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


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
08 03 2021
Historique:
received: 01 10 2020
accepted: 12 02 2021
entrez: 9 3 2021
pubmed: 10 3 2021
medline: 10 3 2021
Statut: epublish

Résumé

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.

Identifiants

pubmed: 33686150
doi: 10.1038/s41598-021-84867-6
pii: 10.1038/s41598-021-84867-6
pmc: PMC7940656
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

5436

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Auteurs

Mehrdad Moshtaghi (M)

VITO Remote Sensing, Mol, 2400, Belgium. mehrdad.moshtaghi@vito.be.

Els Knaeps (E)

VITO Remote Sensing, Mol, 2400, Belgium.

Sindy Sterckx (S)

VITO Remote Sensing, Mol, 2400, Belgium.

Shungudzemwoyo Garaba (S)

Marine Sensor Systems Group, Institute for Chemistry and Biology of the Marine Environment, Carl von Ossietzky University of Oldenburg, Wilhelmshaven, 26382, Germany.

Dieter Meire (D)

Flanders Hydraulics, Antwerp, 2140, Belgium.

Classifications MeSH