

Gitelson, AA, Dall'Olmo, G, Moses, W, Rundquist, DC, Barrow, T, Fisher, TR, Gurlin, D, Holz, J (2008). A simple semianalytical model for remote estimation of chlorophylla in turbid waters: Validation. REMOTE SENSING OF ENVIRONMENT, 112(9), 35823593. Abstract Accurate assessment of phytoplankton chlorophylla (chla) concentrations in turbid waters by means of remote sensing is challenging due to the optical complexity of case 2 waters. We have applied a recently developed model of the form [Rrs(1)(lambda(1))Rrs(1)(lambda(2))] x Rrs(lambda(3)) where Rrs(lambda(i)) is the remotesensing reflectance at the wavelength lambda(i), for the estimation of chla concentrations in turbid waters. The objectives of this paper are (a) to validate the threeband model as well as its special case, the twoband model Rrs(1)(lambda(1)) x Rrs(lambda(3)), using datasets collected over a considerable range of optical properties, trophic status, and geographical locations in turbid lakes, reservoirs, estuaries, and coastal waters, and (b) to evaluate the extent to which the threeband Model Could be applied to the Medium Resolution Imaging Spectrometer (MERIS) and twoband model Could be applied to the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate chla in turbid waters. The threeband model was calibrated and validated using three MERIS spectral bands (660670 nm, 703.75713.75 nm, and 750757.5 nm), and the 2band model was tested using two MODIS spectral hands (lambda(1) = 662672, lambda(3) = 743753 nm). We assessed the accuracy of chla prediction in four independent datasets without reparameterization (adjustment of the coefficients) after initial calibration elsewhere. Although the validation data set contained widely variable chla (1.2 to 236 mg m(3)), Secchi disk depth (0.18 to 4.1 m), and turbidity (1.3 to 78 NTU), chla predicted by the threeband algorithm was strongly correlated with observed chla (r(2) > 0.96), with a precision of 32% and average bias across data sets of 4.9% to 11%. Chla predicted by the twoband algorithm was also closely correlated with observed chin (r(2) > 0.92); however, the precision declined to 57%, and average bias across the data sets was 19% to 50.3%. These findings imply that, provided that an atmospheric correction scheme for the red and NIR bands is available, the extensive database of MERIS and MODIS imagery could be used for quantitative monitoring of chla turbid waters. (C) 2008 Elsevier Inc. All rights reserved. DOI: 10.1016/j.rse.2008.04.015 ISSN: 00344257 