Big Plastic Masses Detection using Sentinel 2 Images

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.