Simis, S.G.H. and Ruiz-Verdú, A. and Domínguez-Gómez, J.A. and Peña-Martinez, R. and Peterson, S.W. and Gons, H.J. (2007) Influence of phytoplankton pigment composition on remote sensing of cyanobacterial biomass. Remote Sensing of Environment, 106, 414-427. ISSN 0034-4257.
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Official URL: http://dx.doi.org/10.1016/j.rse.2006.09.008
An extensive field campaign was carried out for the validation of a previously published reflectance ratio-based algorithm for quantification of the cyanobacterial pigment phycocyanin (PC). The algorithm uses band settings of the Medium Resolution Imaging Spectrometer (MERIS) onboard ENVISAT, and should accurately retrieve the PC concentration in turbid, cyanobacteria-dominated waters. As algae and cyanobacteria often co-occur, the algorithm response to varying phytoplankton composition was explored. Remote sensing reflectance and reference pigment measurements were obtained in the period 2001–2005 in Spain and the Netherlands using field spectroradiometry and various pigment extraction methods. Additional field data was collected in Spain in May 2005 to allow intercalibration of spectroradiometry and pigment assessment methods. Two methods for extraction of PC from concentrated water samples, and in situ measured PC fluorescence, compared well. Reflectance measurements with different field spectroradiometers used in Spain and the Netherlands also gave similar results. Residual analysis of PC predicted by the algorithm showed that overestimation of PC mainly occurred in the presence of chlorophylls b and c, and phaeophytin. The errors were strongest at low PC relative to Chl a concentrations. A correction applied for absorption by Chl b markedly improved the prediction. Without such a correction, the quality of the PC prediction still increased markedly with estimates > 50 mg PC m− 3, allowing monitoring of the cyanobacterial status of eutrophic waters. The threshold concentration may be lowered when a high intracellular PC:Chl a ratio or cyanobacterial dominance is expected. Below the limit, predicted PC concentrations should be considered as the highest estimate. We evaluated that remote sensing of both PC and Chl a would allow assessment of cyanobacterial risk to water quality and public health in over 70% of our cases.
|Institutes:||Nederlands Instituut voor Ecologie (NIOO)|
|Deposited On:||15 Sep 2009 02:00|
|Last Modified:||15 Jan 2014 09:21|
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