Review of Methods for Automatic Plastic Detection in Water Areas Using Satellite Images and Machine Learning
Problem
Ocean plastic pollution forms growing 'rubbish islands' that damage marine ecosystems; sources, accumulation sites and movement need to be identified and tracked.
Why it matters
Plastic pollution is described as one of the global environmental problems of our time.
What the AI did
The review catalogs projects using machine learning, especially deep learning, to automate detection of floating plastics from satellite imagery and UAV photographs, and analyzes limitations.
Results
not stated in source
Impact
Authors indicate modern machine learning makes automated detection of floating plastics possible, while noting various limitations of space imagery.
Record
| Venue | Sensors |
|---|---|
| Published | 2024 |
| Work type | article |
| Authors | Aleksandr Danilov, Elizaveta Serdiukova |
| Citations | 27 (OpenAlex, at import time) |
| References | 54 |
| Model or method | not stated in source |
| Organization | not stated in source |
| Primary source | https://doi.org/10.3390/s24165089 |
| Open access | gold |
| Keywords | marine plastic pollution, satellite remote sensing, deep learning, UAV imagery, environmental monitoring |
Importance rating
significant — thousands to millions affected
Abstract calls ocean plastic pollution one of the global environmental problems of our time, with growing rubbish islands damaging marine ecosystems; tracking sources and accumulation is needed. No quantified scale given.
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