Geospatial Assessment and Monitoring of Harmful Algal Blooms in Utah Lake Using Google Earth Engine and Remote Sensing Models

Abstract

Harmful algal blooms (HABs) in inland waters pose a significant ecological and public health concern. Excessive nutrient runoff fuels the growth of toxic algae, impacting water quality. Utah Lake, like many freshwater bodies, experiences eutrophication—a process characterized by excessive nutrient input. Utah Lake, with its susceptibility to nutrient runoff from agricultural and urban areas, faces challenges in maintaining optimal water quality. To assess and monitor HABs, Landsat 8/9 satellite data of Utah Lake between 2019 to 2023 are utilized in this study. As the studied ecosystem is aquatic, top-of-atmosphere corrected satellite imagery is primarily utilized, the correction being essential for discerning subtle variations in water properties. By mitigating atmospheric interference, these corrected images enhance the precision of water quality assessments, facilitating the comprehensive monitoring of aquatic ecosystems. Top-of-atmosphere corrected satellite imagery is crucial for accurate aquatic environmental research, mitigating atmospheric interference to enhance precision in water quality assessments and facilitate comprehensive monitoring of aquatic ecosystems by discerning subtle variations in water properties. In quantifying HABs and assisting in early detection, remote sensing models employing mathematical algorithms are important tools. To implement and utilize various models, a generalizable toolset called GPX VisualExporter was built inside Google Earth Engine (GEE). GPX VisualExporter leverages GEE cloud computing and data processing capabilities to flexibly select datasets, apply models, create preview and visualization aids, and export processed data. These data are then further analyzed using other geographic information systems. In this manner, the quantities of HABs are able to be extracted from Utah Lake.