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Optimal Cyanobacterial Pigment Retrieval from Ocean Colour Sensors in a Highly Turbid, Optically Complex Lake

1
Biological and Environmental Science, School of Natural Sciences, University of Stirling, Stirling FK9 4LA, UK
2
Crop Research Institute, 161 06 Prague, Czech Republic
3
Remote Sensing Group, Plymouth Marine Laboratory, Plymouth PL1 3DH, UK
4
Balaton Limnological Institute, MTA Centre for Ecological Research, 8237 Tihany, Hungary
5
Institute of Genetics, Biological Research Centre Hungarian Academy of Sciences, 6726 Szeged, Hungary
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(13), 1613; https://doi.org/10.3390/rs11131613
Received: 28 May 2019 / Revised: 27 June 2019 / Accepted: 2 July 2019 / Published: 7 July 2019
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Abstract

To date, several algorithms for the retrieval of cyanobacterial phycocyanin (PC) from ocean colour sensors have been presented for inland waters, all of which claim to be robust models. To address this, we conducted a comprehensive comparison to identify the optimal algorithm for retrieval of PC concentrations in the highly optically complex waters of Lake Balaton (Hungary). MEdium Resolution Imaging Spectrometer (MERIS) top-of-atmosphere radiances were first atmospherically corrected using the Self-Contained Atmospheric Parameters Estimation for MERIS data v.B2 (SCAPE-M_B2). Overall, the Simis05 semi-analytical algorithm outperformed more complex inversion algorithms, providing accurate estimates of PC up to ±7 days from the time of satellite overpass during summer cyanobacteria blooms (RMSElog < 0.33). Same-day retrieval of PC also showed good agreement with cyanobacteria biomass (R2 > 0.66, p < 0.001). In-depth analysis of the Simis05 algorithm using in situ measurements of inherent optical properties (IOPs) revealed that the Simis05 model overestimated the phytoplankton absorption coefficient [aph(λ)] by a factor of ~2. However, these errors were compensated for by underestimation of the mass-specific chlorophyll absorption coefficient [a*chla(λ)]. This study reinforces the need for further validation of algorithms over a range of optical water types in the context of the recently launched Ocean Land Colour Instrument (OLCI) onboard Sentinel-3. View Full-Text
Keywords: cyanobacteria; phycocyanin; MERIS; Sentinel-3; remote sensing; Lake Balaton cyanobacteria; phycocyanin; MERIS; Sentinel-3; remote sensing; Lake Balaton
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Riddick, C.A.; Hunter, P.D.; Domínguez Gómez, J.A.; Martinez-Vicente, V.; Présing, M.; Horváth, H.; Kovács, A.W.; Vörös, L.; Zsigmond, E.; Tyler, A.N. Optimal Cyanobacterial Pigment Retrieval from Ocean Colour Sensors in a Highly Turbid, Optically Complex Lake. Remote Sens. 2019, 11, 1613.

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