Remote Sensing Laboratory, National Technical University of Athens, Athens, Zografou, Greece.
Institute of Oceanography, Hellenic Centre for Marine Research, Athens, Anavyssos, Greece.
PLoS One. 2022 Jan 7;17(1):e0262247. doi: 10.1371/journal.pone.0262247. eCollection 2022.
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.
目前，大量的研究都集中在通过遥感来探测海洋垃圾并评估其光谱特性，最终旨在提出新的运行监测解决方案。在这里，我们引入了一个海洋垃圾档案库（MARIDA），作为开发和评估能够探测海洋垃圾的机器学习（ML）算法的基准数据集。MARIDA 是第一个基于多光谱哨兵-2（S2）卫星数据的数据集，它能够将海洋垃圾与其他共存的海洋特征区分开来，包括马尾藻、船只、天然有机物质、波浪、尾流、泡沫、不同的水体类型（即清澈、浑浊水、含沙水、浅水）和云。我们提供了来自全球多个地理区域、不同季节、年份和海况条件下已验证的塑料碎片事件的注释（地理参考多边形/像素）。我们对 MARIDA 数据集进行了详细的光谱和统计分析，并为弱监督语义分割和多标签分类任务提供了成熟的 ML 基线。MARIDA 是一个开放获取的数据集，使研究界能够探索某些漂浮材料、海况特征和水体类型的光谱特性，开发和评估基于人工智能和深度学习架构的海洋垃圾探测解决方案，以及卫星预处理管道。
