Light absorption by phytoplankton pigments plays an important role not only in photosynthesis but also in modulating the appearance of water color. Some pigments are markers of phytoplankton classes or species. To better characterize phytoplankton, an inversion model is developed to retrieve the absorption coefficients of multiple pigments from hyperspectral remote sensing reflectance. In the model, the Gaussian functions proposed by Hoepffner and Sathyendranath (1991) were refined and implemented for the estimation of the absorption coefficients of multiple pigments. Application of the inversion model to remote sensing measurements made in cyanobacteria bloom waters resulted in the absorption coefficients of chlorophylls a, b, and c, carotenoid, phycoerythrin, and phycocyanin with the mean absolute relative error under 32% for wavelengths between 400 nm and 700 nm. The results indicate that it is feasible to retrieve the absorption coefficients of multiple pigments from hyperspectral remote sensing reflectance as long as the pigments make adequate contributions to the total absorption coefficient.

A study was conducted to determine the potential suitability of Terra/MODIS imagery for monitoring short-term phenological changes in forage conditions in a semi-arid region. The study sites included four meadow steppes and six typical steppes in the Xilingol steppe in central Inner Mongolia, China. The live biomass, dead standing biomass, total biomass, crude protein (CP) concentration and standing CP were estimated from early April to late October using the Enhanced Vegetation Index (EVI) values from Terra imagery (500 m pixels). Applying regression models, the EVI accounted for 80% of the variation in live biomass, 42% of the dead biomass, 77% of the total biomass, 11% of the CP concentration and 74% of the standing CP. MODIS/EVI is superior to AVHRR/NDVI when estimating forage quantity. Applying these results, the seasonal changes in live biomass and the standing CP could be described in the selected four sites with different degrees of grazing intensity. Generally, the increase in grazing intensity tended to decrease live biomass and standing CP. It was suggested that the EVI obtained from Terra imagery was an available predictor of the forage condition as measured by live biomass and standing CP. The MODIS/EVI values could provide information on the suitable timing of cutting for hay-making and nutritive value to range managers.

The remote sensing of chlorophyll a concentration from ocean color satellites has been an essential variable quantifying phytoplankton in the past decades, yet estimation of accessory pigments from ocean color remote sensing data has remained largely elusive. In this study, we validated the concentrations of multiple pigments (Cpigs) retrieved from in situ and MEdium Resolution Imaging Spectrometer (MERIS) measured remote sensing reflectance (Rrs(λ)) in the global oceans. A multi-pigment inversion model (MuPI) was used to semi-analytically retrieve Cpigs from Rrs(λ). With a set of globally optimized parameters, the accuracy of the retrievals obtained with MuPI is quite promising. Compared with High-Performance Liquid Chromatography (HPLC) measurements near Bermuda, the concentrations of chlorophyll a, b, c ([Chl-a], [Chl-b], [Chl-c]), photoprotective carotenoids ([PPC]), and photosynthetic carotenoids ([PSC]) can be retrieved from MERIS data with a mean unbiased absolute percentage difference of 38%, 78%, 65%, 36%, and 47%, respectively. The advantage of the MuPI approach is the simultaneous retrievals of [Chl-a] and the accessory pigments [Chl-b], [Chl-c], [PPC], [PSC] from MERIS Rrs(λ) based on a closure between the input and output Rrs(λ) spectra. These results can greatly expand scientific studies of ocean biology and biogeochemistry of the global oceans that are not possible when the only available information is [Chl-a].

Phytoplankton pigments absorb sunlight for photosynthesis, protect the chloroplast from damage caused by excess light energy, and influence the color of the water. Some pigments act as bio-markers and are important for separation of phytoplankton functional types. Among many efforts that have been made to obtain information on phytoplankton pigments from bio-optical properties, Gaussian curves decomposed from phytoplankton absorption spectrum have been used to represent the light absorption of different pigments. We incorporated the Gaussian scheme into a semi-analytical model and obtained the Gaussian curves from remote sensing reflectance. In this study, a series of sensitivity tests were conducted to explore the potential of obtaining the Gaussian curves from multi-spectral satellite remote sensing. Results showed that the Gaussian curves can be retrieved with 35% or less mean unbiased absolute percentage differences from MEdium Resolution Imaging Spectrometer (MERIS) and Moderate Resolution Imaging Spectroradiometer (MODIS)-like sensors. Further, using Lake Erie as an example, the spatial distribution of chlorophyll a and phycocyanin concentrations were obtained from the Gaussian curves and used as metrics for the spatial extent of an intense cyanobacterial bloom occurred in Lake Erie in 2014. The seasonal variations of Gaussian absorption properties in 2011 were further obtained from MERIS imagery. This study shows that it is feasible to obtain Gaussian curves from multi-spectral satellite remote sensing data, and the obtained chlorophyll a and phycocyanin concentrations from these Gaussian peak heights demonstrated potential application to monitor harmful algal blooms (HABs) and identification of phytoplankton groups from satellite ocean color remote sensing semi-analytically.