Above-water measurements of water-leaving radiance are widely used for water-quality monitoring and ocean-color satellite data validation. Reflected skylight in above-water radiometry needs to be accurately estimated prior to derivation of water-leaving radiance. Up-to-date methods to estimate reflection of diffuse skylight on rough sea surfaces are based on radiative transfer simulations and sky radiance measurements. But these methods neglect the polarization state of the incident skylight, which is generally highly polarized. In this paper, the effects of polarization on the sea surface reflectance and the subsequent water-leaving radiance estimation are investigated. We show that knowledge of the polarization field of the diffuse skylight significantly improves above-water radiometry estimates, in particular in the blue part of the spectrum where the reflected skylight is dominant. A newly developed algorithm based on radiative transfer simulations including polarization is described. Its application to the standard Aerosol Robotic Network-Ocean Color and hyperspectral radiometric measurements of the 1.5-year dataset acquired at the Long Island Sound site demonstrates the noticeable importance of considering polarization for water-leaving radiance estimation. In particular it is shown, based on time series of collocated data acquired in coastal waters, that the azimuth range of measurements leading to good-quality data is significantly increased, and that these estimates are improved by more than 12% at 413 nm. Full consideration of polarization effects is expected to significantly improve the quality of the field data utilized for satellite data validation or potential vicarious calibration purposes.
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http://dx.doi.org/10.1364/AO.51.008324 | DOI Listing |
Radiative transfer simulations of measurements performed with the Skylight-Blocked Approach (SBA) for water exhibiting diverse optical properties confirmed the non-negligible impact of the depth z of the radiometer shield in the determination of the water-leaving radiance L. In particular, results showed that the shield-shaded water volume lowers the measured L value by a few up to tens of percent as a function of the depth z, water attenuation, and wavelength. The study also confirmed the potential applicability of an analytical correction scheme based on the sole water absorption and backscattering coefficients to support operational SBA measurements, still at the expense of decreased accuracy with increasing depth z and water turbidity.
View Article and Find Full Text PDFSensors (Basel)
October 2024
Community and Ecosystem Ecology, Leibniz Institute of Freshwater Ecology and Inland Fisheries, 12587 Berlin, Germany.
In recent decades, inland water remote sensing has seen growing interest and very strong development. This includes improved spatial resolution, increased revisiting times, advanced multispectral sensors and recently even hyperspectral sensors. However, inland waters are more challenging than oceanic waters due to their higher complexity of optically active constituents and stronger adjacency effects due to their small size and nearby vegetation and built structures.
View Article and Find Full Text PDFMar Environ Res
July 2024
Department of Oceanography and Marine Research Institute, Pusan National University, Busan, 46241, South Korea. Electronic address:
Satellite-derived chlorophyll-a concentration (Chl-a) is essential for assessing environmental conditions, yet its application in the optically complex waters of the eastern Yellow Sea (EYS) is challenged. This study refines the Chl-a algorithm for the EYS employing a switching approach based on normalized water-leaving radiance at 555 nm wavelength according to turbidity conditions to investigate phytoplankton bloom patterns in the EYS. The refined Chl-a algorithm (EYS algorithm) outperforms prior algorithms, exhibiting a strong alignment with in situ Chl-a.
View Article and Find Full Text PDFAccurate retrieval of the water-leaving radiance from hyperspectral/multispectral remote sensing data in optically complex inland and coastal waters remains a challenge due to the excessive concentrations of phytoplankton and suspended sediments as well as the inaccurate estimation and extrapolation of aerosol radiance over the visible wavelengths. In recent years, reasonably accurate methods were established to estimate the enhanced contribution of suspended sediments in the near-infrared (NIR) and shortwave infrared (SWIR) bands to enable atmospheric correction in coastal waters, but solutions to derive the dominant phytoplankton contribution in the NIR and SWIR bands are less generalizable and subject to large uncertainties in the remotely-derived water color products. These issues are not only associated with the standard atmospheric correction algorithm in the SeaDAS processing system but with the non-traditional algorithms such as POLYMER (POLYnomial-based approach established for the atmospheric correction of MERIS data).
View Article and Find Full Text PDFRemote Sens (Basel)
September 2023
Department of Computer Science, Kennesaw State University, Marietta, GA 30060, USA.
Mapping the seagrass distribution and density in the underwater landscape can improve global Blue Carbon estimates. However, atmospheric absorption and scattering introduce errors in space-based sensors' retrieval of sea surface reflectance, affecting seagrass presence, density, and above-ground carbon () estimates. This study assessed atmospheric correction's impact on mapping seagrass using WorldView-2 satellite imagery from Saint Joseph Bay, Saint George Sound, and Keaton Beach in Florida, USA.
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