The World’s Plastic Waste You Can See From Space

10 May 2022 by Kitty Grubb
blog author

The masses of plastic pollution building up around the globe can now be seen and monitored from space via a ground-breaking platform that uses artificial intelligence (AI) to monitor and reduce ocean pollution.

In what is believed to be a world-first, Global Plastic Watch (GPW) is a digital platform that works in near real-time, utilising both AI and satellite data technology to map the plastic pollution and pinpoint the worst-affected areas which require urgent attention.

The European Space Agency makes data freely available which enables GPW to detect and monitor the problem areas on land; to flag up the waste sites which need a clean-up, and ensure laws against dumping are effectively enforced.

The pioneering platform will also provide risk indicators for existing plastic waste in terms of proximity to water or communities and will highlight priority areas for investment in waste and recycling infrastructure. Mapping waste which sits dangerously close to water will help stop the plastic usually destined for the sea or rivers reaching them, as action can be mobilised to focus on these problem areas.

Developed and funded by the Australian philanthropic Minderoo Foundation, the innovative platform has identified thousands of waste sites across 25 countries for the first time ever.

The data, which is updated monthly, shows there are currently four plastic waste sites in Singapore, compared to 415 sites in China and 690 in India. The country report goes as far as naming the leading plastic polymer producers as well as the amount they generate in mega tonnes.

Every year, 10 million tonnes of plastic is dumped in our oceans and the GPW system aims to use technology to help fight the plastic waste battle which is a major contributor to the climate crisis.

Every waste site detected by the GPW system is validated by a trained reviewer using high-resolution satellite imagery and on-the-ground imagery where possible.

The resolution of the data is too poor for the naked human eye to identify whether there is plastic waste in a certain area, so neural networks have been trained to analyse the spatial, spectral and temporal information in the data to classify whether a region contains said waste. From there it uses external sources to build extra information into the collected data about the number of habitants living near the waste and how far the site is from a waterway.

Minderoo Foundation’s No Plastic Waste initiative has joined forces with Earthrise Media to develop a tool that can help with evidenced-based decision-making on how to manage and mitigate the world’s plastic pollution crisis. The tool can be accessed by governments, funding agencies, intergovernmental organisations, NGOs, scientific researchers and the general public in a bid to work towards waste management goals.

Kakuko Nagatani-Yoshida from the United Nations Environment Programme told Sky News: “It is difficult to control what you cannot measure or even locate.”

Fabien Laurier, a key architect of GPW, said it was not about naming and shaming, but rather empowering governments with information to help tackle the problem.

Kitty Grubb, Senior Consultant – Sustainable Business at Acre, said: “This is a perfect example of the use of ‘tech for good’. To many, AI is a terrifying concept because of its seemingly infinite potential and because of the little we understand it. However, GPW and Earthrise Media have developed a tool that can be accessed by all and used by all in the global battle against extreme climate change.”

K​itty is a Senior Consultant in Acre’s Sustainable Business Team and has been appointed to a variety of international executives and boards since 2016. She began her career recruiting into wealth management and private banking for a boutique recruitment firm, before moving into global non-profits at a medium-sized, purpose-driven search firm. Since then, she has worked with ambitious, world-leading charities; membership bodies and commercial businesses to identify progressive and next-generation talent.

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