Flash-flood-driven litter accumulation on beaches studied with aerial imagery and machine learning on Sicily’s northeastern coast, southern Italy

This study examines the distributions and dynamics of litter accumulation in a part of the northeastern coast of Sicily, southern Italy, using a multidisciplinary approach with manned and unmanned aerial systems imagery, a machine-learning algorithm and analysis of meteorological data. Aerial imagery shows that litter accumulations are present on beaches near the river mouths and potentially after flash floods. At least five distinct flash flood events depositing litter have been inferred since March 2015 to January 2024 in the study area. Meteorological data show that high precipitation, resulting in flash floods, and prevailing wind direction from the sea are the primary contributors to litter accumulation in this area. The algorithm applied on drone imagery on one of the accumulations detected a composition of polystyrene (42.6%), wood (35.6%), polyurethane (6.1%) and polyethylene terephthalate (5.4%). The general composition of the litter accumulation and its distribution near river mouths suggests that its source is associated with the input from nearby towns through mismanagement on the riverbeds, followed by flash floods. This study highlights the importance of considering river floods when investigating litter dynamics in coastal environments, as well as the potential of using aerial imagery and machine learning to help assess this problem.This article is part of the Theo Murphy meeting issue 'Sedimentology of plastics: state of the art and future directions'.

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Publication Details

Journal
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
Published
2025-10-23
DOI
https://doi.org/10.1098/rsta.2024.0427
Primary Topic
Microplastics and Plastic Pollution
Type
article
Field-Weighted Citation Impact
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article

Flash-flood-driven litter accumulation on beaches studied with aerial imagery and machine learning on Sicily’s northeastern coast, southern Italy

Marcello Gugliotta, Christoph Tholen, J.S. Oh, Carolin Leluschko
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
Microplastics and Plastic Pollution
article

Flash-flood-driven litter accumulation on beaches studied with aerial imagery and machine learning on Sicily’s northeastern coast, southern Italy

Marcello Gugliotta, Christoph Tholen, J.S. Oh, Carolin Leluschko
article en

Abstract

This study examines the distributions and dynamics of litter accumulation in a part of the northeastern coast of Sicily, southern Italy, using a multidisciplinary approach with manned and unmanned aerial systems imagery, a machine-learning algorithm and analysis of meteorological data. Aerial imagery shows that litter accumulations are present on beaches near the river mouths and potentially after flash floods. At least five distinct flash flood events depositing litter have been inferred since March 2015 to January 2024 in the study area. Meteorological data show that high precipitation, resulting in flash floods, and prevailing wind direction from the sea are the primary contributors to litter accumulation in this area. The algorithm applied on drone imagery on one of the accumulations detected a composition of polystyrene (42.6%), wood (35.6%), polyurethane (6.1%) and polyethylene terephthalate (5.4%). The general composition of the litter accumulation and its distribution near river mouths suggests that its source is associated with the input from nearby towns through mismanagement on the riverbeds, followed by flash floods. This study highlights the importance of considering river floods when investigating litter dynamics in coastal environments, as well as the potential of using aerial imagery and machine learning to help assess this problem.This article is part of the Theo Murphy meeting issue 'Sedimentology of plastics: state of the art and future directions'.

Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering SciencesVol. 383(2307)
University of Bremen (DE), German Research Centre for Artificial Intelligence (DE), Hochschule für Technik und Wirtschaft des Saarlandes (DE), Martin Luther University Halle-Wittenberg (DE)
Openalex Percentile: Top 76%
Microplastics and Plastic Pollution
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