Twin Cities WRS Seminar
Using Satellite-based Remote Sensing Methods for Automated Lake Water Quality and Ice Phenology Mapping
Recent advances in satellite technology along with cloud-based and supercomputing capabilities have enabled the use of satellite data for automated regional scale measurements of water resource characteristics beyond water clarity. The launch of NASA's Landsat-8 (L8) and the European Space Agency's Sentinel-2 (S2) have improved the capability of satellite optical data to measure chlorophyll, colored dissolved organic matter (CDOM) and suspended sediment; the main determinants of water clarity. On the other hand, Sentinel-1 is a satellite with a synthetic apertures radar (SAR) that can penetrate through clouds, which when coupled with optical data opens up new opportunities to measure lake ice phenology. To explore the capabilities of these systems, we conducted a number of field campaigns in the winter to measure snow depth and ice thickness and in the summer to measure optical water quality characteristics and in situ reflectance spectra nearly contemporaneously with satellite imagery at sites with wide ranges of optical complexity. We are using these measurements along with publically available data to validate our processing steps to develop field-validated methods that will be implemented in an automated water quality and ice phenology monitoring system. Water quality models developed for Landsat-8 and Sentinel-2 data are used to map chlorophyll, CDOM and water clarity for Minnesota's >10,000 lakes. The combination of optical and SAR data will be used to identify the onset of lake ice, snow and ice thickness to map ice phenology in all Minnesota lakes. This approach will enable near real-time monitoring of water quality variables and ice phenology at regional scales, which will enhance our understanding of spatial and temporal variability and responses of surface waters to environmental change.