Spectral and determining size class distributions (4,5 and

Spectrallight absorption and backscattering are the two inherent optical propertiesdirectly controlling the light field in water and further influencing watercolor. Optical properties of phytoplankton, specifically the absorptioncoefficients of the pigments inside them, play a key role in determining boththe penetration of radiant energy in water and the use of this radiant energyfor photosynthesis. These pigment absorption coefficients and their concentrationsare important for understanding photosynthetic rate 1,2, identifying andquantifying phytoplankton functional groups 3 and determining size classdistributions (4,5 and references therein). These properties of phytoplanktonand their associated backscattering, along with colored dissolved organicmatter absorption and non-algal particle absorption and scattering directly control the light field of water.With the objective of expanding the ability todetect more pigments than just chlorophyll a,various methods have been proposed 6–8.

Most of these methods could obtainone or more pigments in addition to chlorophyll a from Rrs(?), but the accuracy was influenced bythe presence of non-algal particles and dissolved organic matters in the watercolumn. To reduce the influence from components other than phytoplankton, Wanget al. 9 developed a multi-pigment inversion model (MuPI) to obtaininformation of multiple pigments from hyperspectral Rrs(?). Thismodel incorporated a Gaussian decomposition scheme into a semi-analyticalinversion model and demonstrated that 13 Gaussian curves that contain importantphytoplankton pigment information can be retrieved from hyperspectral remotesensing reflectance. The Gaussian scheme was first described by Hoepffner and Sathyendranath 10,11, and was one of themethods proposed to obtain multiple pigments from phytoplankton absorptioncoefficients 12–17.

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Hoepffner and Sathyendranath 10used these Gaussian curves to represent light absorption of different pigmentsand demonstrated that some of the Gaussian peak heights showed goodrelationships with phytoplankton pigments, such as peaks at 435 and 675 nm forchlorophyll a, peaks at 643 nm forchlorophyll c, peaks at 460 and 655nm for chlorophyll b, and peaks at489 and 582 nm for carotenoids. This Gaussian decomposition scheme sheds lighton the potential of obtaining information for multiple phytoplankton pigmentsbeyond chlorophyll asemi-analytically using bio-optical techniques. Most of the past and current operational ocean colorsatellite missions are multispectral. It is thus necessary to evaluate theviability and associated uncertainties of obtaining these Gaussian curves frommulti-spectral remote sensing data. Using measurements from cyanobacteria bloomwaters in different regions, we validated the MuPI performance in obtainingmultiple independent Gaussian curves, and the sensitivity of MuPI to thespecific 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 Aquasatellite (MODIS-Aqua), and MEdium Resolution Imaging Spectrometer (MERIS)imagery over Lake Erie to obtain the spatial distributions of pigmentabsorption coefficients, chlorophyll a (Chl-a)and phycocyanin (PC) for a cyanobacteria bloom event in the western basin ofLake Erie.



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