RGB sensor integrated into unmanned aerial vehicle for monitoring cyanobacterial density in reservoirs.

This article focuses on evaluating the use of unmanned aerial vehicles (UAVs) equipped with low-cost RGB sensors to monitor cyanobacterial blooms in two water supply reservoirs in northeastern Brazil. The study developed multiple linear regression models correlating UAV-derived spectral data with in situ measurements of chlorophyll-a concentration, total phytoplankton, and cyanobacterial densities and biovolumes, achieving high predictive accuracy (adjusted R² up to 0.95–0.96). The models enabled spatial mapping of cyanobacterial biomass, highlighting areas of higher risk within the reservoirs, which are dominated by toxin-producing cyanobacteria such as Raphidiopsis raciborskii and Microcystis viridis. This UAV-based remote sensing approach offers a rapid, effective complement to traditional water quality monitoring methods, with potential applications in managing eutrophic reservoirs critical for public water supply.