Abstract

With the increasing interest in ocean color remote sensing in polar oceans and geostationary ocean color satellite with diurnal observations, it is unavoidable to encounter ocean color retrievals under high solar zenith angles. Under these scenarios, the capability of current remote sensing algorithms is poorly known. In this study, the performance of the two widely used semi-analytical algorithms for the water inherent optical properties (QAA and GSM01) under high solar zenith angle conditions were firstly evaluated based on global in situ data set (SeaBASS-NOMAD). The results showed that the performances of both QAA and GSM01 degraded significantly with the increasing in solar zenith angle (SZA), and the biases increased about 1.3-fold when SZA varied from 30° to 80°. The high uncertainties at high SZA was mainly induced by the systematic overestimation of the key parameter u (ratio of backscattering coefficient to the sum of absorption and backscattering coefficients) at high solar zenith angles. Based on the Hydrolight-simulated data set, a new model (NN-algorithm) for retrieving u from remote sensing reflectance was developed for high solar zenith angle conditions using the neural network method. The validation results revealed that the NN-algorithm could improve the estimation of parameter u and further ocean color products. In addition, our results indicate that a more accurate atmosphere correction is needed to deal with ocean color remote sensing data acquired under large solar zenith angle conditions.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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2018 (1)

X He, K Stamnes, Y Bai, W Li, and D Wang, “Effects of Earth curvature on atmospheric correction for ocean color remote sensing,” Remote Sensing of Environment.  209,118–133. (2018)

2017 (4)

S. Vadakke-Chanat and P. Shanmugam, “Modelling the contributions of phytoplankton and non-algal particles to spectral scattering properties in near-shore and lagoon waters,” Cont. Shelf Res. 135, 35–46 (2017).
[Crossref]

S. Vadakke-Chanat, P. Shanmugam, and Y. H. Ahn, “A Model for Deriving the Spectral Backscattering Properties of Particles in Inland and Marine Waters From In Situ and Remote Sensing Data,” IEEE Trans. Geosci. Remote Sens. 55(3), 1461–1476 (2017).
[Crossref]

H. Li, X. He, Y. Bai, X. Y. Chen, F. Gong, Q. K. Zhu, and Z. F. Hu, “Assessment of satellite-based chlorophyll-a retrieval algorithms for high sun zenith angle conditions,” J. Appl. Remote Sens. 11(1), 012004 (2017).
[Crossref]

Y. Fan, W. Li, K. J. Voss, C. K. Gatebe, and K. Stamnes, “A neural network method to correct bidirectional effects in water-leaving radiance,” AIP Conference Procedings 1810(120001), 12001 (2017).
[Crossref]

2016 (3)

H. Li, X. He, J. Ding, Z. F. Hu, W. S. Cui, S. D. Li, and L. Zhang, “Validation of the Remote Sensing Products Retrieved by Geostationary Ocean Color Imager in Liaodong Bay in Spring,” Acta Opt. Sin. 36(4), 0401002 (2016).
[Crossref]

F. Watanabe, D. R. Mishra, I. Astuti, T. Rodrigues, E. Alcântara, N. N. Imai, and C. Barbosa, “Parametrization and calibration of a quasi-analytical algorithm for tropical eutrophic waters,” ISPRS J. Photogramm. Remote Sens. 121(C), 28–47 (2016).
[Crossref]

Z. Hu, D. P. Wang, D. Pan, X. He, Y. Miyazawa, Y. Bai, D. Wang, and F. Gong, “Mapping surface tidal currents and Changjiang plume in the East China Sea from Geostationary Ocean Color Imager,” J. Geophys. Res. Oceans 121(3), 1563–1572 (2016).
[Crossref]

2015 (1)

J. E. Chaves, P. J. Werdell, C. W. Proctor, A. R. Neeley, S. A. Freeman, C. S. Thomas, and S. B. Hooker, “Assessment of ocean color data records from MODIS-Aqua in the western Arctic Ocean,” Deep Sea Res. Part II Top. Stud. Oceanogr. 118, 32–43 (2015).
[Crossref]

2014 (3)

R. K. Singh and P. Shanmugam, “A novel method for estimation of aerosol radiance and its extrapolation in the atmospheric correction of satellite data over optically complex oceanic waters,” Remote Sens. Environ. 142(1), 188–206 (2014).
[Crossref]

X. He, D. Pan, Y. Bai, D. Wang, and Z. Hao, “A new simple concept for ocean colour remote sensing using parallel polarisation radiance,” Sci. Rep. 4(6168), 3748 (2014).
[PubMed]

N. Pahlevan, Z. Lee, C. Hu, and J. R. Schott, “Diurnal remote sensing of coastal/oceanic waters: a radiometric analysis for Geostationary Coastal and Air Pollution Events,” Appl. Opt. 53(4), 648–665 (2014).
[Crossref] [PubMed]

2013 (2)

I. Ioannou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, “Deriving ocean color products using neural networks,” Remote Sens. Environ. 134(7), 78–91 (2013).
[Crossref]

X. He, Y. Bai, D. Pan, N. Huang, X. Dong, J. Chen, C.-T. A. Chen, and Q. Cui, “Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters,” Remote Sens. Environ. 133(12), 225–239 (2013).
[Crossref]

2012 (2)

J. K. Choi, Y. J. Park, and J. H. Ahn, “GOCI, the world’s first geostationary ocean color observation satellite, for the monitoring of temporal variability in coastal water turbidity,” J. Geophys. Res. Oceans 117(C9), 1–14 (2012).

J. H. Ryu, H. J. Han, S. Cho, Y.-J. Park, and Y.-H. Ahn, “Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS),” Ocean Science Journal. 47(3), 223–233 (2012).
[Crossref]

2011 (1)

2009 (1)

L. Sun, X. Wang, M. Guo, and J.W Tang, “MODIS ocean color product validation around the Yellow Sea and East China Sea,” Hupo Kexue 21(2), 298–306 (2009).
[Crossref]

2008 (1)

Y. H. Ahn, P. Shanmugam, J. E. Moon, and J. H. Ryu, “Satellite remote sensing of a low-salinity water plume in the East China Sea,” Ann. Geophys. 26(7), 2019–2035 (2008).
[Crossref]

2007 (2)

Z. P. Lee, A. Weidemann, and J. Kindle, “Euphotic zone depth: Its derivation and implication to ocean-color remote sensing,” J. Geophys. Res. Oceans 112(C3), 1–12 (2007).

