Interpolated fields of satellite-derived multi-algorithm chlorophyll-a estimates at global and European scales in the frame of the European Copernicus-Marine Environment Monitoring Service

References

• Antoine D, Morel A. 1999. A multiple scattering algorithm for atmospheric correction of remotely sensed ocean colour (MERIS instrument): principle and implementation for atmospheres carrying various aerosols including absorbing ones. Int J Remote Sens. 20(9):1875–1916. doi: 10.1080/014311699212533
   Google Scholar
• Bowers DG, Binding CE. 2006. The optical properties of mineral suspended particles: a review and synthesis. Estuarine Coastal Shelf Sci. 67(1):219–230. doi: 10.1016/j.ecss.2005.11.010
   Google Scholar
• Bricaud A, Morel A, Babin M, Allali K, Claustre H. 1998. Variations of light absorption by suspended particles with chlorophyll a concentration in oceanic (case 1) waters: analysis and implications for bio-optical models. J Geophys Res Oceans. 103(C13):31033–31044. doi: 10.1029/98JC02712
   Google Scholar
• CMEMS. Quality Information Document. http://marine.copernicus.eu/documents/QUID/CMEMS-OC-QUID-009-033-037-082.pdf
   Google Scholar
• Doerffer R, Schiller H. 2007. The MERIS case 2 water algorithm. Int J Remote Sens. 28(3-4):517–535. doi: 10.1080/01431160600821127
   Google Scholar
• Donlon CJ, Martin M, Stark J, Roberts-Jones J, Fiedler E, Wimmer W. 2012. The operational sea surface temperature and sea ice analysis (OSTIA) system. Remote Sens Environ. 116:140–158. doi: 10.1016/j.rse.2010.10.017
   Google Scholar
• Doxaran D, Froidefond JM, Lavender S, Castaing P. 2002. Spectral signature of highly turbid waters: application with SPOT data to quantify suspended particulate matter concentrations. Remote Sens Environ. 81(1):149–161. doi: 10.1016/S0034-4257(01)00341-8
   Google Scholar
• Flannery B. 2007. Gaussian Mixture models and k-means Clustering. 3rd ed. Numerical Recipes: The Art of Scientific Computing, Section 16.1.
   Google Scholar
• Gohin F, Druon JN, Lampert L. 2002. A five channel chlorophyll concentration algorithm applied to SeaWiFS data processed by SeaDAS in coastal waters. Int J Remote Sens. 23(8):1639–1661. doi: 10.1080/01431160110071879
   Google Scholar
• Hu C, Lee Z, Franz B. 2012. Chlorophyll a algorithms for oligotrophic oceans: a novel approach based on three-band reflectance difference. J Geophys Res. 117(C1). doi: 10.1029/2011jc007395
   Google Scholar
• Krasnopolsky V, Nadiga S, Mehra A, Bayler E, Behringer D. 2016. Neural networks technique for filling gaps in satellite measurements: application to ocean color observations. Comput Intell Neurosci. Article ID 6156513:9. doi: 10.1155/2016/6156513
   Google Scholar
• Kuching S. 2007. The performance of maximum likelihood, spectral angle mapper, neural network and decision tree classifiers in hyperspectral image analysis. J Comput Sci. 3(6):419–423. doi: 10.3844/jcssp.2007.419.423
   Google Scholar
• Lee ZP. 2006. Remote sensing of inherent optical properties: fundamentals, tests of algorithms, and applications. IOCCG report, 5.
   Google Scholar
• Loisel H, Morel A. 1998. Light scattering and chlorophyll concentration in case 1 waters: a reexamination. Limnol Oceanogr. 43(5):847–858. doi: 10.4319/lo.1998.43.5.0847
   Google Scholar
• Matheron G. 1971. The Theory of Regionalized Variables and Its Applications. Paris, France: Cahier du centre de Morphologie Mathémathique de Fontainblea. p. 211, No. 5.
   Google Scholar
• Melin F, Vantrepotte V, Chuprin A, Grant M, Jackson T, Sathyendranath S. 2017. Assessing the fitness-for-purpose of satellite multi-mission ocean color climate data records: a protocol applied to OC-CCI chlorophyll- a data. Remote Sens Environ. 203:139–151. doi: 10.1016/j.rse.2017.03.039
   Google Scholar
• MERIS Level 2 Detailed Processing Model. [Online]. Available: https://earth.esa.int/documents/700255/707222/MERIS-DPM-L2-i8r0B.pdf/c5249b79-bf8d-4a27-b397-bfb4a74753db.
