Characterization of Radiance from the Ocean Surface by Hyperspectral Imaging

Abstract

A novel snapshot hyperspectral imager is introduced for ocean color (OC) applications and its capabilities are demonstrated. The instrument provides hyperspectral radiance images with a wide field-of-view (FOV) and short exposure time. which is valuable for the direct characterization of the wind-roughened surface in various illumination conditions and wind speeds. Uncertainties in the total (L-t), sky (L-s) and derived water- leaving (L-w) radiances at viewing angles of 20-60 degrees are determined as a function of wind speed together with associated correlation coefficients and variances of the sea surface reflectance coefficient p. Estimated L-w uncertainties can partially explain the inaccuracy of satellite retrievals in the blue bands in the coastal waters. It is shown that in above-water measurements in no-glint conditions with viewing and azimuth angles of 40 degrees and 90 degrees, respectively, for both L-t(lambda) and L-s(lambda) the impact of FOV is minimal at least up to measured W = 5.7 m/s for full-angle FOV of 4 degrees and larger. Implications of uncertainties for the derivation of water leaving radiance in above-water ship-borne and AERONET-OC measurements are discussed.

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Document Details

Document Type
Technical Report
Publication Date
Jan 18, 2019
Accession Number
AD1096849

Entities

People

  • Ahmed El-habashi
  • Alexander Gilerson
  • Andrii Golovin
  • Carlos Carrizo
  • Robert E. Foster

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Satellites
  • Covariance
  • Data Acquisition
  • Data Analysis
  • Detectors
  • Hyperspectral Imagery
  • Information Science
  • Measurement
  • Observation
  • Optical Properties
  • Optics
  • Reflectance
  • Remote Sensing
  • Research Facilities
  • Scattering
  • Spectra

Fields of Study

  • Physics

Readers

  • Acoustical Oceanography.
  • Coastal Oceanography
  • Image Processing and Computer Vision.

Technology Areas

  • Space