G. Volpe, R. Santoleri, V. Vellucci, M. Ribera d’Alcalà, S. Marullo, and F. D’Ortenzio, “The colour of the Mediterranean Sea: Global versus regional bio-optical algorithms evaluation and implication for satellite chlorophyll estimates,” Remote Sens. Environ. 107(4), 625–638 (2007).
[Crossref]

2005 (1)

P. J. Werdell and S. W. Bailey, “An improved in-situ bio-optical data set for ocean color algorithm development and satellite data product validation,” Remote Sens. Environ. 98(1), 122–140 (2005).
[Crossref]

2003 (1)

T. Zhang, F. Fell, and Z. S. Liu, “Evaluating the performance of artificial neural network techniques for pigment retrieval from ocean color in Case I waters,” J. Geophys. Res. D Atmospheres 108(C9), 1–12 (2003).
[Crossref]

2002 (3)

2001 (1)

A. Morel and S. Maritorena, “Bio-optical properties of oceanic waters: A reappraisal,” J. Geophys. Res. Oceans 106(C4), 7163–7180 (2001).
[Crossref]

1999 (2)

K. L. Carder, F. R. Chen, Z. P. Lee, S. K. Hawes, and D. Kamykowski, “Semianalytic Moderate-Resolution Imaging Spectrometer Algorithms for Chlorophyll A and Absorption with Bio-Optical Domains Based on Nitrate-Depletion Temperatures,” J. Geophys. Res. D Atmospheres 104(C3), 5403–5421 (1999).
[Crossref]

L. Gross, S. Thiria, and R. Frouin, “Applying artificial neural network methodology to ocean color remote sensing,” Ecol. Modell. 120(2–3), 237–246 (1999).
[Crossref]

1998 (1)

J. E. O’Reilly, S. Maritorena, B. G. Mitchell, D. A. Siegel, K. L. Carder, S. A. Garver, M. Kahru, and C. McClain, “Ocean color chlorophyll algorithms for SeaWiFS,” J. Geophys. Res. Oceans 103(C11), 24937–24953 (1998).
[Crossref]

1996 (1)

L. Lazzara, A. Bricaud, and H. Claustre, “Spectral absorption and fluorescence excitation properties of phytoplanktonic populations at a mesotrophic and an oligotrophic site in the tropical North Atlantic (EUMELI program),” Deep Sea Res. Part I Oceanogr. Res. Pap. 43(8), 1215–1240 (1996).
[Crossref]

1994 (1)

1993 (1)

1991 (2)

A. Morel and B. Gentili, “Diffuse reflectance of oceanic waters: its dependence on Sun angle as influenced by the molecular scattering contribution,” Appl. Opt. 30(30), 4427–4438 (1991).
[Crossref] [PubMed]

K. L. Carder, S. K. Hawes, K. A. Baker, R. C. Smith, R. G. Steward, and B. G. Mitchell, “Reflectance model for quantifying chlorophyll a in the presence of productivity degradation products,” J. Geophys. Res. Oceans 96(C11), 20599–20611 (1991).
[Crossref]

1988 (1)

H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, and D. K. Clark, “A semianalytic radiance model of ocean color,” J. Geophys. Res. D Atmospheres 93(D9), 10909–10924 (1988).
[Crossref]

Ahmed, S.

I. Ioannou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, “Deriving ocean color products using neural networks,” Remote Sens. Environ. 134(7), 78–91 (2013).
[Crossref]

I. Ioannou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, “Neural network approach to retrieve the inherent optical properties of the ocean from observations of MODIS,” Appl. Opt. 50(19), 3168–3186 (2011).
[Crossref] [PubMed]

Ahn, J. H.

J. K. Choi, Y. J. Park, and J. H. Ahn, “GOCI, the world’s first geostationary ocean color observation satellite, for the monitoring of temporal variability in coastal water turbidity,” J. Geophys. Res. Oceans 117(C9), 1–14 (2012).

Ahn, Y. H.

S. Vadakke-Chanat, P. Shanmugam, and Y. H. Ahn, “A Model for Deriving the Spectral Backscattering Properties of Particles in Inland and Marine Waters From In Situ and Remote Sensing Data,” IEEE Trans. Geosci. Remote Sens. 55(3), 1461–1476 (2017).
[Crossref]

Y. H. Ahn, P. Shanmugam, J. E. Moon, and J. H. Ryu, “Satellite remote sensing of a low-salinity water plume in the East China Sea,” Ann. Geophys. 26(7), 2019–2035 (2008).
[Crossref]

Ahn, Y.-H.

J. H. Ryu, H. J. Han, S. Cho, Y.-J. Park, and Y.-H. Ahn, “Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS),” Ocean Science Journal. 47(3), 223–233 (2012).
[Crossref]

Alcântara, E.

F. Watanabe, D. R. Mishra, I. Astuti, T. Rodrigues, E. Alcântara, N. N. Imai, and C. Barbosa, “Parametrization and calibration of a quasi-analytical algorithm for tropical eutrophic waters,” ISPRS J. Photogramm. Remote Sens. 121(C), 28–47 (2016).
[Crossref]

Antoine, D.

Arnone, R. A.

Astuti, I.

F. Watanabe, D. R. Mishra, I. Astuti, T. Rodrigues, E. Alcântara, N. N. Imai, and C. Barbosa, “Parametrization and calibration of a quasi-analytical algorithm for tropical eutrophic waters,” ISPRS J. Photogramm. Remote Sens. 121(C), 28–47 (2016).
[Crossref]

Bai, Y

X He, K Stamnes, Y Bai, W Li, and D Wang, “Effects of Earth curvature on atmospheric correction for ocean color remote sensing,” Remote Sensing of Environment.  209,118–133. (2018)

Bai, Y.

H. Li, X. He, Y. Bai, X. Y. Chen, F. Gong, Q. K. Zhu, and Z. F. Hu, “Assessment of satellite-based chlorophyll-a retrieval algorithms for high sun zenith angle conditions,” J. Appl. Remote Sens. 11(1), 012004 (2017).
[Crossref]

Z. Hu, D. P. Wang, D. Pan, X. He, Y. Miyazawa, Y. Bai, D. Wang, and F. Gong, “Mapping surface tidal currents and Changjiang plume in the East China Sea from Geostationary Ocean Color Imager,” J. Geophys. Res. Oceans 121(3), 1563–1572 (2016).
[Crossref]

X. He, D. Pan, Y. Bai, D. Wang, and Z. Hao, “A new simple concept for ocean colour remote sensing using parallel polarisation radiance,” Sci. Rep. 4(6168), 3748 (2014).
[PubMed]

X. He, Y. Bai, D. Pan, N. Huang, X. Dong, J. Chen, C.-T. A. Chen, and Q. Cui, “Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters,” Remote Sens. Environ. 133(12), 225–239 (2013).
[Crossref]

Bailey, S. W.

