Technical Abstract: In this research, we present a novel technique to monitor cyanobacterial algal bloom using remote sensing measurements. We have used a multi-band quasi analytical algorithm that determines phytoplankton absorption coefficients, aF('), from above-surface remote sensing reflectance, Rrs('). In situ data including remote sensing reflectance, phytoplankton pigment concentration, and absorption coefficients of optically active constituents in the water were collected from highly turbid and productive aquaculture ponds These shallow (<1.5 m) ponds in northwestern Mississippi, USA, were used for channel catfish Ictalurus punctatus aquaculture and had high nitrogen and phosphorus loading rates from manufactured feeds added to ponds to promote rapid fish growth. These practices resulted in high phytoplankton biomass (Chlorophyll-a concentrations = 59.4-1376.6 mg m-3) with communities dominated by filamentous, gas vacuolate cyanobacteria. A novel technique was developed to further decompose the aF to obtain phycocyanin absorption coefficient, apC, at 620 nm, a primary peak of phycocyanin absorption spectrum. Validation of the model produced a mean and median absolute relative error of 36.2% and 22.0%. Overall, the model performance was higher in the higher range of PC concentration (>150 µg l-1). Results demonstrate that the new approach will be suitable for quantifying phycocyanin concentration in cyanobacteria dominated turbid productive waters.