Optimization of a semianalytical ocean color model for global-scale applications.

By Stephane Maritorena, D. Siegel, Alan R Peterson. Applied Optics, 2002

947 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/450d8ab77e752e169c67a1197f420e0f3f366f94

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Citations in the corpus

Space‐based lidar measurements of global ocean carbon stocks (2013, methodology): “…(22°N, 40°W) (Methods S1, sections c and d) and (2) MODIS-Aqua satellite ocean color b bp products from the Garver-Siegel-Maritorena (GSM) inversion algorithm [ Garver and Siegel , 1997; Maritorena et al ., 2002; Siegel et al ., 2002] and the Quasi-Analytical Algorithm (QAA) [ Lee et al ., 2002].”
Deriving optical metrics of coastal phytoplankton biomass from ocean colour (2012, neutral): “These fall broadly into two classes of algorithms—empirical band-ratio algorithms, which are derived from the statistical relationship between the ratio of two or more wavebands (blue and green) of remote sensing reflectance, Rrs (sr−1; see Table 1 for a list of symbols and units) and in situ measur”
Sensor Capability and Atmospheric Correction in Ocean Colour Remote Sensing (2015, methodology): “These estimates are then used to derive the biological and biogeochemical properties of the water, such as concentrations of phytoplankton and chlorophyll-a [31], total suspended matter [32–34], coloured dissolved organic matter (CDOM) and detritus, or the inherent optical properties (IOPs) of the w”
Particle optical backscattering along a chlorophyll gradient in the upper layer of the eastern South Pacific Ocean (2007, methodology): “(2005) used the Garver-Siegel-Maritorena inversion model (Maritorena et al., 2002), and a bias in the satellitederived backscattering coefficient probably occurs when this model is used at low [Chl] (see Appendix).”
A decade of satellite ocean color observations. (2009, methodology): “For example, Chomko et al. (2003) used a set of 72 aerosol models, including absorbing aerosols, with the Maritorena et al. (2002) ocean reflectance model (a revision of Garver & Siegel 1997) to formulate a “spectral optimization” technique and successfully tested it using SeaWiFS data off the U.S.…”
Optical oceanography: Recent advances and future directions using global remote sensing and in situ observations (2006, methodology): “Several inverse models have been reported [e.g., Morel, 1988; Garver and Siegel, 1997; Barnard et al., 1999; Loisel et al., 2001; Morel and Maritorena, 2001; Lee et al., 2002; Maritorena et al., 2002; Roesler and Boss, 2003].”
Carbon‐based ocean productivity and phytoplankton physiology from space (2005, methodology): “…(Chl: mg m 3) and bbp at 440 nm (m 1) were estimated using the Garver-SiegelMaritorena (GSM) semi-analytical algorithm [Garver and Siegel,1997; Maritorena et al., 2002; Siegel et al., 2002] and monthly satellite water-leaving radiances for the September 1997 to January 2002 period from the…”
Consistent merging of satellite ocean color data sets using a bio-optical model (2005, methodology): “The performance of the GSM01 model and a comparison with the retrievals from the SeaWiFS operational algorithm (OC4) were presented in a previous paper using in situ data (Maritorena et al., 2002).”
Abandoning Sverdrup's Critical Depth Hypothesis on phytoplankton blooms. (2010, background): “Key words: Critical Depth Hypothesis; grazing; growth rates; North Atlantic; phytoplankton blooms; remote sensing.”
Colored dissolved organic matter and its influence on the satellite‐based characterization of the ocean biosphere (2005, methodology): “…GSM algorithm considers that Chl, colored dissolved and detrital organic materials (CDM) and particulate abundances each independently affect ocean color and these properties are retrieved simultaneously from a water-leaving radiance spectrum [Maritorena et al., 2002; Siegel et al., 2002, 2005].”