P. J. Werdell and S. W. Bailey, “An improved in-situ bio-optical data set for ocean color algorithm development and satellite data product validation,” Remote Sens. Environ. 98(1), 122–140 (2005).
[Crossref]

Baker, K. A.

K. L. Carder, S. K. Hawes, K. A. Baker, R. C. Smith, R. G. Steward, and B. G. Mitchell, “Reflectance model for quantifying chlorophyll a in the presence of productivity degradation products,” J. Geophys. Res. Oceans 96(C11), 20599–20611 (1991).
[Crossref]

Baker, K. S.

H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, and D. K. Clark, “A semianalytic radiance model of ocean color,” J. Geophys. Res. D Atmospheres 93(D9), 10909–10924 (1988).
[Crossref]

Barbosa, C.

F. Watanabe, D. R. Mishra, I. Astuti, T. Rodrigues, E. Alcântara, N. N. Imai, and C. Barbosa, “Parametrization and calibration of a quasi-analytical algorithm for tropical eutrophic waters,” ISPRS J. Photogramm. Remote Sens. 121(C), 28–47 (2016).
[Crossref]

Bricaud, A.

L. Lazzara, A. Bricaud, and H. Claustre, “Spectral absorption and fluorescence excitation properties of phytoplanktonic populations at a mesotrophic and an oligotrophic site in the tropical North Atlantic (EUMELI program),” Deep Sea Res. Part I Oceanogr. Res. Pap. 43(8), 1215–1240 (1996).
[Crossref]

Brown, J. W.

H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, and D. K. Clark, “A semianalytic radiance model of ocean color,” J. Geophys. Res. D Atmospheres 93(D9), 10909–10924 (1988).
[Crossref]

Brown, O. B.

H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, and D. K. Clark, “A semianalytic radiance model of ocean color,” J. Geophys. Res. D Atmospheres 93(D9), 10909–10924 (1988).
[Crossref]

Carder, K. L.

Z. Lee, K. L. Carder, and R. A. Arnone, “Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters,” Appl. Opt. 41(27), 5755–5772 (2002).
[Crossref] [PubMed]

K. L. Carder, F. R. Chen, Z. P. Lee, S. K. Hawes, and D. Kamykowski, “Semianalytic Moderate-Resolution Imaging Spectrometer Algorithms for Chlorophyll A and Absorption with Bio-Optical Domains Based on Nitrate-Depletion Temperatures,” J. Geophys. Res. D Atmospheres 104(C3), 5403–5421 (1999).
[Crossref]

J. E. O’Reilly, S. Maritorena, B. G. Mitchell, D. A. Siegel, K. L. Carder, S. A. Garver, M. Kahru, and C. McClain, “Ocean color chlorophyll algorithms for SeaWiFS,” J. Geophys. Res. Oceans 103(C11), 24937–24953 (1998).
[Crossref]

K. L. Carder, S. K. Hawes, K. A. Baker, R. C. Smith, R. G. Steward, and B. G. Mitchell, “Reflectance model for quantifying chlorophyll a in the presence of productivity degradation products,” J. Geophys. Res. Oceans 96(C11), 20599–20611 (1991).
[Crossref]

Chaves, J. E.

J. E. Chaves, P. J. Werdell, C. W. Proctor, A. R. Neeley, S. A. Freeman, C. S. Thomas, and S. B. Hooker, “Assessment of ocean color data records from MODIS-Aqua in the western Arctic Ocean,” Deep Sea Res. Part II Top. Stud. Oceanogr. 118, 32–43 (2015).
[Crossref]

Chen, C.-T. A.

X. He, Y. Bai, D. Pan, N. Huang, X. Dong, J. Chen, C.-T. A. Chen, and Q. Cui, “Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters,” Remote Sens. Environ. 133(12), 225–239 (2013).
[Crossref]

Chen, F. R.

K. L. Carder, F. R. Chen, Z. P. Lee, S. K. Hawes, and D. Kamykowski, “Semianalytic Moderate-Resolution Imaging Spectrometer Algorithms for Chlorophyll A and Absorption with Bio-Optical Domains Based on Nitrate-Depletion Temperatures,” J. Geophys. Res. D Atmospheres 104(C3), 5403–5421 (1999).
[Crossref]

Chen, J.

X. He, Y. Bai, D. Pan, N. Huang, X. Dong, J. Chen, C.-T. A. Chen, and Q. Cui, “Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters,” Remote Sens. Environ. 133(12), 225–239 (2013).
[Crossref]

Chen, X. Y.

H. Li, X. He, Y. Bai, X. Y. Chen, F. Gong, Q. K. Zhu, and Z. F. Hu, “Assessment of satellite-based chlorophyll-a retrieval algorithms for high sun zenith angle conditions,” J. Appl. Remote Sens. 11(1), 012004 (2017).
[Crossref]

Cho, S.

J. H. Ryu, H. J. Han, S. Cho, Y.-J. Park, and Y.-H. Ahn, “Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS),” Ocean Science Journal. 47(3), 223–233 (2012).
[Crossref]

Choi, J. K.

J. K. Choi, Y. J. Park, and J. H. Ahn, “GOCI, the world’s first geostationary ocean color observation satellite, for the monitoring of temporal variability in coastal water turbidity,” J. Geophys. Res. Oceans 117(C9), 1–14 (2012).

Clark, D. K.

H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, and D. K. Clark, “A semianalytic radiance model of ocean color,” J. Geophys. Res. D Atmospheres 93(D9), 10909–10924 (1988).
[Crossref]

Claustre, H.

L. Lazzara, A. Bricaud, and H. Claustre, “Spectral absorption and fluorescence excitation properties of phytoplanktonic populations at a mesotrophic and an oligotrophic site in the tropical North Atlantic (EUMELI program),” Deep Sea Res. Part I Oceanogr. Res. Pap. 43(8), 1215–1240 (1996).
[Crossref]

Cui, Q.

X. He, Y. Bai, D. Pan, N. Huang, X. Dong, J. Chen, C.-T. A. Chen, and Q. Cui, “Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters,” Remote Sens. Environ. 133(12), 225–239 (2013).
[Crossref]

Cui, W. S.

H. Li, X. He, J. Ding, Z. F. Hu, W. S. Cui, S. D. Li, and L. Zhang, “Validation of the Remote Sensing Products Retrieved by Geostationary Ocean Color Imager in Liaodong Bay in Spring,” Acta Opt. Sin. 36(4), 0401002 (2016).
[Crossref]

D’Ortenzio, F.

