World Library  

Add to Book Shelf
Flag as Inappropriate
Email this Book

Using Empirical Orthogonal Functions Derived from Remote Sensing Reflectance for the Prediction of Concentrations of Phytoplankton Pigments : Volume 11, Issue 5 (11/09/2014)

By Bracher, A.

Click here to view

Book Id: WPLBN0004020801
Format Type: PDF Article :
File Size: Pages 45
Reproduction Date: 2015

Title: Using Empirical Orthogonal Functions Derived from Remote Sensing Reflectance for the Prediction of Concentrations of Phytoplankton Pigments : Volume 11, Issue 5 (11/09/2014)  
Author: Bracher, A.
Volume: Vol. 11, Issue 5
Language: English
Subject: Science, Ocean, Science
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


APA MLA Chicago

Dinter, T., Steinmetz, F., Taylor, M. H., Taylor, B., Röttgers, R., & Bracher, A. (2014). Using Empirical Orthogonal Functions Derived from Remote Sensing Reflectance for the Prediction of Concentrations of Phytoplankton Pigments : Volume 11, Issue 5 (11/09/2014). Retrieved from

Description: Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Bussestraße 24, 27570 Bremerhaven, Germany. The composition and abundance of algal pigments provide information on characteristics of a phytoplankton community in respect to its photoacclimation, overall biomass, and taxonomic composition. Particularly, these pigments play a major role in photoprotection and in the light-driven part of photosynthesis. Most phytoplankton pigments can be measured by High Performance Liquid Chromatography (HPLC) techniques to filtered water samples. This method, like others when water samples have to be analysed in the laboratory, is time consuming and therefore only a limited number of data points can be obtained. In order to receive information on phytoplankton pigment composition with a higher temporal and spatial resolution, we have developed a method to assess pigment concentrations from continuous optical measurements. The method applies an Empirical Orthogonal Function (EOF) analysis to remote sensing reflectance data derived from ship-based hyper-spectral underwater radiometric and from multispectral satellite data (using the MERIS Polymer product developed by Steinmetz et al., 2011) measured in the Eastern Tropical Atlantic. Subsequently we developed statistically linear models with measured (collocated) pigment concentrations as the response variable and EOF loadings as predictor variables. The model results, show that surface concentrations of a suite of pigments and pigment groups can be well predicted from the ship-based reflectance measurements, even when only a multi-spectral resolution is chosen (i.e. eight bands similar to those used by MERIS). Based on the MERIS reflectance data, concentrations of total and monovinyl chlorophyll a and the groups of photoprotective and photosynthetic carotenoids can be predicted with high quality. The fitted statistical model constructed on the satellite reflectance data as input was applied to one month of MERIS Polymer data to predict the concentration of those pigment groups for the whole Eastern Tropical Atlantic area. Bootstrapping explorations of cross-validation error indicate that the method can produce reliable predictions with relatively small data sets (e.g., < 50 collocated values of reflectance and pigment concentration). The method allows for the derivation of time series from continuous reflectance data of various pigment groups at various regions, which can be used to study variability and change of phytoplankton composition and photo-physiology.

Using empirical orthogonal functions derived from remote sensing reflectance for the prediction of concentrations of phytoplankton pigments

