Remote sensing models using Landsat satellite data to monitor algal blooms in Lake Champlain.

Lake Champlain is significantly impaired by excess phosphorus loading, requiring frequent lake-wide monitoring for eutrophic conditions and algal blooms. Satellite remote sensing provides regular, synoptic coverage of algal production over large areas with better spatial and temporal resolution compared with in situ monitoring. This study developed two algal production models using Landsat Enhanced Thematic Mapper Plus (ETM(+)) satellite imagery: a single band model and a band ratio model. The models predicted chlorophyll a concentrations to estimate algal cell densities throughout Lake Champlain. Each model was calibrated with in situ data compiled from summer 2006 (July 24 to September 10), and then validated with data for individual days in August 2007 and 2008. Validation results for the final single band and band ratio models produced Nash-Sutcliffe efficiency (NSE) coefficients of 0.65 and 0.66, respectively, confirming satisfactory model performance for both models. Because these models have been validated over multiple days and years, they can be applied for continuous monitoring of the lake.