G. Volpe, R. Santoleri, V. Vellucci, M. Ribera d’Alcalà, S. Marullo, and F. D’Ortenzio, “The colour of the Mediterranean Sea: Global versus regional bio-optical algorithms evaluation and implication for satellite chlorophyll estimates,” Remote Sens. Environ. 107(4), 625–638 (2007).
[Crossref]

Ding, J.

H. Li, X. He, J. Ding, Z. F. Hu, W. S. Cui, S. D. Li, and L. Zhang, “Validation of the Remote Sensing Products Retrieved by Geostationary Ocean Color Imager in Liaodong Bay in Spring,” Acta Opt. Sin. 36(4), 0401002 (2016).
[Crossref]

Dong, X.

X. He, Y. Bai, D. Pan, N. Huang, X. Dong, J. Chen, C.-T. A. Chen, and Q. Cui, “Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters,” Remote Sens. Environ. 133(12), 225–239 (2013).
[Crossref]

Evans, R. H.

H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, and D. K. Clark, “A semianalytic radiance model of ocean color,” J. Geophys. Res. D Atmospheres 93(D9), 10909–10924 (1988).
[Crossref]

Fan, Y.

Y. Fan, W. Li, K. J. Voss, C. K. Gatebe, and K. Stamnes, “A neural network method to correct bidirectional effects in water-leaving radiance,” AIP Conference Procedings 1810(120001), 12001 (2017).
[Crossref]

Fell, F.

T. Zhang, F. Fell, and Z. S. Liu, “Evaluating the performance of artificial neural network techniques for pigment retrieval from ocean color in Case I waters,” J. Geophys. Res. D Atmospheres 108(C9), 1–12 (2003).
[Crossref]

Freeman, S. A.

J. E. Chaves, P. J. Werdell, C. W. Proctor, A. R. Neeley, S. A. Freeman, C. S. Thomas, and S. B. Hooker, “Assessment of ocean color data records from MODIS-Aqua in the western Arctic Ocean,” Deep Sea Res. Part II Top. Stud. Oceanogr. 118, 32–43 (2015).
[Crossref]

Frouin, R.

L. Gross, S. Thiria, and R. Frouin, “Applying artificial neural network methodology to ocean color remote sensing,” Ecol. Modell. 120(2–3), 237–246 (1999).
[Crossref]

Garver, S. A.

J. E. O’Reilly, S. Maritorena, B. G. Mitchell, D. A. Siegel, K. L. Carder, S. A. Garver, M. Kahru, and C. McClain, “Ocean color chlorophyll algorithms for SeaWiFS,” J. Geophys. Res. Oceans 103(C11), 24937–24953 (1998).
[Crossref]

Gatebe, C. K.

Y. Fan, W. Li, K. J. Voss, C. K. Gatebe, and K. Stamnes, “A neural network method to correct bidirectional effects in water-leaving radiance,” AIP Conference Procedings 1810(120001), 12001 (2017).
[Crossref]

Gentili, B.

Gilerson, A.

I. Ioannou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, “Deriving ocean color products using neural networks,” Remote Sens. Environ. 134(7), 78–91 (2013).
[Crossref]

I. Ioannou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, “Neural network approach to retrieve the inherent optical properties of the ocean from observations of MODIS,” Appl. Opt. 50(19), 3168–3186 (2011).
[Crossref] [PubMed]

Gong, F.

H. Li, X. He, Y. Bai, X. Y. Chen, F. Gong, Q. K. Zhu, and Z. F. Hu, “Assessment of satellite-based chlorophyll-a retrieval algorithms for high sun zenith angle conditions,” J. Appl. Remote Sens. 11(1), 012004 (2017).
[Crossref]

Z. Hu, D. P. Wang, D. Pan, X. He, Y. Miyazawa, Y. Bai, D. Wang, and F. Gong, “Mapping surface tidal currents and Changjiang plume in the East China Sea from Geostationary Ocean Color Imager,” J. Geophys. Res. Oceans 121(3), 1563–1572 (2016).
[Crossref]

Gordon, H. R.

H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, and D. K. Clark, “A semianalytic radiance model of ocean color,” J. Geophys. Res. D Atmospheres 93(D9), 10909–10924 (1988).
[Crossref]

Gross, B.

I. Ioannou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, “Deriving ocean color products using neural networks,” Remote Sens. Environ. 134(7), 78–91 (2013).
[Crossref]

I. Ioannou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, “Neural network approach to retrieve the inherent optical properties of the ocean from observations of MODIS,” Appl. Opt. 50(19), 3168–3186 (2011).
[Crossref] [PubMed]

Gross, L.

L. Gross, S. Thiria, and R. Frouin, “Applying artificial neural network methodology to ocean color remote sensing,” Ecol. Modell. 120(2–3), 237–246 (1999).
[Crossref]

Guo, M.

L. Sun, X. Wang, M. Guo, and J.W Tang, “MODIS ocean color product validation around the Yellow Sea and East China Sea,” Hupo Kexue 21(2), 298–306 (2009).
[Crossref]

Han, H. J.

J. H. Ryu, H. J. Han, S. Cho, Y.-J. Park, and Y.-H. Ahn, “Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS),” Ocean Science Journal. 47(3), 223–233 (2012).
[Crossref]

Hao, Z.

X. He, D. Pan, Y. Bai, D. Wang, and Z. Hao, “A new simple concept for ocean colour remote sensing using parallel polarisation radiance,” Sci. Rep. 4(6168), 3748 (2014).
[PubMed]

Hawes, S. K.

K. L. Carder, F. R. Chen, Z. P. Lee, S. K. Hawes, and D. Kamykowski, “Semianalytic Moderate-Resolution Imaging Spectrometer Algorithms for Chlorophyll A and Absorption with Bio-Optical Domains Based on Nitrate-Depletion Temperatures,” J. Geophys. Res. D Atmospheres 104(C3), 5403–5421 (1999).
[Crossref]

K. L. Carder, S. K. Hawes, K. A. Baker, R. C. Smith, R. G. Steward, and B. G. Mitchell, “Reflectance model for quantifying chlorophyll a in the presence of productivity degradation products,” J. Geophys. Res. Oceans 96(C11), 20599–20611 (1991).
[Crossref]

He, X

X He, K Stamnes, Y Bai, W Li, and D Wang, “Effects of Earth curvature on atmospheric correction for ocean color remote sensing,” Remote Sensing of Environment.  209,118–133. (2018)

He, X.

