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Satellite monitoring of terrestrial plastic waste

Preprints.org 2023 29 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Caleb Kruse, Edward Boyda, Sully Chen, Krishna Karra, Tristan Bou-Nahra, Dan Hammer, Jennifer Mathis, Taylor Maddalene, Jenna Jambeck, Fabien Laurier

Summary

Researchers developed a neural network system analyzing Sentinel-2 satellite imagery to detect terrestrial plastic waste aggregations, identifying 996 confirmed waste sites across Southeast Asia — far more than existing public databases — and found that 19% of sites sit within 200 meters of waterways, posing high ocean leakage risk.

Body Systems
Study Type Environmental

Plastic waste is a significant environmental pollutant that is difficult to monitor. We created a system of neural networks to analyze spectral, spatial, and temporal components of Sentinel-2 satellite data to identify terrestrial aggregations of waste. The system works at wide geographic scale, finding waste sites in twelve countries across Southeast Asia. We evaluated performance in Indonesia and detected 374 waste aggregations, more than double the number of sites found in public databases. The same system deployed in Southeast Asia identifies 996 subsequently confirmed waste sites. For each detected site, we algorithmically monitor waste site footprints through time and cross-reference other datasets to generate physical and social metadata. 19% of detected waste sites are located within 200 m of a waterway. Numerous sites sit directly on riverbanks, with high risk of ocean leakage.

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