MARIDA: A benchmark for Marine Debris detection from Sentinel-2 remote sensing data.

Katerina Kikaki,Konstantinos Karantzalos,Paraskevi Mikeli,Ioannis Kakogeorgiou,Dionysios E Raitsos,Bijeesh Kozhikkodan Veettil

doi:10.1371/journal.pone.0262247

Katerina Kikaki, Konstantinos Karantzalos + Show 4 more

Open Access

https://doi.org/10.1371/journal.pone.0262247

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Abstract

Currently, a significant amount of research is focused on detecting Marine Debris and assessing its spectral behaviour via remote sensing, ultimately aiming at new operational monitoring solutions. Here, we introduce a Marine Debris Archive (MARIDA), as a benchmark dataset for developing and evaluating Machine Learning (ML) algorithms capable of detecting Marine Debris. MARIDA is the first dataset based on the multispectral Sentinel-2 (S2) satellite data, which distinguishes Marine Debris from various marine features that co-exist, including Sargassum macroalgae, Ships, Natural Organic Material, Waves, Wakes, Foam, dissimilar water types (i.e., Clear, Turbid Water, Sediment-Laden Water, Shallow Water), and Clouds. We provide annotations (georeferenced polygons/ pixels) from verified plastic debris events in several geographical regions globally, during different seasons, years and sea state conditions. A detailed spectral and statistical analysis of the MARIDA dataset is presented along with well-established ML baselines for weakly supervised semantic segmentation and multi-label classification tasks. MARIDA is an open-access dataset which enables the research community to explore the spectral behaviour of certain floating materials, sea state features and water types, to develop and evaluate Marine Debris detection solutions based on artificial intelligence and deep learning architectures, as well as satellite pre-processing pipelines.

Highlights

Marine Debris, such as plastics, is a major global issue with important environmental, economic, human health and aesthetic aspects
This study aims to fill this gap with a new, open-access benchmark dataset, named Marine Debris Archive (MARIDA)—MARIne Debris Archive, based on S2 multispectral satellite data
After training four different models, the results showed that the developed RFSS+SI+GLCM achieved the highest scores for all metrics; yet it seems more prone to S2 noise and different bands resolutions than the deep U-Net architecture

Summary

Introduction

Marine Debris, such as plastics, is a major global issue with important environmental, economic, human health and aesthetic aspects. Plastics remain in the ocean for a long time, and have been found in various areas worldwide [1,2,3], affecting marine life at different trophic levels [4]. To tackle the Marine Debris issue, several solutions for detecting [5, 6], cleaning [7] and preventing [8] have been developed and validated. Among those, detecting and monitoring floating litter has recently gained the attention of most research and development efforts [9].

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