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A pioneering technique to detect plastics floating on the sea surface was released this week, led by scientists from the Plymouth Marine Laboratory. Scientific reports
Earth observation scientists analyzed data from the European Space Agency’s Sentinel-2 satellites to develop this new approach, which demonstrates for the first time that satellites can detect aggregate patches of plastics floating in coastal waters.
With this method, aggregations of plastic particles greater than 5 mm (macroplastics) were also distinguished from natural floating materials, such as algae, driftwood, and foam, with an average accuracy of 86% at 4 study sites of case.
This technical challenge, funded primarily by the ACCORD research program of the Natural Environment Research Council, It is the first step towards developing an operational method to detect floating plastic patches in waters around the world.
The team executed high-resolution multispectral optical satellite data of coastal waters through a tuned algorithm to highlight objects floating on the ocean surface, creating the Floating Debris Index (FDI) for the Sentinel-2 Multispectral Instrument.
The next stage was to identify floating plastics. Thanks to a collaboration with the University of the Aegean, which shared information on deployed plastic targets for their new study on plastic litter, the team was able to find out exactly what Sentinel-2 was “seeing” through FDI, and therefore He was able to build an optical signature for floating plastics. These known plastic detections were supplemented by validated data on plastics detected after severe floods in Durban, South Africa. Once the plastic signatures were established, the team began the same process for natural debris, such as driftwood, algae, and sea foam, which will likely mix with the plastic patches.
With algorithm development and full validation, the team began searching for plastics “in the wild.” Based on published studies and social media posts, they detected aggregations in two developed countries: Canada (Saint John Islands) and Scotland, and two developing countries: Ghana (Accra) and Vietnam (Da Nang).
They manually selected pixels that were suspected of being dominated by plastics using spectral signature and FDI, as well as a Normalized Difference Vegetation Index (NDVI). Then, using an automated approach, the floating materials were differentiated using a Naïve Bayes (Bayesian) classification model. This Naïve Bayes classifier is a probabilistic algorithm, which calculates the probability that a detected pixel belongs to the classes of material with which it has been trained; in this case, known plastics, sea water, floating wood, algae and sea foam.
At all four study sites, suspect plastics were successfully classified as plastics with an overall accuracy of 86% (Saint John Islands 100%, Accra 87%, Scotland 83%, and Da Nang 77%). A less accurate classification resulted from the pixels not being sufficiently filled with floating debris and a small proportion of suspect plastics identified as sea foam.
The team will continue to refine the technique to further increase its accuracy in detecting floating plastic patches in murky coastal waters and large river systems.
Dr. Lauren Biermann, Earth Observation Scientist at Plymouth Marine Laboratory and lead author commented: “Plastic pollution is a global problem. Hopefully this method will provide a springboard for satellites and drones to be used to tackle the problem of marine plastics at the end of the product life cycle. However, we will only make significant progress if we also address the source and reduce the amount of plastics produced. ”
