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Sensing Ocean Plastics with an Airborne Hyperspectral Shortwave Infrared Imager

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dc.contributor University Of Connecticut
dc.contributor Inst Chem & Biol Marine Environm
dc.contributor Univ Connecticut
dc.contributor Marine Sensor Syst Grp
dc.contributor Dept Marine Sci
dc.contributor Ocean Cleanup Fdn
dc.contributor Australian Inst Marine Sci
dc.contributor King Abdullah Univ Sci & Technol
dc.contributor Carl Von Ossietzky Univ Oldenburg
dc.contributor Modelling House
dc.contributor Australian Institute Of Marine Science
dc.contributor King Abdullah University Of Science & Technology
dc.contributor Carl Von Ossietzky Universitat Oldenburg
dc.contributor Teledyne Optech Inc
dc.contributor Indian Ocean Marine Res Ctr
dc.contributor Red Sea Res Ctr
dc.contributor.author LEBRETON, LAURENT
dc.contributor.author GARABA, SHUNGUDZEMWOYO P.
dc.contributor.author AITKEN, JEN
dc.contributor.author DIERSSEN, HEIDI M.
dc.contributor.author ZIELINSKI, OLIVER
dc.contributor.author REISSER, JULIA
dc.contributor.author SLAT, BOYAN
dc.date.accessioned 2018-11-18T18:57:54Z
dc.date.accessioned 2018-11-18T18:57:54Z
dc.date.accessioned 2019-07-08T02:17:58Z
dc.date.available 2018-11-18T18:57:54Z
dc.date.available 2018-11-18T18:57:54Z
dc.date.available 2019-07-08T02:17:58Z
dc.date.issued 2018-10-16
dc.identifier.citation Garaba SP, Aitken J, Slat B, Dierssen HM, Lebreton L, Zielinski O, Reisser J (2018) Sensing ocean plastics with an airborne hyperspectral shortwave infrared imager. Environmental Science and Technology 52:11699-11707
dc.identifier.issn 0013-936X
dc.identifier.uri http://epubs.aims.gov.au/11068/14881
dc.description.abstract Here, we present a proof-of-concept on remote sensing of ocean plastics using airborne shortwave infrared (SWIR) imagery. We captured red, green, and blue (RGB) and hyperspectral SWIR imagery with equipment mounted on a C-130 aircraft surveying the "Great Pacific Garbage Patch" at a height of 400 m and a speed of 140 knots. We recorded the position, size, color, and type (container, float, ghost net, rope, and unknown) of every plastic piece identified in the RGB mosaics. We then selected the top 30 largest items within each of our plastic type categories (0.6-6.8 m in length) to investigate SWIR spectral information obtained with a SASI-600 imager (950-2450 nm). Our analyses revealed unique SWIR spectral features common to plastics. The SWIR spectra obtained (N = 118 items) were quite similar both in magnitude and shape. Nonetheless, some spectral variability was observed, likely influenced by differences in the object optical properties, the level of water submersion, and an intervening atmosphere. Our simulations confirmed that the similar to 1215 and similar to 1732 nm absorption features have potential applications in detecting ocean plastics from spectral information. We explored the potential of SWIR remote sensing technology for detecting and quantifying ocean plastics, thus provide relevant information to those developing better monitoring solutions for ocean plastic pollution.
dc.description.sponsorship We would like to thank donors of The Ocean Cleanup and partners of the "Aerial Expedition" project. Partners included International Air Response, ITRES, Teledyne Optech, Salesforce and Google for Moffett Airfield sponsorship. We also thank NOARC for the collaboration and support with acquiring the SWIR data over the North Pacific. We are grateful for assistance on the project by Robert Marthouse. We acknowledge Rick Martini and Anna Schwarz for support with logistics and survey planning; Chandra Salgado, Sue Gibbs, Kim Noble, Sara Niksic, Florent Beauverd, and Taylor Swift for assistance with the field work; and Sara Hajbane and Igor Carneiro for postprocessing of the RGB mosaics. We appreciate the fellowship funded by NASA Ocean Biology and Biogeochemistry Grant No. NNX15AC32G.
dc.language English
dc.subject Environmental Sciences & Ecology
dc.subject Sea
dc.subject Macro
dc.subject Environmental Sciences
dc.subject Marine Debris
dc.subject Water
dc.subject Rapid Identification
dc.subject Engineering, Environmental
dc.subject Engineering
dc.subject Surface
dc.subject Hydrocarbons
dc.subject Algorithm
dc.title Sensing Ocean Plastics with an Airborne Hyperspectral Shortwave Infrared Imager
dc.type journal article
dc.identifier.doi 10.1021/acs.est.8b02855
dc.identifier.wos WOS:000447816100027


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