Abstract Machine learning covers a large set of algorithms that can be trained to identify
patterns in data. Thanks to the increase in the amount of data and computing power …

Plastic pollution in coastal and marine areas is an ongoing environmental concern in the
world. Despite its growing concern worldwide, there is a knowledge gap in terms of its …

A vital and rapidly growing application, remote sensing offers vast yet sparsely labeled,
spatially aligned multimodal data; this makes self-supervised learning algorithms invaluable …

Large-area, artificial floating marine litter (FML) targets were deployed during a controlled
field experiment and data acquisition campaign: the Plastic Litter Project 2021. A set of 22 …

Detecting and quantifying marine pollution and macroplastics is an increasingly pressing
ecological issue that directly impacts ecology and human health. Here, remote sensing can …

The last couple of years has been ground-breaking for marine pollution monitoring
purposes. It has been suggested that combining multi-spectral satellite information and …

Marine scientists use a variety of collection and monitoring methods to survey macrolitter in
aquatic environments, aiming to assess the level of pollution and design mitigation actions …

Marine environmental pollution is one of the growing concerns of humans all over the world.
Therefore, managing these marine pollutants has been a crucial matter for scientists in …

Marine plastic pollution poses significant ecological, economic, and social challenges,
necessitating innovative detection, management, and mitigation solutions. Spectral imaging …

Remote detection of marine debris (also called marine litter) has received increased
attention in the past decade, with the Multispectral Instruments (MSI) onboard the Sentinel …