   Google Scholar
• Moore TS, Campbell JW, Feng H. 2001. A fuzzy logic classification scheme for selecting and blending satellite ocean color algorithms. IEEE Trans Geosci Remote Sens. 39(8):1764–1776. doi: 10.1109/36.942555
   Google Scholar
• Morel A, Gentili B, Chami M, Ras J. 2006. Bio-optical properties of high chlorophyll case 1 waters, and of yellow substance-dominated case 2 waters. Deep Sea Res Part I. 53:1439–1459. doi: 10.1016/j.dsr.2006.07.007
   Google Scholar
• Morel A, Huot Y, Gentili B, Werdell PJ, Hooker SB, Franz BA. 2007. Examining the consistency of products derived from various ocean color sensors in open ocean (case 1) waters in the perspective of a multi-sensor approach. Remote Sens Environ. 111:69–88. doi: 10.1016/j.rse.2007.03.012
   Google Scholar
• O'Reilly JE, Maritorena S, Siegel DA, O'Brien MC, Toole D, Mitchell BG, Hooker SB, et al. 2000. Ocean colorchlorophyll a algorithms for SeaWiFS, OC2, and OC4: Version 4. SeaWiFS postlaunch calibration and validation analyses, Part, 3, 9–23.
   Google Scholar
• Saulquin B, Fablet R, Ailliot P, Mercier G, Doxaran D, Mangin A, d'Andon OHF. 2015. Characterization of time-varying regimes in remote sensing time series: application to the forecasting of satellite-derived suspended matter concentrations. IEEE J STARS. 8:406–417.
   Google Scholar
• Saulquin B, Fablet R, Bourg L, Mercier G, d'Andon OF. 2016. MEETC2: ocean color atmospheric corrections in coastal complex waters using a Bayesian latent class model and potential for the incoming sentinel 3—OLCI mission. Remote Sens Environ. 172:39–49. doi: 10.1016/j.rse.2015.10.035
   Google Scholar
• Saulquin B, Gohin F, Garrello R. 2010. Regional objective analysis for merging high-resolution MERIS, MODIS/Aqua, and SeaWiFS chlorophyll-a data from 1998 to 2008 on the European Atlantic Shelf. IEEE Trans. Geosc. and Remote Sensing.
   Google Scholar
• Saulquin B, Hamdi A, Gohin F, Populus J, Mangin A, d'Andon OF. 2013. Estimation of the diffuse attenuation coefficient KdPAR using MERIS and application to seabed habitat mapping. Remote Sens Environ. 128:224–233. doi: 10.1016/j.rse.2012.10.002
   Google Scholar
• Schaeffer P, Faugere Y, Legeais JF, Picot N. 2011. The CNES CLS 2011 global mean sea surface. San-Diego: OST-ST.
   Google Scholar
• SeaWiFS Postlaunch Technical report series Nasa Tech. Memo., 2003–206892, vol. 22.
   Google Scholar
• Siegel DA, Maritorena S, Nelson NB, Behrenfeld MJ, McClain CR. 2005. Colored dissolved organic matter and its influence on the satellite-based characterization of the ocean biosphere. Geophys Res Lett. 32(20). doi: 10.1029/2005GL024310
   Google Scholar
• Tandeo P, Autret E, Chapron B, Fablet R, Garello R. 2014. SST spatial anisotropic covariances from METOP-AVHRR data. Remote Sens Environ. 141:144–148. doi: 10.1016/j.rse.2013.10.024
   Google Scholar
• Tilstone G, Mallor-Hoya S, Gohin F, Couto AB, Sá C, Goela P, Groom S. 2017. Which ocean colour algorithm for MERIS in North West European waters? Remote Sens Environ. 189:132–151. doi: 10.1016/j.rse.2016.11.012
   Google Scholar
• Wang M. 2010. Atmospheric correction for remotely-sensed ocean-colour products. Reports and Monographs of the International Ocean-Colour Coordinating Group (IOCCG).
   Google Scholar