We developed empirical remote sensing models to estimate chlorophyll a concentrations and cyanobacteria synoptically, over a large inland lake using available Landsat Enhanced Thematic Mapper Plus (ETM+) data. In contrast to previous studies which rely on the spectral characteristics of the cyanobacterial specific pigment, phycocyanin, we developed remote sensing models capable of directly detecting cyanobacterial biovolume. This distinction is important because Landsat ETM+ data lacks the spectral band information required for optimal phycocyanin detection. Each model was calibrated and cross-validated with existing in situ measurements from Lake Champlain’s Long-Term Water Quality and Biological Monitoring Program (LTMP). Lake station measurements taken between 2006 and 2009 were matched with radiometrically converted exoatmospheric reflectance data from seven spectral bands on the Landsat ETM+ sensor. Step-wise multi-linear regression indicated data from Landsat ETM+ bands 1, 2 and 3 were most significant for predicting chl-a and cyanobacteria biovolume. Based on statistical analysis, the linear models that included visible band ratios slightly outperformed single band models. The final models captured the extents of cyanobacterial blooms throughout the 2006-2009 study period. The results serve as an added monitoring tool for resource managers and present new insight into the initiation and propagation of cyanobacterial blooms in Lake Champlain.