Synergistic exploitation of hyper- and multispectral Sentinel measurements to determine Phytoplankton Functional Types at best spatial and temporal resolution (SynSenPFT)

Losa, SN; Soppa, MA; Dinter, T; Wolanin, A; Brewin, RJW; Bricaud, A; Oelker, J; Rozanov, V; Peeken, L; Bracher, A. 2017 Synergistic exploitation of hyper- and multispectral Sentinel measurements to determine Phytoplankton Functional Types at best spatial and temporal resolution (SynSenPFT). Frontiers in Marine Science, 4 (203). 10.3389/fmars.2017.00203

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Abstract/Summary

We derive the chlorophyll a concentration (Chla) for three main phytoplankton functional types (PFTs) – diatoms, coccolithophores and cyanobacteria – by combining satellite multispectral-based information, being of a high spatial and temporal resolution, with retrievals based on high resolution of PFT absorption properties derived from hyperspectral satellite measurements. The multispectral-based PFT Chla retrievals are based on a revised version of the empirical OC-PFT algorithm applied to the Ocean Color Climate Change Initiative (OC-CCI) total Chla product. The PhytoDOAS analytical algorithm is used with some modifications to derive PFT Chla from SCIAMACHY hyperspectral measurements. To combine synergistically these two PFT products (OC-PFT and PhytoDOAS), an optimal interpolation is performed for each PFT in every OC-PFT sub-pixel within a PhytoDOAS pixel, given its Chla and its a priori error statistics. The synergistic product (SynSenPFT) is presented for the period of August 2002 March 2012 and evaluated against PFT Chla data obtained from in situ marker pigment data and the NASA Ocean Biogeochemical Model simulations and satellite information on phytoplankton size. The most challenging aspects of the SynSenPFT algorithm implementation are discussed. Perspectives on SynSenPFT product improvements and prolongation of the time series over the next decades by adaptation to Sentinel multi- and hyperspectral instruments are highlighted.

Item Type: Publication - Article
Subjects: Biology
Earth Observation - Remote Sensing
Ecology and Environment
Marine Sciences
Divisions: Plymouth Marine Laboratory > Science Areas > Earth Observation Science and Applications
Depositing User: Robert Brewin
Date made live: 16 Aug 2017 14:06
Last Modified: 16 Aug 2017 14:06
URI: http://plymsea.ac.uk/id/eprint/7488

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