Riddick CAL, Hunter PD, Gómez JAD, Martinez-Vicente V, Présing M, Horváth H, Kovács AW, Vörös L, Zsigmond E & Tyler AN (2019) Optimal Cyanobacterial Pigment Retrieval from Ocean Colour Sensors in a Highly Turbid, Optically Complex Lake. Remote Sensing, 11 (13), Art. No.: 1613. https://doi.org/10.3390/rs11131613
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.
cyanobacteria; phycocyanin; MERIS; Sentinel-3; remote sensing; Lake Balaton
Remote Sensing: Volume 11, Issue 13
|Funders||University of Stirling, NERC Airborne Research and Survey Facility (ARSF) and Field Spectroscopy Facility, NERC Airborne Research and Survey Facility (ARSF) and Field Spectroscopy Facility and Carnegie Trust|
|Publication date online||07/07/2019|
|Date accepted by journal||02/07/2019|