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 continental scale. 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 across twelve countries 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.
@article{arxiv.2204.01485,
title = {Satellite Monitoring of Terrestrial Plastic Waste},
author = {Caleb Kruse and Edward Boyda and Sully Chen and Krishna Karra and Tristan Bou-Nahra and Dan Hammer and Jennifer Mathis and Taylor Maddalene and Jenna Jambeck and Fabien Laurier},
journal= {arXiv preprint arXiv:2204.01485},
year = {2023}
}