VISUALIZING AND MONITORING HARMFUL ALGAL BLOOMS IN UTAH LAKE USING REMOTE SENSING AND GOOGLE EARTH ENGINE

The integration of remote sensing and geospatial modeling through Google Earth Engine (GEE) into modern GIS is an innovative approach to visualizing scientific data, monitoring short- and long-term ecosystem changes, and providing solutions to environmental questions. In this study, GEE and remotely sensed data were used to create a toolset called Utah Lake Set (ULS), consisting of TimeSeriesVis, ImageExporter, ImageExporterComposite, and TimeSeriesAnim, to monitor harmful algal blooms (HABs) in Utah Lake.

Utah Lake is one of the largest freshwater lakes west of the Mississippi River and experiences frequent HABs due to excessive nutrient inflow. ULS was utilized to visualize Utah Lake from April to October of 2019 to 2021, process and export satellite imagery, and generate time lapses to capture temporospatial changes. TimeSeriesVis contained a user interface (UI) allowing the user to preview the area before exporting data. ImageExporter stored image sets from LANDSAT, MODIS, and Sentinel as objects in GEE and filtered them with the boundaries of Utah Lake and the desired time period. The image sets were sorted by bands and exported for analysis with GIS tools. Complementing this, ImageExporterComposite exported images from the satellites as composites when possible without losing resolution. Additionally, TimeSeriesAnim created an animated time series of Utah Lake that could be viewed externally.

For wider application, these tools were expanded into a general-purpose integrated toolset within GEE called GPX VisualExporter (GPX-VE). When run, GPX-VE would filter the data with temporospatial bounds set by the user and would allow for the selection of datasets and bands desired for export through a UI. Before the export process began, the user would be prompted to dynamically preview the area by loading in satellite images while a time lapse of the time period would be generated, allowing for the visualization of the data. Afterwards, GPX-VE would export the data.

The integration of GEE and remote sensing enables automation of data sourcing, time lapse creation, and visualization of HABs in Utah Lake. This approach produces valuable water quality management information for the state of Utah. The toolset created in this project will assist other scientists in carrying out similar research throughout the world.