OPAT – Geomatys

Born of a desire by Geomatys staff to design a geospatial service useful in the fight against environmental pollution, The Ocean Plastic Alert and Tracking (OPAT) system is a service for locating plastic pollution at sea using satellite-derived earth observation data and anticipating their drift. This project, which leverages Geomatys’ EXAMIND Datacube technology to efficiently combine diverse geospatial datasets and run spatio-temporal analyses, enables users to know when plastic pollution enters their jurisdiction and precisely locate where they should focus their mitigation measures.

Plastic waste and coastlines: the issue

On a global scale, plastic waste is estimated to account for 85% of all marine litter, or between 75 and 199 million tonnes, a quantity that some studies see tripling by 2060.

In coastal areas, cities are spending up to several million euros a year on beach clean-ups. This problem also obviously affects the tourism sector, since the presence of garbage on the beaches of seaside resorts affects their reputation: studies estimate that the presence of garbage on the coasts can reduce the overall income of these tourist areas by 1 to 5%.

Acting upstream with OPAT

This is what OPAT is all about. By using geospatial images and then passing them through detection algorithms developed and integrated into EXAMIND Datacube, we are able, thanks to hyperspectral imagery, to accurately determine the position of plastic waste banks.

The idea is therefore to anticipate the arrival of plastics on the beach, providing a number of social and environmental advantages. For the local economy, this reduces clean-up costs while also enhancing the image of beaches for tourists. Plastic is also easier to recycle when it’s collected at sea than when it’s collected soiled by sand on the beach. Furthermore, the earlier we remove plastic from the environment, the less time it has to break down into microplastics which can enter into the food chain for decades, or even centuries, to come.

EXAMIND Datacube enables us to manage large volumes of geospatial data, and therefore to carry out spatio-temporal analyses. What’s more, the currentology experts mobilized through the project reinforce the quality and relevance of the drift predictions that Geomatys has already implemented through prior activity, notably through projects with the Japan Aerospace Exploration Agency, JAXA. Plastic pollution collection data history is then used to improve drift predictions by training and tuning Machine Learning algorithms. For instance, here, the boat has collected waste at a position (x,y) and a time T, which differed from the predictions made by the OPAT’s original algorithm.

Plastic waste and coastlines: the issue

Acting upstream with OPAT

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