Assessing CyAN Satellite Accuracy: A Closer Look at Kansas' Aquatic Boundaries

Abstract

Cyanobacteria, commonly known as blue-green algae, pose significant environmental and public health challenges, producing toxins that degrade water quality and affect human health, local economies, and ecosystems. In Kansas, bodies of water like Marion Reservoir, Milford Lake, and Webster Lake are notably affected. Traditional in-situ sampling methods by the Kansas Department of Health and Environment (KDHE) often rely on public reports, potentially missing broader occurrences of harmful algal blooms (HABs). This study evaluates the efficacy of the Cyanobacteria Assessment Network (CyAN) satellite remote sensing technology as a method of bolstering existing efforts, examining its accuracy against localized in-situ measurements at the three eutrophic Kansas reservoirs. Through comparative analyses, this research assesses CyAN’s performance in estimating cyanobacteria concentrations at the water’s edge as well as when classified these into KDHE’s HAB levels: Watch, Warning, and Hazard. Findings from the cell concentration analysis demonstrate that the satellite data's accuracy varies significantly with lake geometry and spatial processing techniques, such as grid cell aggregation and zonal statistic type. However, in the KDHE HAB level classification analysis accuracy improved across all waterbodies. This research supports the potential of integrating remote sensing into existing monitoring frameworks to enhance HAB surveillance and management, providing a more comprehensive understanding of public health and environmental threats along the water’s edge in Kansas's freshwater systems.