Detecting phytoplankton diatom fraction based on the spectral shape of satellite‐derived algal light absorption coefficient
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Detecting phytoplankton diatom fraction based on the spectral shape of satellite‐derived algal light absorption coefficient

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  • Journal Title:
    Limnology and Oceanography
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    Knowledge about phytoplankton composition is important for biological and biogeochemical research as well as for ecological applications (e.g., water quality) in coastal and inland waters. Satellite remote sensing can potentially map the baseline patterns, anomalies, and trends of phytoplankton composition on a synoptic basis. A prominent challenge is the attribution of the total optical signal to phytoplankton amid interference from minerals and humus. Here, we obtained the phytoplankton light absorption coefficient, aph(λ), in the Chesapeake Bay by partitioning satellite‐derived total light absorption coefficient of water using the generalized stacked‐constraints model (GSCM). We show that the red‐to‐blue band ratio of GSCM‐derived aph(670)/aph(440) can be associated with diatom fraction in Chesapeake Bay. Further, the spatial‐temporal patterns shown in the satellite‐derived diatom fraction data agree well with field studies conducted previously around this region, including low diatom dominance in summer, high diatom dominance in the lower bay in winter, diatom‐dominated spring blooms in coastal waters outside of the bay, and increasing seasonal variability of diatom fraction from the upper to the lower bay. We also found that in the middle bay the summer diatom fraction correlates strongly with spring streamflow on an annual basis, which can be explained because sediment deposited by spring freshets is the main source of silicate supply during summer. These results suggest that the satellite‐derived diatom fraction maps can serve as a baseline for detecting phytoplankton composition anomalies, and highlight the effectiveness of using absorption‐based approach to extract phytoplankton composition information for optically complex waters.
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  • Source:
    Limnology and Oceanography, 63(S1)
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  • ISSN:
    0024-3590;1939-5590;
  • Format:
    PDF
  • Publisher:
    Wiley
  • Document Type:
    Journal Article
  • License:
  • Rights Information:
    CC BY
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    Library
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