Marine Litter (ML) comprises a wide range of undesired materials that enter the marine environment through various pathways, which include plastics and natural debris. As these ML persist and circulate on the ocean surface due to their resistance against natural decompositions, they generally form slicks or filaments-like structures called Litter Windrows (LWs). Among LWs, plastics compose a significant portion, along with an alarming growing rate of LWs in recent decades. This environmental threat has devasted the marine ecosystems and posed challenges in achieving global sustainability development goals. Despite governmental and industrial efforts to monitor and mitigate ML problems, more effective and scalable management actions are yet to be taken.

Hong Kong waters are considered one of the ML hotpots, with an annual collection of debris exceeding 4000 tons by relevant agency. An extensive in-situ data collection effort has been devoted to assessing the situation of ML in Hong Kong waters, with data sources from both Hong Kong and mainland governmental agencies, non-governmental organizations, and academia. Preliminary analysis shows that more than half of the ML collected is found on the water surface, with approximately 70% composed of plastic. However, due to the size of the Hong Kong water and the infrequent collection efforts, plenty of mysteries remain below the water.

This study then employs the established Earth Observation for Marine Litters (EO4ML) platform, which adopted the use of Copernicus Sentinel-2 MSI sensors to detect and monitor ML, especially LWs. Based on EO4ML's successful heritage in the Mediterranean Sea, where a tailored Windrows Spectral Indices (WSI) was developed, this study aims to deploy the EO4ML technology to Hong Kong waters, potentially the PRE. Coupling hydrodynamics data and visualizing results through the Geo-Information System (GIS), this study seeks to map ML hotspots and identify their spatial patterns, seasonal trends and many other critical drivers of ML distribution. The outcome of this study is expected to provide a unique “source-to-sink” perspective of ML on Hong Kong waters, providing a systematic and vital approach for decision-makers in management actions.