Zoeken
Zoeken kan via de modus 'eenvoudig zoeken' (één veld) of uitgebreid via 'geavanceerd zoeken' (meerdere velden). Zo kan je bv. zoeken op een combinatie van een auteursnaam (auteur), een jaartal (jaar) en een documenttype.
Boekenmand
Nuttige resultaten kan je aanvinken en toevoegen aan een mandje. De inhoud hiervan kan je exporteren of afdrukken (naar bv. PDF).
RSS
Op de hoogte blijven van nieuw toegevoegde publicaties binnen uw interessegebied? Dit kan door een RSS-feed (?) te maken van jouw zoekopdracht.
nieuwe zoekopdracht
Finding plastic patches in coastal waters using optical satellite data
Biermann, L.; Clewley, D.; Martinez-Vicente, V.; Topouzelis, K. (2020). Finding plastic patches in coastal waters using optical satellite data. NPG Scientific Reports 10(1): 10 pp. https://dx.doi.org/10.1038/s41598-020-62298-z
In: Scientific Reports (Nature Publishing Group). Nature Publishing Group: London. ISSN 2045-2322; e-ISSN 2045-2322
|   |
| Auteurs | | Top |
- Biermann, L.
- Clewley, D.
- Martinez-Vicente, V.
- Topouzelis, K.
|
|
|
| Abstract |
Satellites collecting optical data offer a unique perspective from which to observe the problem of plastic litter in the marine environment, but few studies have successfully demonstrated their use for this purpose. For the first time, we show that patches of floating macroplastics are detectable in optical data acquired by the European Space Agency (ESA) Sentinel-2 satellites and, furthermore, are distinguishable from naturally occurring materials such as seaweed. We present case studies from four countries where suspected macroplastics were detected in Sentinel-2 Earth Observation data. Patches of materials on the ocean surface were highlighted using a novel Floating Debris Index (FDI) developed for the Sentinel-2 Multi-Spectral Instrument (MSI). In all cases, floating aggregations were detectable on sub-pixel scales, and appeared to be composed of a mix of seaweed, sea foam, and macroplastics. Building first steps toward a future monitoring system, we leveraged spectral shape to identify macroplastics, and a Naïve Bayes algorithm to classify mixed materials. Suspected plastics were successfully classified as plastics with an accuracy of 86%. |
IMIS is ontwikkeld en wordt gehost door het VLIZ.
