Extending satellite ocean color remote sensing to the near-blue ultraviolet bands
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Extending satellite ocean color remote sensing to the near-blue ultraviolet bands

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  • Journal Title:
    Remote Sensing of Environment
  • Personal Author:
  • NOAA Program & Office:
    NOAA General Documents
  • Description:
    Ultraviolet (UV) radiation has a profound impact on marine life, but historically and even currently, most ocean color satellites cannot provide radiance measurements in the UV, and thus UV penetration, in the global ocean. We develop a system (termed as UVISRdl) in this study, based on deep learning, to estimate remote sensing reflectance (Rrs) at 360, 380, and 400 nm (collectively termed as near-blue UV bands, nbUV) from Rrs in the visible bands that are obtained by ocean color satellites. This system is tested using both synthetic and field-measured data that cover a wide range and large number of values, with the resulted coefficient of determination close to 1.0 and bias close to 0 between UVISRdl estimated and known Rrs(nbUV). These results indicate excellent predictability of Rrs(nbUV) from Rrs(visible) via UVISRdl. The system was further applied to VIIRS (the Visible Infrared Imaging Radiometer Suite) data with the estimated Rrs(nbUV) evaluated using matchup field measurements, and obtained a mean absolute relative difference (MARD) at 360 nm of ~14% for oceanic waters and ~ 50% for coastal waters. These results are equivalent to those reported in the literature for satellite Rrs(visible) in oceanic and coastal waters. Examples of the global distribution of Rrs(nbUV), and subsequently the diffuse attenuation coefficient at the nbUV bands (Kd(nbUV)), are generated after applying UVISRdl to Rrs(visible) from the VIIRS data. The system lays the groundwork to generate decade-long Rrs(nbUV) and Kd(nbUV) from satellite ocean color data, which will be useful and important for both ocean color remote sensing and biogeochemical studies.
  • Keywords:
  • Source:
    Remote Sensing of Environment, 253, 112228
  • DOI:
  • ISSN:
    0034-4257
  • Format:
    PDF
  • Publisher:
    Elsevier BV
  • Document Type:
    Journal Article
  • Rights Information:
    Accepted Manuscript
  • Compliance:
    Library
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