Literature DB >> 30249095

Sensing Ocean Plastics with an Airborne Hyperspectral Shortwave Infrared Imager.

Shungudzemwoyo P Garaba1,2,3, Jen Aitken1,4, Boyan Slat1, Heidi M Dierssen2, Laurent Lebreton1,5, Oliver Zielinski3, Julia Reisser1,6,7.   

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 ∼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.

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Year:  2018        PMID: 30249095     DOI: 10.1021/acs.est.8b02855

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  2 in total

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

Authors:  Mehrdad Moshtaghi; Els Knaeps; Sindy Sterckx; Shungudzemwoyo Garaba; Dieter Meire
Journal:  Sci Rep       Date:  2021-03-08       Impact factor: 4.379

2.  Aerial and underwater drones for marine litter monitoring in shallow coastal waters: factors influencing item detection and cost-efficiency.

Authors:  Gabriela Escobar-Sánchez; Greta Markfort; Mareike Berghald; Lukas Ritzenhofen; Gerald Schernewski
Journal:  Environ Monit Assess       Date:  2022-10-11       Impact factor: 3.307

  2 in total

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