Spectral the objective of expanding the ability to

Spectral
light absorption and backscattering are the two inherent optical properties
directly controlling the light field in water and further influencing water
color. Optical properties of phytoplankton, specifically the absorption
coefficients of the pigments inside them, play a key role in determining both
the penetration of radiant energy in water and the use of this radiant energy
for photosynthesis. These pigment absorption coefficients and their concentrations
are important for understanding photosynthetic rate 1,2, identifying and
quantifying phytoplankton functional groups 3 and determining size class
distributions (4,5 and references therein). These properties of phytoplankton
and their associated backscattering, along with colored dissolved organic
matter absorption and non-algal particle absorption and scattering directly control the light field of water.

With the objective of expanding the ability to
detect more pigments than just chlorophyll a,
various methods have been proposed 6–8. Most of these methods could obtain
one or more pigments in addition to chlorophyll a from Rrs(?), but the accuracy was influenced by
the presence of non-algal particles and dissolved organic matters in the water
column. To reduce the influence from components other than phytoplankton, Wang
et al. 9 developed a multi-pigment inversion model (MuPI) to obtain
information of multiple pigments from hyperspectral Rrs(?). This
model incorporated a Gaussian decomposition scheme into a semi-analytical
inversion model and demonstrated that 13 Gaussian curves that contain important
phytoplankton pigment information can be retrieved from hyperspectral remote
sensing reflectance. The Gaussian scheme was first described by Hoepffner and Sathyendranath 10,11, and was one of the
methods proposed to obtain multiple pigments from phytoplankton absorption
coefficients 12–17. Hoepffner and Sathyendranath 10
used these Gaussian curves to represent light absorption of different pigments
and demonstrated that some of the Gaussian peak heights showed good
relationships with phytoplankton pigments, such as peaks at 435 and 675 nm for
chlorophyll a, peaks at 643 nm for
chlorophyll c, peaks at 460 and 655
nm for chlorophyll b, and peaks at
489 and 582 nm for carotenoids. This Gaussian decomposition scheme sheds light
on the potential of obtaining information for multiple phytoplankton pigments
beyond chlorophyll a
semi-analytically using bio-optical techniques.

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Most of the past and current operational ocean color
satellite missions are multispectral. It is thus necessary to evaluate the
viability and associated uncertainties of obtaining these Gaussian curves from
multi-spectral remote sensing data. Using measurements from cyanobacteria bloom
waters in different regions, we validated the MuPI performance in obtaining
multiple independent Gaussian curves, and the sensitivity of MuPI to the
specific spectral bands of existing ocean color satellite sensors. Further,
the inversion scheme was applied to Hyperspectral Imager for the Coastal Ocean
(HICO), and Moderate Resolution Imaging Spectroradiometer aboard the Aqua
satellite (MODIS-Aqua), and MEdium Resolution Imaging Spectrometer (MERIS)
imagery over Lake Erie to obtain the spatial distributions of pigment
absorption coefficients, chlorophyll a (Chl-a)
and phycocyanin (PC) for a cyanobacteria bloom event in the western basin of
Lake Erie. 

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