H. Li, X. He, Y. Bai, X. Y. Chen, F. Gong, Q. K. Zhu, and Z. F. Hu, “Assessment of satellite-based chlorophyll-a retrieval algorithms for high sun zenith angle conditions,” J. Appl. Remote Sens. 11(1), 012004 (2017).
[Crossref]

Z. Hu, D. P. Wang, D. Pan, X. He, Y. Miyazawa, Y. Bai, D. Wang, and F. Gong, “Mapping surface tidal currents and Changjiang plume in the East China Sea from Geostationary Ocean Color Imager,” J. Geophys. Res. Oceans 121(3), 1563–1572 (2016).
[Crossref]

H. Li, X. He, J. Ding, Z. F. Hu, W. S. Cui, S. D. Li, and L. Zhang, “Validation of the Remote Sensing Products Retrieved by Geostationary Ocean Color Imager in Liaodong Bay in Spring,” Acta Opt. Sin. 36(4), 0401002 (2016).
[Crossref]

X. He, D. Pan, Y. Bai, D. Wang, and Z. Hao, “A new simple concept for ocean colour remote sensing using parallel polarisation radiance,” Sci. Rep. 4(6168), 3748 (2014).
[PubMed]

X. He, Y. Bai, D. Pan, N. Huang, X. Dong, J. Chen, C.-T. A. Chen, and Q. Cui, “Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters,” Remote Sens. Environ. 133(12), 225–239 (2013).
[Crossref]

Hooker, S. B.

J. E. Chaves, P. J. Werdell, C. W. Proctor, A. R. Neeley, S. A. Freeman, C. S. Thomas, and S. B. Hooker, “Assessment of ocean color data records from MODIS-Aqua in the western Arctic Ocean,” Deep Sea Res. Part II Top. Stud. Oceanogr. 118, 32–43 (2015).
[Crossref]

Hu, C.

Hu, Z.

Z. Hu, D. P. Wang, D. Pan, X. He, Y. Miyazawa, Y. Bai, D. Wang, and F. Gong, “Mapping surface tidal currents and Changjiang plume in the East China Sea from Geostationary Ocean Color Imager,” J. Geophys. Res. Oceans 121(3), 1563–1572 (2016).
[Crossref]

Hu, Z. F.

H. Li, X. He, Y. Bai, X. Y. Chen, F. Gong, Q. K. Zhu, and Z. F. Hu, “Assessment of satellite-based chlorophyll-a retrieval algorithms for high sun zenith angle conditions,” J. Appl. Remote Sens. 11(1), 012004 (2017).
[Crossref]

H. Li, X. He, J. Ding, Z. F. Hu, W. S. Cui, S. D. Li, and L. Zhang, “Validation of the Remote Sensing Products Retrieved by Geostationary Ocean Color Imager in Liaodong Bay in Spring,” Acta Opt. Sin. 36(4), 0401002 (2016).
[Crossref]

Huang, N.

X. He, Y. Bai, D. Pan, N. Huang, X. Dong, J. Chen, C.-T. A. Chen, and Q. Cui, “Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters,” Remote Sens. Environ. 133(12), 225–239 (2013).
[Crossref]

Imai, N. N.

F. Watanabe, D. R. Mishra, I. Astuti, T. Rodrigues, E. Alcântara, N. N. Imai, and C. Barbosa, “Parametrization and calibration of a quasi-analytical algorithm for tropical eutrophic waters,” ISPRS J. Photogramm. Remote Sens. 121(C), 28–47 (2016).
[Crossref]

Ioannou, I.

I. Ioannou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, “Deriving ocean color products using neural networks,” Remote Sens. Environ. 134(7), 78–91 (2013).
[Crossref]

I. Ioannou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, “Neural network approach to retrieve the inherent optical properties of the ocean from observations of MODIS,” Appl. Opt. 50(19), 3168–3186 (2011).
[Crossref] [PubMed]

Kahru, M.

J. E. O’Reilly, S. Maritorena, B. G. Mitchell, D. A. Siegel, K. L. Carder, S. A. Garver, M. Kahru, and C. McClain, “Ocean color chlorophyll algorithms for SeaWiFS,” J. Geophys. Res. Oceans 103(C11), 24937–24953 (1998).
[Crossref]

Kamykowski, D.

K. L. Carder, F. R. Chen, Z. P. Lee, S. K. Hawes, and D. Kamykowski, “Semianalytic Moderate-Resolution Imaging Spectrometer Algorithms for Chlorophyll A and Absorption with Bio-Optical Domains Based on Nitrate-Depletion Temperatures,” J. Geophys. Res. D Atmospheres 104(C3), 5403–5421 (1999).
[Crossref]

Kindle, J.

Z. P. Lee, A. Weidemann, and J. Kindle, “Euphotic zone depth: Its derivation and implication to ocean-color remote sensing,” J. Geophys. Res. Oceans 112(C3), 1–12 (2007).

Lazzara, L.

L. Lazzara, A. Bricaud, and H. Claustre, “Spectral absorption and fluorescence excitation properties of phytoplanktonic populations at a mesotrophic and an oligotrophic site in the tropical North Atlantic (EUMELI program),” Deep Sea Res. Part I Oceanogr. Res. Pap. 43(8), 1215–1240 (1996).
[Crossref]

Lee, Z.

Lee, Z. P.

Z. P. Lee, A. Weidemann, and J. Kindle, “Euphotic zone depth: Its derivation and implication to ocean-color remote sensing,” J. Geophys. Res. Oceans 112(C3), 1–12 (2007).

K. L. Carder, F. R. Chen, Z. P. Lee, S. K. Hawes, and D. Kamykowski, “Semianalytic Moderate-Resolution Imaging Spectrometer Algorithms for Chlorophyll A and Absorption with Bio-Optical Domains Based on Nitrate-Depletion Temperatures,” J. Geophys. Res. D Atmospheres 104(C3), 5403–5421 (1999).
[Crossref]

Li, H.

H. Li, X. He, Y. Bai, X. Y. Chen, F. Gong, Q. K. Zhu, and Z. F. Hu, “Assessment of satellite-based chlorophyll-a retrieval algorithms for high sun zenith angle conditions,” J. Appl. Remote Sens. 11(1), 012004 (2017).
[Crossref]

H. Li, X. He, J. Ding, Z. F. Hu, W. S. Cui, S. D. Li, and L. Zhang, “Validation of the Remote Sensing Products Retrieved by Geostationary Ocean Color Imager in Liaodong Bay in Spring,” Acta Opt. Sin. 36(4), 0401002 (2016).
[Crossref]

Li, S. D.

