Using hyperspectral remote sensing to estimate chlorophyll-a and phycocyanin in a mesotrophic reservoir

This research estimates phytoplankton pigment concentrations (chlorophyll-a (chl-a) and phycocyanin (PC)) from hyperspectral Airborne Imaging Spectrometer for Applications (AISA) imagery. AISA images were acquired for a meso-eutrophic reservoir in Central Indiana, USA. Concurrent with the airborne image acquisition, in situ water samples and reflectances were collected. The water samples were subsequently analysed for pigment concentrations, and in situ measured reflectance spectra were used for calibrating the AISA images. Spectral indices, derived from the AISA reflectance spectra, were regressed against the measured pigment concentrations to derive algorithms for estimating chl-a and PC. The relationship between the pigment concentrations and the spectral indices were analysed and evaluated. The results indicate that the highest correlation occurred between chl-a and a near-infrared to red ratio (coefficient of determination R2 = 0.78) and between PC and the reflectance trough at 628 nm (R2 = 0.80). The relationship between PC and the reflectance at 628 nm provides an approach to the estimation of cyanobacteria concentration from hyperspectral imagery, which facilitates water-quality authorities or management agencies in making well-informed management decisions.