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Plastic Litter Project 2018: a feasibility study on detecting plastics in the aquatic environment using drones and satellite images
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Researchers tested whether drone and satellite imagery could detect floating plastic litter in the ocean, using large artificial plastic targets made of PET bottles, plastic bags, and nylon fishing nets. While drones could detect the targets, satellite resolution was insufficient at the tested target size, highlighting current limitations of remote sensing for marine plastic litter monitoring.
Plastic litter has been shown to pose a significant problem in the marine environment and the food chain at all trophic levels. Within the scope of Plastic Project 2018, we investigated the prospective use of imaging technology on airborne and spaceborne platforms in detecting floating plastic litter. Three artificial targets of plastic litter were prepared using PET-1water bottles, LDPE plastic bags and nylon fishing ghost nets. Each target measured 10 m x 10 m fixed by a PVC frame to prevent spillage as well as to make an aggregated target. We evaluated the derived spectral reflectances of these plastic litter targets gathered from the airborne (drone) and spaceborne (Sentinel-2) images. Improved geo-referencing of the high geo-spatial resolution (resampled 10 m) Sentinel-2 images was achieved by utilizing excellent geospatial resolution (<0.03 m) drone images. Further analysis involved determining accurate pixel coverage of each target with future application in quantification efforts. Of the three plastic litter targets, it was noted that the plastic bottles had the highest spectral reflectances that were measured by the Sentinel-2 mission image. The experiment showed that Sentinel-2 satellites could be used to detect marine plastics when they cover a large area. The Sentinel-2 NIR band can significantly contribute to marine litter detection and the water content partly influence the behaviour of spectral values.
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Remote Sensing of Sea Surface Artificial Floating Plastic Targets with Sentinel-2 and Unmanned Aerial Systems (Plastic Litter Project 2019)
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Researchers tested remote sensing of floating plastic targets in a real marine environment using Sentinel-2 satellite imagery and unmanned aerial systems during the 2019 Plastic Litter Project, collecting reference spectral data to help calibrate detection algorithms. The study provided a validated dataset characterizing the spectral behavior of floating plastics to support future remote monitoring efforts.
Assessment of marine litter through remote sensing: recent approaches and future goals
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This review classified remote sensing approaches for detecting marine litter — including satellite, aircraft, and drone platforms with optical, infrared, and radar sensors — finding that few studies had reached operational status and that detecting small or submerged litter remains a major technical challenge.
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This review evaluates the current state of satellite and aerial remote sensing for detecting marine plastic debris, noting that while progress has been made using optical and hyperspectral imaging, significant challenges remain including low detection resolution for small particles, confusion with other floating materials, and the need for better machine learning algorithms. The paper is relevant to the microplastics field as large-scale monitoring tools are needed to track plastic pollution distribution and inform cleanup and policy efforts, though direct detection of microplastics (<5 mm) from orbit remains largely out of reach with current technology.
Detection of exogenous floating marine debris: an overview of techniques associated with remote sensing
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This review surveyed remote sensing techniques for detecting floating marine debris including plastic litter, identifying current capabilities, limitations, and research gaps. The paper calls for development of a spectral reference library for marine debris to improve detection accuracy from satellite and aerial platforms.
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Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.