ACRI: GlobColour Full Validation Report, version 1.1, December 14, 2007, available at: (last access: 10 September 2014), 2007.; Aiken, J., Pradhan, Y., Barlow, R., Lavender, S., Poulton, A., Holligan, P., and Hardman-Mountford, N.: Phytoplankton pigments and functional types in the Atlantic Ocean: A decadal assessment, 1995–2005, Deep-Sea Res. Pt. II, 56, 899–917, doi:10.1016/j.dsr2.2008.09.017, 2009.; Barker, K., Mazeran, C., Lerebourg, C., Bouvet, M., Antoine, D., Ondrusek, M., Zibordi, G. and Lavender, S.: MERMAID: MERis MAtchup In-situ Database. Proceedings of the 2nd (A)ATSR and MERIS Workshop, Frascati, Italy, September 2008.; Barlow, R. G., Cummings, D. G, and Gibb, S. W.: Improved resolution of mono- anddivinyl chlorophylls a and b and zeaxanthin andlutein in phytoplankton extracts using reverse phase C-8 HPLC, Marine Ecol. Prog. Ser., 161, 303–307, 1997.; Brewin, R. J. W., Sathyendranath, S., Müeller, D., Brockmann, C., Deschamps, P.-Y., Devred, E., Doerffer, R., Fomferra, N., Franz, B. A., Grant, M. G., Groom, S. B., Horseman, A., Hu, C., Krasemann, H., Lee, Z., Maritorena, S., Mélin, F., Peters, M., Platt, T., Regner, P., Smyth, T., Steinmetz, F., Swinton, J., Werdell, J., and White III, G. N. The Ocean Colour Climate Change Initiative: A round-robin comparison on in-water bio-optical algorithms, Remote Sens. Environ., in press, 2014.; Chase, A., Boss, E., Zaneveld, R., Bricaud, A., Claustre, H., Ras, J., Dall'Olmo, G., and Westberry, T. K.: Decomposition of in situ particulate absorption spectra, Methods Oceanogr., 7, 110–124, 2013.; Craig, S. E., Jones, C. T., Li, W. K. W., Lazin, G., Horne, E., Caverhill, C., and Cullen, J. J.: Deriving optical metrics of ecological variability from measurements of coastal ocean colour, Remote Sens. Environ., 119, 72–83, 2012.; Hirata, T., Hardman-Mountford, N. J., Brewin, R. J. W., Aiken, J., Barlow, R., Suzuki, K., Isada, T., Howell, E., Hashioka, T., Noguchi-Aita, M., and Yamanaka, Y.: Synoptic relationships between surface Chlorophyll-a and diagnostic pigments specific to phytoplankton functional types, Biogeosciences, 8, 311–327, doi:10.5194/bg-8-311-2011, 2011.; Hooker, S. B., Van Heukelem, L., Thomas, C. S., Claustre, H., Ras, J., and Barlow, R.: The second SeaWiFS HPLC analysis round robin experiment (SeaHARRE-2), NASA TM/2005-212785, NASA Goddard Space Flight Center, Greenbelt, Maryland, 2005.; Longhurst, A.: Ecological Geography of the Sea, 2nd Edn., Elsevier Academic press, USA, 2006.; Lubac, B. and Loisel, H.: Variability and classi?cation of remote sensing reflectance spectra in the eastern English Channel and southern North Sea, Remote Sens. Environ., 110, 45–48, 2007.; Mackey, M. D., Mackey, D. J., Higgins, H. W., and Wright, S. W.: CHEMTAX – a program for estimating class abundances from chemical markers: application to HPLC measurements of phytoplankton pigments, Marine Ecol. Progr. Ser., 144, 265–283, 1996.; McClain, C. R.: A Decade of Satellite Ocean Color Observations, Ann. Rev. Marine Sci., 1, 19–42, doi:10.1146/annurev.marine.010908.163650, 2009.; Morel, A. and Gentili, B.: Diffuse reflectance of oceanic waters. 2. Bidirectional aspects, Appl. Opt., 32, 6864–6872, 1993.; Morel, A. and Gentili, B.: Diffuse reflectance of oceanic waters. 3. Implication of bidirectionality for the remote-sensing problem, Appl. Opt., 35, 4850–4862, 1996.; Morel, A., Voss, K. J., and Gentili, B.: Bidirectional reflectance of oceanic waters: A comparison of modeled and measured upward radiance fields, J. Geophys. Res., 100, 13143–13150, 1995.; Müller, D. and Krasemann, H.: Pr


Click To View

Additional Books

  • Characterisation and Quantification of R... (by )
  • Seasonal Cycles of Mixed Layer Salinity ... (by )
  • Structure and Forcing of the Overflow at... (by )
  • A Study of the Hydrographic Conditions i... (by )
  • Mesoscale Variability of Water Masses in... (by )
  • Halocline Water Modification and Along S... (by )
  • Validation of the Nemo-ersem Operational... (by )
  • Modeling of Wave-induced Irradiance Vari... (by )
  • Improving the Parameterisation of Horizo... (by )
  • Effects of the 2003 European Heatwave on... (by )
  • An Overview of the Synoptic Antarctic Sh... (by )
  • Upper Labrador Sea Water in the Irminger... (by )
Scroll Left
Scroll Right


Copyright © World Library Foundation. All rights reserved. eBooks from World Library are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.