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.

The challenge
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.






The solution
Data fusion algorithms for the Black Sea water quality analysis and monitoring (DaFSys) is subject to a project collaboration between TERRASIGNA (leader) and partners from France (Thales Alenia Space) and Romania (Faculty of Geography, University of Bucharest). The algorithm prototype is focused on the Black Sea water problematic and provides the most adapted data fusion products for monitoring this coastal area.
How DaFSys works?
The algorithm combines multispectral satellite data images in order to derive fusion products, that inherits the best characteristics of the input datasets. High spatial resolution satellite products (i.e. Landsat, Sentinel-2) and high spectral resolution data (i.e. MODIS, Sentinel-3) are the inputs for the data fusion system.

DaFSys implementation was based on ARSIS algorithm architecture and was highly improved for a versatile user experience. Its benefits:

  • interactive graphic interface with access to multiple functionalities;
  • opportunity to merge satellite datasets with different spectral, radiometric and spatial solution;
  • water quality products (chlorophyll concentration, suspended particulate matter) with better spatial resolution and improved accuracy;
  • small scale ocean colour events and phenomena easier to detect and analyse.





The users’ feed-back could be the basis for the further development of DaFSys, that could focus on issues such as:

  • extend the validation activities in other areas of interest with different optical properties of the sea water;
  • enhanced variants of products - remote sensing reflectance/water leaving reflectance, chlorophyll a, turbidity, suspended particulate matter, diffuse attenuation coefficient;
  • additional pre-processing algorithm development to enable consistently pre-process of all pixels in the original images to be fused;

DaFSys provides the medium for extended analysis of this marine environment, with one of the most severe degradation amongst the world’s basins.

The technology implemented proved to be robust and can be applied to any type of satellite imagery.
Its further development provides a reliable platform for future possible integration within the new ESA initiatives for the Black/Baltic Seas, such as The Pathfinder.

See related Black Sea topics:
River Ice Extent - Pathfinder Use Case
Danube Delta Wetlands
Exploitation Platforms