Spectral reflectance of marine macroplastics in the VNIR and SWIR measured in a controlled environment

• Published in: Scientific reports Vol. 11; no. 1; p. 5436
• Main Authors: Moshtaghi, Mehrdad, Knaeps, Els, Sterckx, Sindy, Garaba, Shungudzemwoyo, Meire, Dieter
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 08.03.2021; Nature Publishing Group; Nature Portfolio
• Subjects: 639/624; 704/172; 704/829; Aquatic environment; Humanities and Social Sciences; Litter; Marine debris; Marine environment; multidisciplinary; Natural environment; Oceans; Plastic debris; Plastics; Polyethylene; Polyethylene terephthalate; Polymers; Polypropylene; R&D; Reflectance; Remote sensing; Research & development; Science; Science (multidisciplinary); Suspended sediments; Water depth
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-021-84867-6

While at least 8 million tons of plastic litter are ending up in our oceans every year and research on marine litter detection is increasing, the spectral properties of wet as well as submerged plastics in natural marine environments are still largely unknown. Scientific evidence-based knowledge about these spectral characteristics has relevance especially to the research and development of future remote sensing technologies for plastic litter detection. In an effort to bridge this gap, we present one of the first studies about the hyperspectral reflectances of virgin and naturally weathered plastics submerged in water at varying suspended sediment concentrations and depth. We also conducted further analyses on the different polymer types such as Polyethylene terephthalate (PET), Polypropylene (PP), Polyester (PEST) and Low-density polyethylene (PE-LD) to better understand the effect of water absorption on their spectral reflectance. Results show the importance of using spectral wavebands in both the visible and shortwave infrared (SWIR) spectrum for litter detection, especially when plastics are wet or slightly submerged which is often the case in natural aquatic environments. Finally, we demonstrate in an example how to use the open access data set driven from this research as a reference for the development of marine litter detection algorithms.