The Marine Litter Aggregation Forecast project estimated long-term global distribution of marine litter proceeding from land-based and sea-based sources at a global scale, taking advantage of numerical reanalysis databases of historical met-ocean conditions. Different machine learning techniques were applied to generate long-term climate-based series of the environmental variables that may affect the drift of marine litter over the sea surface, for example currents, wind and wave-induced Stokes drift.

Find out more here.

The project was funded through the Discovery element of ESA’s Basic Activities. It was selected through an Open Space Innovation Platform (OSIP) call for ideas on remote sensing of plastic marine litter.

Access the other Final presentations of ESA Discovery element activities videos.