The Potential of Different Reflectance-Based Algorithms to Retrieve Phycocyanin Concentration through Remote Sensing: Application in a Hypereutrophic Mediterranean Lake

Cyanobacterial blooms impact aquatic environments and human health. Cyanobacterial biomass is usually estimated using traditional time-consuming and costly field sampling techniques. A remote sensing approach is time and cost efficient and feasible for repetitive monitoring. In this work, we test the potential of various algorithms to retrieve phycocyanin concentration in a Mediterranean lake. Field Spectro radiometric measurements and sampling were performed during 2016 and 2017. The results obtained prove that various ratio models can be used for the estimation of phycocyanin, with the model “R(700)/R(600)” being the best (R2 = 0.716). This research highlights the potential of cyanobacteria mapping using various available satellites.