H. Li, X. He, J. Ding, Z. F. Hu, W. S. Cui, S. D. Li, and L. Zhang, “Validation of the Remote Sensing Products Retrieved by Geostationary Ocean Color Imager in Liaodong Bay in Spring,” Acta Opt. Sin. 36(4), 0401002 (2016).
[Crossref]

Li, W

X He, K Stamnes, Y Bai, W Li, and D Wang, “Effects of Earth curvature on atmospheric correction for ocean color remote sensing,” Remote Sensing of Environment.  209,118–133. (2018)

Li, W.

Y. Fan, W. Li, K. J. Voss, C. K. Gatebe, and K. Stamnes, “A neural network method to correct bidirectional effects in water-leaving radiance,” AIP Conference Procedings 1810(120001), 12001 (2017).
[Crossref]

Liu, Z. S.

T. Zhang, F. Fell, and Z. S. Liu, “Evaluating the performance of artificial neural network techniques for pigment retrieval from ocean color in Case I waters,” J. Geophys. Res. D Atmospheres 108(C9), 1–12 (2003).
[Crossref]

Maritorena, S.

S. Maritorena, D. A. Siegel, and A. R. Peterson, “Optimization of a semianalytical ocean color model for global-scale applications,” Appl. Opt. 41(15), 2705–2714 (2002).
[Crossref] [PubMed]

A. Morel and S. Maritorena, “Bio-optical properties of oceanic waters: A reappraisal,” J. Geophys. Res. Oceans 106(C4), 7163–7180 (2001).
[Crossref]

J. E. O’Reilly, S. Maritorena, B. G. Mitchell, D. A. Siegel, K. L. Carder, S. A. Garver, M. Kahru, and C. McClain, “Ocean color chlorophyll algorithms for SeaWiFS,” J. Geophys. Res. Oceans 103(C11), 24937–24953 (1998).
[Crossref]

Marullo, S.

G. Volpe, R. Santoleri, V. Vellucci, M. Ribera d’Alcalà, S. Marullo, and F. D’Ortenzio, “The colour of the Mediterranean Sea: Global versus regional bio-optical algorithms evaluation and implication for satellite chlorophyll estimates,” Remote Sens. Environ. 107(4), 625–638 (2007).
[Crossref]

McClain, C.

J. E. O’Reilly, S. Maritorena, B. G. Mitchell, D. A. Siegel, K. L. Carder, S. A. Garver, M. Kahru, and C. McClain, “Ocean color chlorophyll algorithms for SeaWiFS,” J. Geophys. Res. Oceans 103(C11), 24937–24953 (1998).
[Crossref]

Mishra, D. R.

F. Watanabe, D. R. Mishra, I. Astuti, T. Rodrigues, E. Alcântara, N. N. Imai, and C. Barbosa, “Parametrization and calibration of a quasi-analytical algorithm for tropical eutrophic waters,” ISPRS J. Photogramm. Remote Sens. 121(C), 28–47 (2016).
[Crossref]

Mitchell, B. G.

J. E. O’Reilly, S. Maritorena, B. G. Mitchell, D. A. Siegel, K. L. Carder, S. A. Garver, M. Kahru, and C. McClain, “Ocean color chlorophyll algorithms for SeaWiFS,” J. Geophys. Res. Oceans 103(C11), 24937–24953 (1998).
[Crossref]

K. L. Carder, S. K. Hawes, K. A. Baker, R. C. Smith, R. G. Steward, and B. G. Mitchell, “Reflectance model for quantifying chlorophyll a in the presence of productivity degradation products,” J. Geophys. Res. Oceans 96(C11), 20599–20611 (1991).
[Crossref]

Miyazawa, Y.

Z. Hu, D. P. Wang, D. Pan, X. He, Y. Miyazawa, Y. Bai, D. Wang, and F. Gong, “Mapping surface tidal currents and Changjiang plume in the East China Sea from Geostationary Ocean Color Imager,” J. Geophys. Res. Oceans 121(3), 1563–1572 (2016).
[Crossref]

Moon, J. E.

Y. H. Ahn, P. Shanmugam, J. E. Moon, and J. H. Ryu, “Satellite remote sensing of a low-salinity water plume in the East China Sea,” Ann. Geophys. 26(7), 2019–2035 (2008).
[Crossref]

Morel, A.

Moshary, F.

I. Ioannou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, “Deriving ocean color products using neural networks,” Remote Sens. Environ. 134(7), 78–91 (2013).
[Crossref]

I. Ioannou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, “Neural network approach to retrieve the inherent optical properties of the ocean from observations of MODIS,” Appl. Opt. 50(19), 3168–3186 (2011).
[Crossref] [PubMed]

Neeley, A. R.

J. E. Chaves, P. J. Werdell, C. W. Proctor, A. R. Neeley, S. A. Freeman, C. S. Thomas, and S. B. Hooker, “Assessment of ocean color data records from MODIS-Aqua in the western Arctic Ocean,” Deep Sea Res. Part II Top. Stud. Oceanogr. 118, 32–43 (2015).
[Crossref]

O’Reilly, J. E.

J. E. O’Reilly, S. Maritorena, B. G. Mitchell, D. A. Siegel, K. L. Carder, S. A. Garver, M. Kahru, and C. McClain, “Ocean color chlorophyll algorithms for SeaWiFS,” J. Geophys. Res. Oceans 103(C11), 24937–24953 (1998).
[Crossref]

Pahlevan, N.

Pan, D.

Z. Hu, D. P. Wang, D. Pan, X. He, Y. Miyazawa, Y. Bai, D. Wang, and F. Gong, “Mapping surface tidal currents and Changjiang plume in the East China Sea from Geostationary Ocean Color Imager,” J. Geophys. Res. Oceans 121(3), 1563–1572 (2016).
[Crossref]

X. He, D. Pan, Y. Bai, D. Wang, and Z. Hao, “A new simple concept for ocean colour remote sensing using parallel polarisation radiance,” Sci. Rep. 4(6168), 3748 (2014).
[PubMed]

X. He, Y. Bai, D. Pan, N. Huang, X. Dong, J. Chen, C.-T. A. Chen, and Q. Cui, “Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters,” Remote Sens. Environ. 133(12), 225–239 (2013).
[Crossref]

Park, Y. J.

J. K. Choi, Y. J. Park, and J. H. Ahn, “GOCI, the world’s first geostationary ocean color observation satellite, for the monitoring of temporal variability in coastal water turbidity,” J. Geophys. Res. Oceans 117(C9), 1–14 (2012).

