Big Plastic Masses Detection using Sentinel 2 Images
Fernando Martin-Rodriguez

TL;DR
This paper explores detecting large plastic accumulations in oceans using Sentinel 2 satellite imagery and neural networks, focusing on nonfloating plastic in Almeria greenhouses.
Contribution
It introduces a novel method combining all Sentinel 2 spectral bands with neural networks for plastic detection in satellite images.
Findings
Neural networks outperform differential indexes in plastic detection
All 13 spectral bands improve recognition accuracy
Preliminary results show potential for large-scale marine litter monitoring
Abstract
This communication describes a preliminary research on detection of big masses of plastic (marine litter) on the oceans and seas using EO (Earth Observation) satellite systems. Free images from the Sentinel 2 (Copernicus Project) platform are used. To develop a plastic recognizer, we start with an image where we can find a big accumulation of "nonfloating" plastic: Almer\'ia greenhouses. We made a test using remote sensing differential indexes, but we got much better results using all available wavelengths (thirteen frequency bands) and applying Neural Networks to that feature vector.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSpectroscopy and Chemometric Analyses
