Europe’s seas are its lifeblood. They provide trade routes, regulate the climate and supply food and energy. But these seas face a series of threats: land-based pollution originated in urban areas, from industry and intensive agriculture, and the growing level of shipping and the risks it brings.
All these pressures harm the marine ecosystems, and the climate change will further aggravate their impact, with consequences for human activities that depend on sea.
The Black Sea is no exception. Its unique hydrological characteristics shape the condition of its biodiversity, and increase its vulnerability to pollution and decline of habitat, coastal and marine resources.
The water quality evolution is one of the monitoring indicators for this environment. Remotely-sensed water quality information of specific parameters (i.e. suspended particulate matters, chlorophyll concentration) provide the tools to understand the dynamics of coastal areas.
For understanding the dynamics of the sediments, chlorophyll concentration and yellow substances in the coastal areas, improved ocean colour datasets are required (with increased spatial resolution - tens of meters). Ocean colour applications require specific spectral bands with high temporal, spectral, and radiometric resolutions.
For identifying specific waters’ bio-physical properties a minimum number of well-chosen thin spectral band is needed. Since there is no current satellite sensor to satisfy all the above criteria, an improved and custom-tailored algorithm is used in order to provide data fusion products required for better understanding the coastal processes.