Satellite Monitoring of Terrestrial Plastic Waste

Autor:	Kruse, Caleb, Boyda, Edward, Chen, Sully, Karra, Krishna, Bou-Nahra, Tristan, Hammer, Dan, Mathis, Jennifer, Maddalene, Taylor, Jambeck, Jenna, Laurier, Fabien
Rok vydání:	2022
Předmět:	Computer Science - Computers and Society Computer Science - Computer Vision and Pattern Recognition Computer Science - Machine Learning Electrical Engineering and Systems Science - Image and Video Processing
Zdroj:	PLoS ONE 18(1): e0278997 (2023)
Druh dokumentu:	Working Paper
DOI:	10.1371/journal.pone.0278997
Popis:	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. Comment: 14 pages, 14 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2204.01485 Zobrazit plný text záznamu View this record from Arxiv