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An Estimation Method of Coastal Ocean Debris Using Aerial Drone
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This study developed a drone-based aerial estimation method for detecting and quantifying coastal ocean debris, including plastic litter. The approach used aerial imagery analysis to address limitations of traditional survey methods for large-scale marine litter assessment.
The actual situation of marine litter has not been measured accurately; however innumerable floating garbage are drifting in the ocean. Especially, non-perishable waste such as microplastics continues to grow and is damaging marine life, including endangered species, and some are washed ashore and causing pollution damage to coastal areas. Microplastics incorporated into marine organisms, Arctic Sea ice, and deep-sea seafloor sediments have also been detected. The Ellen MacArthur Foundation in the United Kingdom estimates that the total amount of marine debris exceeds 150 million tons, with more than 8 million tons of new inflow each year. We measured and compared the amount of ocean debris in coasts in Hirado and Matsuura cities, Nagasaki with manual count and an aerial drone observation.
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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.
A Proposed Technology Solution for Preventing Marine Littering Based on Uavs and Iot Cloud-based Data Analytics
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This paper proposes a technological solution using unmanned aerial vehicles and automated collection systems to prevent marine littering at coastal hotspots. The approach aims to intercept plastic waste before it enters the ocean and breaks down into microplastics.
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.
Quantifying Marine Macro Litter Abundance on a Sandy Beach Using Unmanned Aerial Systems and Object-Oriented Machine Learning Methods
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Researchers developed an object-oriented machine learning classification strategy using unmanned aerial system imagery to automatically identify and quantify marine macro litter on sandy beaches, comparing three automated methods against manual counts. The UAS-based approach demonstrated capacity for scalable, cost-effective beach litter monitoring to support coastal pollution surveillance programs.
Unmanned Aerial Vehicles for Debris Survey in Coastal Areas: Long-Term Monitoring Programme to Study Spatial and Temporal Accumulation of the Dynamics of Beached Marine Litter
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Researchers used UAVs to acquire georeferenced RGB images over a ten-month monitoring programme at a protected marine area near Pisa, Italy, to characterize the spatial and temporal distribution of beached marine debris. Post-processing via visual interpretation allowed localization and identification of anthropogenic debris accumulation patterns, demonstrating UAV-based surveying as an effective low-impact approach for long-term coastal litter monitoring.
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.