suitable for describing the background SSR induced by wind, and these data were then converted into wind speed for accuracy evaluation. The estimated wind matched reasonably well with corresponding reanalysis wind data from the European Centre for Medium-Range Weather Forecasting and buoy wind data from the National Data Buoy Center. The results showed that the proposed model has an inversion accuracy that is comparable to other remote sensing methods. Next, we presented three examples of high-resolution SSR images of an oil slick, submarine topography, and internal wave information to illustrate the applications of the model. These estimated SSR images showed detailed oceanographic features with low noise and quantitative changes in SSR at a pixel scale. The results of this study demonstrate that it is feasible to estimate SSR at a high resolution using multi-angle SG images, and high-resolution SSR observations have considerable applicability to oceanographic phenomena.