Sensing Ocean Plastics with an Airborne Hyperspectral Shortwave Infrared Imager

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.

Hyperspectral ultraviolet to shortwave infrared characteristics of marine-harvested, washed-ashore and virgin plastics

“…Of these eight wavebands, we concluded that ∼ 931, 1215, 1417 and 1732 nm were diagnostic absorption features after continuum removal and derivative analyses. Several studies have already shown prospective applications of the ∼ 1215 and ∼ 1732 nm wavebands in detection and quantification algorithms for floating and land-based plastic litter Goddijn-Murphy and Dufaur, 2018;Kühn et al, 2004). Unfortunately, the 931 nm and the 1417 nm absorption features fall outside the atmospheric window.…”

On Thermal Infrared Remote Sensing of Plastic Pollution in Natural Waters

“…Polished metals have a low emissivity at 8 to14 µm (0.02-0.2) while for wood, it is 0.87 [8]. It may be possible to separate the TIR signal of different materials, and even different kinds of polymers, by measuring their different spectral signatures, such as with a hyperspectral imager in the NIR-SWIR [4,6]. When applying this methodology, it is still important to aim for the strongest TIR signal as its spectral features weaken when overall levels drop.…”

“…Most progress has been made in the field of spectral remote sensing in visible (VIS), near-infrared (NIR) and short-wave infrared (SWIR) spectra where optical physics applies. Over these wavelengths, spectral light reflectance measurements of floating plastic litter have been made in situ [4], from unmanned aerial vehicles (UAV) [5], airplanes [6] and very recently, the Sentinel-2 satellite [5]. It has become clear that spectral remote sensing would be improved by using complementary measurements using different sensing technologies [7].…”

Cetacean sightings within the Great Pacific Garbage Patch

“…We also fitted three sensors to the aircraft: a short-wave infrared imager (Garaba et al 2018), a Lidar System (Feygels et al 2017) and RGB CS-4800i 16MP frame camera. While in survey mode, these sensors imaged the ocean at NADIR position from the open cargo door (rear of aircraft).…”

“…Some of the objects detected in the RGB mosaics were further explored using the simultaneously collected LIDAR and hyperspectral data. Hyperspectral imagery was captured using an ITRES SASI-600 push broom line scanning imager with 100 wavebands in the SWIR, ranging from 950 to 2450 nm, at 15 nm spectral resolution and 0.5 m across × 1.2 m along track spatial resolution (Garaba et al 2018). The CZMIL LIDAR used in this study is a hybrid scanned-flash system employing a 10-kHz laser and circular scanner, with a segmented detector enabling simultaneous recording of high-density data from a single laser (Feygels et al 2017).…”