Park, Y.-J.

J. H. Ryu, H. J. Han, S. Cho, Y.-J. Park, and Y.-H. Ahn, “Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS),” Ocean Science Journal. 47(3), 223–233 (2012).
[Crossref]

Peterson, A. R.

Proctor, C. W.

J. E. Chaves, P. J. Werdell, C. W. Proctor, A. R. Neeley, S. A. Freeman, C. S. Thomas, and S. B. Hooker, “Assessment of ocean color data records from MODIS-Aqua in the western Arctic Ocean,” Deep Sea Res. Part II Top. Stud. Oceanogr. 118, 32–43 (2015).
[Crossref]

Ribera d’Alcalà, M.

G. Volpe, R. Santoleri, V. Vellucci, M. Ribera d’Alcalà, S. Marullo, and F. D’Ortenzio, “The colour of the Mediterranean Sea: Global versus regional bio-optical algorithms evaluation and implication for satellite chlorophyll estimates,” Remote Sens. Environ. 107(4), 625–638 (2007).
[Crossref]

Rodrigues, T.

F. Watanabe, D. R. Mishra, I. Astuti, T. Rodrigues, E. Alcântara, N. N. Imai, and C. Barbosa, “Parametrization and calibration of a quasi-analytical algorithm for tropical eutrophic waters,” ISPRS J. Photogramm. Remote Sens. 121(C), 28–47 (2016).
[Crossref]

Ryu, J. H.

J. H. Ryu, H. J. Han, S. Cho, Y.-J. Park, and Y.-H. Ahn, “Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS),” Ocean Science Journal. 47(3), 223–233 (2012).
[Crossref]

Y. H. Ahn, P. Shanmugam, J. E. Moon, and J. H. Ryu, “Satellite remote sensing of a low-salinity water plume in the East China Sea,” Ann. Geophys. 26(7), 2019–2035 (2008).
[Crossref]

Santoleri, R.

G. Volpe, R. Santoleri, V. Vellucci, M. Ribera d’Alcalà, S. Marullo, and F. D’Ortenzio, “The colour of the Mediterranean Sea: Global versus regional bio-optical algorithms evaluation and implication for satellite chlorophyll estimates,” Remote Sens. Environ. 107(4), 625–638 (2007).
[Crossref]

Schott, J. R.

Shanmugam, P.

S. Vadakke-Chanat and P. Shanmugam, “Modelling the contributions of phytoplankton and non-algal particles to spectral scattering properties in near-shore and lagoon waters,” Cont. Shelf Res. 135, 35–46 (2017).
[Crossref]

S. Vadakke-Chanat, P. Shanmugam, and Y. H. Ahn, “A Model for Deriving the Spectral Backscattering Properties of Particles in Inland and Marine Waters From In Situ and Remote Sensing Data,” IEEE Trans. Geosci. Remote Sens. 55(3), 1461–1476 (2017).
[Crossref]

R. K. Singh and P. Shanmugam, “A novel method for estimation of aerosol radiance and its extrapolation in the atmospheric correction of satellite data over optically complex oceanic waters,” Remote Sens. Environ. 142(1), 188–206 (2014).
[Crossref]

Y. H. Ahn, P. Shanmugam, J. E. Moon, and J. H. Ryu, “Satellite remote sensing of a low-salinity water plume in the East China Sea,” Ann. Geophys. 26(7), 2019–2035 (2008).
[Crossref]

Siegel, D. A.

S. Maritorena, D. A. Siegel, and A. R. Peterson, “Optimization of a semianalytical ocean color model for global-scale applications,” Appl. Opt. 41(15), 2705–2714 (2002).
[Crossref] [PubMed]

J. E. O’Reilly, S. Maritorena, B. G. Mitchell, D. A. Siegel, K. L. Carder, S. A. Garver, M. Kahru, and C. McClain, “Ocean color chlorophyll algorithms for SeaWiFS,” J. Geophys. Res. Oceans 103(C11), 24937–24953 (1998).
[Crossref]

Singh, R. K.

R. K. Singh and P. Shanmugam, “A novel method for estimation of aerosol radiance and its extrapolation in the atmospheric correction of satellite data over optically complex oceanic waters,” Remote Sens. Environ. 142(1), 188–206 (2014).
[Crossref]

Smith, R. C.

K. L. Carder, S. K. Hawes, K. A. Baker, R. C. Smith, R. G. Steward, and B. G. Mitchell, “Reflectance model for quantifying chlorophyll a in the presence of productivity degradation products,” J. Geophys. Res. Oceans 96(C11), 20599–20611 (1991).
[Crossref]

H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, and D. K. Clark, “A semianalytic radiance model of ocean color,” J. Geophys. Res. D Atmospheres 93(D9), 10909–10924 (1988).
[Crossref]

Stamnes, K

X He, K Stamnes, Y Bai, W Li, and D Wang, “Effects of Earth curvature on atmospheric correction for ocean color remote sensing,” Remote Sensing of Environment.  209,118–133. (2018)

Stamnes, K.

Y. Fan, W. Li, K. J. Voss, C. K. Gatebe, and K. Stamnes, “A neural network method to correct bidirectional effects in water-leaving radiance,” AIP Conference Procedings 1810(120001), 12001 (2017).
[Crossref]

Steward, R. G.

K. L. Carder, S. K. Hawes, K. A. Baker, R. C. Smith, R. G. Steward, and B. G. Mitchell, “Reflectance model for quantifying chlorophyll a in the presence of productivity degradation products,” J. Geophys. Res. Oceans 96(C11), 20599–20611 (1991).
[Crossref]

Sun, L.

L. Sun, X. Wang, M. Guo, and J.W Tang, “MODIS ocean color product validation around the Yellow Sea and East China Sea,” Hupo Kexue 21(2), 298–306 (2009).
[Crossref]

Tang, J.W

L. Sun, X. Wang, M. Guo, and J.W Tang, “MODIS ocean color product validation around the Yellow Sea and East China Sea,” Hupo Kexue 21(2), 298–306 (2009).
[Crossref]

Tassan, S.

Thiria, S.

L. Gross, S. Thiria, and R. Frouin, “Applying artificial neural network methodology to ocean color remote sensing,” Ecol. Modell. 120(2–3), 237–246 (1999).
[Crossref]

Thomas, C. S.

J. E. Chaves, P. J. Werdell, C. W. Proctor, A. R. Neeley, S. A. Freeman, C. S. Thomas, and S. B. Hooker, “Assessment of ocean color data records from MODIS-Aqua in the western Arctic Ocean,” Deep Sea Res. Part II Top. Stud. Oceanogr. 118, 32–43 (2015).
[Crossref]

Vadakke-Chanat, S.

