Near simultaneous collection of 34 surface water samples and airborne multispectral scanner data provided input for regression models developed to predict surface concentrations of estuarine chlorophyll a. Two wavelength ratios were employed in model development. The ratios werechosen to capitalize on the spectral characteristics of chlorophyll a, while minimizing atmospheric influences. Models were then applied to data previously acquired over the study area thre years earlier. Results are in the form of color-coded displays of predicted chlorophyll a concentrations and comparisons of the agreement among measured surface samples and predictions basedon coincident remotely sensed data. The influence of large variations in fresh-water inflow to the estuary are clearly apparent in the results. The synoptic view provided by remote sensing is another method of examining important estuarine dynamics difficult to observe from in situ sampling alone.