Super-resolution total suspended matter and chlorophyll concentration using Sentinel-2 and Sentinel-3 data.

<p>Coastal ocean areas are very dynamic regions subject to strong anthropogenic pressure (e.g. industry, tourism, renewable energies, population). Satellite data constitute a unique tool that allows one to study and monitor these areas at a unique spatial and temporal resolution. The spatial and temporal scales needed to assess changes at coastal regions are higher than what can be rendered by individual missions: for example, <span>s</span>atellites like Sentinel-3 provide daily temporal resolution, but the sensors onboard these satellites do not measure at the necessary high spatial resolution to resolve complex coastal dynamics; on the other hand, high spatial resolution sensors, like MSI onboard Sentinel-2 (10 m resolution), are able to resolve these small scales, but with a low temporal revisit time (about 5 days). Both high spatial resolution datasets and traditional ones are hindered by the presence of clouds, resulting in a large amount of missing data. The complementarity of Sentinel-2 and Sentinel-3 datasets <span>can</span> be exploited to derive <span>a</span> super-resolution dataset of total suspended matter and chlorophyll concentration in the Belgian coast (North Sea), with the spatial resolution of Sentinel-2 and the temporal resolution of Sentinel-3. Moreover, as the approach used is based in DINEOF (Data Interpolating Empirical Orthogonal Functions), missing data can be interpolated as well, to provide a gap-free super-resolution dataset retaining the spatial scales of the highest resolution dataset (Sentinel-2 in this case). <span>T</span>he influence of ocean dynamics <span>in the region will be assess using these ocean colour variables.</span></p><p> </p>