TY - JOUR T1 - Automating the characterisation of beach microplastics through the application of image analyses A1 - Gauci,Adam A1 - Deidun,Alan A1 - Montebello,John A1 - Abela,John A1 - Galgani,Francois AD - Department of Geosciences, Faculty of Science, University of Malta, Msida, Malta AD - Department of Computer Information Systems, Faculty of ICT, University of Malta, Msida, Malta AD - Station de Corse, IFREMER, Immeuble Agostini- Z.I, Furiani, 20600, Bastia, Corsica, France UR - https://doi.org/10.1016/j.ocecoaman.2019.104950 DO - 10.1016/j.ocecoaman.2019.104950 KW - Image processing KW - Microplastics KW - Parameterisation KW - Monitoring obligations KW - Marine litter N2 - Four sandy beaches on the island of Malta in the Central Mediterranean were regularly sampled for Large MicroPlastic (LMP) particles having a diameter between 1 mm and 5 mm, at stations located at the waterline and 10 m inshore. The 10975 extracted LMP particles were characterised (dimensions, surface roughness, colour) through unaided visual observation, microscopic analyses, and an algorithm developed within the current study. Two-thirds of the isolated particles were smooth and the majority of these belonged to the grey-white colour category, with a low degree of opaqueness and discolouration, and a high degree of transparency, suggesting that these were dominated by low-density polyethylene LMPs. Conflicting evidence concerning the relative residence time of the isolated LMPs within seawater emerged from the colour and contour roughness determination, although an abundance of primary LMPs (production pellets) within our sample might have been responsible for the low contour roughness results obtained. Roughly six times as many particles were recorded within the inshore sampling stations as the particles recorded at the waterline stations. The developed algorithm performed very well when the dimension and colour parameter values it delivered were compared with those obtained by microscopic analyses. Y1 - 2019/12 PB - Elsevier BV JF - Ocean & Coastal Management SN - 0964-5691 VL - 182 ID - 62471 ER -