Effect of bio-optical parameter variability and uncertainties in reflectance measurements on the remote estimation of chlorophyll-a concentration in turbid productive waters: modeling results.
Most algorithms for retrieving chlorophyll-a concentration (Chla) from reflectance spectra assume that bio-optical parameters such as the phytoplankton specific absorption coefficient (aPhi*) or the chlorophyll-a fluorescence quantum yield (eta) are constant. Yet there exist experimental data showing large ranges of variability for these quantities. The main objective of this study was to analyze the sensitivity of two Chla algorithms to variations in bio-optical parameters and to uncertainties in reflectance measurements. These algorithms are specifically designed for turbid productive waters and are based on red and near-infrared reflectances. By means of simulated data, it is shown that the spectral regions where the algorithms are maximally sensitive to Chla overlap those of maximal sensitivity to variations in the above bio-optical parameters. Thus, to increase the accuracy of Chla retrieval, we suggest using spectral regions where the algorithms are less sensitive to Chla, but also less sensitive to these interferences. aPhi* appeared to be one of the most important sources of error for retrieving Chla. However, when the phytoplankton backscattering coefficient (bb,Phi) dominates the total backscattering, as is likely during algal blooms, variations in the specific bb,Phi may introduce large systematic uncertainties in Chla estimation. Also, uncertainties in reflectance measurements, which are due to incomplete atmospheric correction or reflected skylight removal, seem to affect considerably the accuracy of Chla estimation. Instead, variations in other bio-optical parameters, such as eta or the specific backscattering coefficient of total suspended particles, appear to have minor importance. Suggestions regarding the optimal band locations to be used in the above algorithms are finally provided.
Dall'Olmo
Giorgio
G
Center for Advanced Land Management Information Technologies, School of Natural Resources, University of Nebraska-Lincoln 68588-0517, USA.
Gitelson
Anatoly A
AA
D000465:Algorithms; D002734:Chlorophyll / Q000032:analysis*; D000077194:Chlorophyll A; D003198:Computer Simulation; D004784:Environmental Monitoring / Q000379:methods*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008027:Light; D008954:Models, Biological; D008956:Models, Chemical; D009391:Nephelometry and Turbidimetry / Q000379:methods*; D010839:Phytoplankton / Q000302:isolation & purification / Q000378:metabolism; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014867:Water / Q000032:analysis*; D014871:Water Microbiology
D014867:Water; D002734:Chlorophyll; D000077194:Chlorophyll A