TY - JOUR
T1 - Sensing Ocean Plastics with an Airborne Hyperspectral Shortwave Infrared Imager
AU - Garaba, Shungudzemwoyo P.
AU - Aitken, Jen
AU - Slat, Boyan
AU - Dierssen, Heidi M.
AU - Lebreton, Laurent
AU - Zielinski, Oliver
AU - Reisser, Julia
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: 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.
PY - 2018/9/25
Y1 - 2018/9/25
N2 - 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 ∼1215 and ∼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.
AB - 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 ∼1215 and ∼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.
UR - http://hdl.handle.net/10754/628857
UR - https://pubs.acs.org/doi/10.1021/acs.est.8b02855
UR - http://www.scopus.com/inward/record.url?scp=85054089427&partnerID=8YFLogxK
U2 - 10.1021/acs.est.8b02855
DO - 10.1021/acs.est.8b02855
M3 - Article
SN - 0013-936X
VL - 52
SP - 11699
EP - 11707
JO - Environmental Science & Technology
JF - Environmental Science & Technology
IS - 20
ER -