Estimation of chlorophyll-a in urban lakes using drones

Abstract

Urban lakes provide significant ecological and societal benefits, but they are compromised by anthropogenic activities when there are insufficient protection and monitoring programs. Several problems affect these water bodies, and eutrophication is one of the more significant issues. One of the indicators to estimate eutrophication is the chlorophyll-a concentration in water (Chl-a), determined by analytical methods using fluorophotometry, spectrophotometry, and high-performance liquid chromatography (HPLC). In recent decades remote sensing of Chl-a in water bodies used satellite and airborne-based sensors. Still, those systems are inadequate for monitoring most urban lakes due to spatial and spectral resolution limitations, problems in modeling atmospheric corrections, and issues related to the removal of effects of other components in the water column. The methodology presented here estimated Chl-a content sensing sun-induced fluorescence (SIF) at the Fraunhofer line Hα (656.3 nm) and correlated the results to the concentrations reported by an external laboratory using fluorophotometry methods. The system used in this investigation has a georeferenced imaging system, an optical narrow-band filter (NBF), and a drone. The results of this investigation indicated that sensing at the Hα Fraunhofer line and a simple linear regression estimated better content of Chl-a in water compared to other studies measuring SIF at different Fraunhofer lines.