the analytical development and underlying hypothesis of a three-band algorithm for estimating chlorophyll-a concentration ([chla]) in turbid productive waters are presented. the sensitivity of the algorithm to the spectral location of the bands used is analyzed. a large set of experimental observations ([chla] varied between 4 and 217 mg m 3 and turbidity between 2 and 78 nephelometric turbidity units) was used to calibrate and validate the algorithm. it was found that the variability of the chlorophyll-a fluorescence quantum yield and of the chlorophyll-a specific absorption coefficient can reduce considerably the accuracy of remote predictions of [chla]. instead of parameterizing these interferences, their effects were minimized by tuning the spectral regions used in the algorithm. this allowed us to predict [chla] with a relative root-mean-square error of less than 30%.
satellite and airborne optical sensors can provide the high spatial and temporal resolution data that are needed for monitoring inland and coastal water ecosystems. the radiance signals recorded remotely in specific regions of the electromagnetic spectrum are usually transformed into reflectance and combined into models for the remote estimation of chlorophyll-a concentration, [chla], a parameter that is relatable to the biomass and productivity of phytoplankton.