Chl-a ESTIMATION FROM RS TECHNIQUES: COMPARATIVE ANALYSIS OF DATA ACQUIRED BY SATELLITES AND RPA

The composition and concentration of algal biomass serve as key indicators of water quality and eutrophication levels in both lentic and lotic environments. Estimating algal concentrations has been a focal point of remote sensing research, with recent advancements in modeling and data acquisition techniques aimed at minimizing errors inherent to acquisition systems and environmental conditions. This study aimed to develop a strategy for monitoring chlorophyll-a using high-spatial-resolution multispectral imagery in a region impacted by both point and diffuse pollution sources, specifically at the mouth of Riacho Fundo in Paranoá Lake, Federal District, Brazil. Data were collected from PlanetScope satellite imagery and a Remotely Piloted Aircraft (RPA) system, alongside limnological, meteorological, and in situ Remote Sensing Reflectance (Rrs) measurements. The relationship between remote sensing data and chlorophyll-a concentrations was assessed using statistically validated linear regression models, revealing strong correlations: R² = 0.80 for RPA data using the red channel (640–680 nm) and R² values of 0.81 and 0.72 for PlanetScope data using the green (500–590 nm) and red (590–670 nm) channels, respectively. These findings demonstrate the potential of high-spatial- and temporal-resolution RPA and satellite-based remote sensing systems for estimating chlorophyll-a concentrations in continental waters, even under low-biomass conditions.