Global Retrieval of Phytoplankton Functional Types (PFTs) from OLCI and Merged Ocean Colour products
This collaborative AWI-ACRI-ST project funded by ACRI-ST focuses on retrieving global PFTs from Sentinel-3 OLCI data and merged ocean colour (CMEMS GlobColour) products, with integrated use of extensive in situ measurements from various cruises in different regions. The main retrieved PFTs should include at least diatoms, haptophytes, prokaryotic phytoplankton, and more if possible. To achieve the goal we propose to develop a sound and solid approach to retrieve PFT globally from Sentinel-3 OLCI data and the merged ocean-colour products. This shall be done by firstly establishing PFT retrieval algorithms with full use of our current available in situ measurements from various campaigns worldwide, in which we have a number of collocated remote sensing reflectance spectra (Rrs) and PFT data based on HPLC pigments in addition to other bio-optical measurements. Previously investigated retrieval methods, empirical orthogonal functions (EOF) for pigment concentrations estimation (Bracher et al. 2015) and ocean reflectance inversion model (ORM) (Werdell et al. 2014) for PFT discrimination, will be tested and improved potentially with recently suggested band placements by Wolanin et al. (2016). The primary input data shall be multispectral in situ Rrs spectra from selected cruises, to be in consistence with S3 OLCI band setting and merged OC products, so that the established retrieval algorithms can be applied to the above mentioned satellite data. Eventually the global PFT products shall be developed for long-term and updated timely with more available OLCI data in the future. Meanwhile the prototype of the processor for PFT products shall be implemented to ODESA/SALSA (Optical Data Processor for ESA) developed by ACRI to enable convenient and efficient satellite data processing. To assess the accuracy and quality of derived PFT products, global and regional validation will be performed with intercomprison to in-situ HPLC data and other existing PFT products.
Bracher A., Taylor B.B., Taylor M., Dinter T., Röttgers R., Steinmetz F. (2015) Using empirical orthogonal functions derived from remote sensing reflectance for the prediction of concentrations of phytoplankton pigments. Ocean Science 11: 139-158.
Werdell, P. J., Roesler, C. S., and Goes, J. I. (2014). Discrimination of phytoplankton functional groups using an ocean reflectance inversion model. Appl. Opt. 53, 4833–4849. doi: 10.1364/AO.53.004833
Wolanin A., Soppa M. A., Bracher A., (2016) Investigation of spectral band requirements for improving retrievals of phytoplankton functional types. Remote Sensing 8: 871; doi:10.3390/rs8100871