S. Vadakke-Chanat and P. Shanmugam, “Modelling the contributions of phytoplankton and non-algal particles to spectral scattering properties in near-shore and lagoon waters,” Cont. Shelf Res. 135, 35–46 (2017).
[Crossref]

S. Vadakke-Chanat, P. Shanmugam, and Y. H. Ahn, “A Model for Deriving the Spectral Backscattering Properties of Particles in Inland and Marine Waters From In Situ and Remote Sensing Data,” IEEE Trans. Geosci. Remote Sens. 55(3), 1461–1476 (2017).
[Crossref]

Vellucci, V.

G. Volpe, R. Santoleri, V. Vellucci, M. Ribera d’Alcalà, S. Marullo, and F. D’Ortenzio, “The colour of the Mediterranean Sea: Global versus regional bio-optical algorithms evaluation and implication for satellite chlorophyll estimates,” Remote Sens. Environ. 107(4), 625–638 (2007).
[Crossref]

Volpe, G.

G. Volpe, R. Santoleri, V. Vellucci, M. Ribera d’Alcalà, S. Marullo, and F. D’Ortenzio, “The colour of the Mediterranean Sea: Global versus regional bio-optical algorithms evaluation and implication for satellite chlorophyll estimates,” Remote Sens. Environ. 107(4), 625–638 (2007).
[Crossref]

Voss, K. J.

Y. Fan, W. Li, K. J. Voss, C. K. Gatebe, and K. Stamnes, “A neural network method to correct bidirectional effects in water-leaving radiance,” AIP Conference Procedings 1810(120001), 12001 (2017).
[Crossref]

Wang, D

X He, K Stamnes, Y Bai, W Li, and D Wang, “Effects of Earth curvature on atmospheric correction for ocean color remote sensing,” Remote Sensing of Environment.  209,118–133. (2018)

Wang, D.

Z. Hu, D. P. Wang, D. Pan, X. He, Y. Miyazawa, Y. Bai, D. Wang, and F. Gong, “Mapping surface tidal currents and Changjiang plume in the East China Sea from Geostationary Ocean Color Imager,” J. Geophys. Res. Oceans 121(3), 1563–1572 (2016).
[Crossref]

X. He, D. Pan, Y. Bai, D. Wang, and Z. Hao, “A new simple concept for ocean colour remote sensing using parallel polarisation radiance,” Sci. Rep. 4(6168), 3748 (2014).
[PubMed]

Wang, D. P.

Z. Hu, D. P. Wang, D. Pan, X. He, Y. Miyazawa, Y. Bai, D. Wang, and F. Gong, “Mapping surface tidal currents and Changjiang plume in the East China Sea from Geostationary Ocean Color Imager,” J. Geophys. Res. Oceans 121(3), 1563–1572 (2016).
[Crossref]

Wang, X.

L. Sun, X. Wang, M. Guo, and J.W Tang, “MODIS ocean color product validation around the Yellow Sea and East China Sea,” Hupo Kexue 21(2), 298–306 (2009).
[Crossref]

Watanabe, F.

F. Watanabe, D. R. Mishra, I. Astuti, T. Rodrigues, E. Alcântara, N. N. Imai, and C. Barbosa, “Parametrization and calibration of a quasi-analytical algorithm for tropical eutrophic waters,” ISPRS J. Photogramm. Remote Sens. 121(C), 28–47 (2016).
[Crossref]

Weidemann, A.

Z. P. Lee, A. Weidemann, and J. Kindle, “Euphotic zone depth: Its derivation and implication to ocean-color remote sensing,” J. Geophys. Res. Oceans 112(C3), 1–12 (2007).

Werdell, P. J.

J. E. Chaves, P. J. Werdell, C. W. Proctor, A. R. Neeley, S. A. Freeman, C. S. Thomas, and S. B. Hooker, “Assessment of ocean color data records from MODIS-Aqua in the western Arctic Ocean,” Deep Sea Res. Part II Top. Stud. Oceanogr. 118, 32–43 (2015).
[Crossref]

P. J. Werdell and S. W. Bailey, “An improved in-situ bio-optical data set for ocean color algorithm development and satellite data product validation,” Remote Sens. Environ. 98(1), 122–140 (2005).
[Crossref]

Zhang, L.

H. Li, X. He, J. Ding, Z. F. Hu, W. S. Cui, S. D. Li, and L. Zhang, “Validation of the Remote Sensing Products Retrieved by Geostationary Ocean Color Imager in Liaodong Bay in Spring,” Acta Opt. Sin. 36(4), 0401002 (2016).
[Crossref]

Zhang, T.

T. Zhang, F. Fell, and Z. S. Liu, “Evaluating the performance of artificial neural network techniques for pigment retrieval from ocean color in Case I waters,” J. Geophys. Res. D Atmospheres 108(C9), 1–12 (2003).
[Crossref]

Zhu, Q. K.

H. Li, X. He, Y. Bai, X. Y. Chen, F. Gong, Q. K. Zhu, and Z. F. Hu, “Assessment of satellite-based chlorophyll-a retrieval algorithms for high sun zenith angle conditions,” J. Appl. Remote Sens. 11(1), 012004 (2017).
[Crossref]

Acta Opt. Sin. (1)

H. Li, X. He, J. Ding, Z. F. Hu, W. S. Cui, S. D. Li, and L. Zhang, “Validation of the Remote Sensing Products Retrieved by Geostationary Ocean Color Imager in Liaodong Bay in Spring,” Acta Opt. Sin. 36(4), 0401002 (2016).
[Crossref]

AIP Conference Procedings (1)

Y. Fan, W. Li, K. J. Voss, C. K. Gatebe, and K. Stamnes, “A neural network method to correct bidirectional effects in water-leaving radiance,” AIP Conference Procedings 1810(120001), 12001 (2017).
[Crossref]

Ann. Geophys. (1)

Y. H. Ahn, P. Shanmugam, J. E. Moon, and J. H. Ryu, “Satellite remote sensing of a low-salinity water plume in the East China Sea,” Ann. Geophys. 26(7), 2019–2035 (2008).
[Crossref]

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A. Morel, D. Antoine, and B. Gentili, “Bidirectional reflectance of oceanic waters: accounting for Raman emission and varying particle scattering phase function,” Appl. Opt. 41(30), 6289–6306 (2002).
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I. Ioannou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, “Neural network approach to retrieve the inherent optical properties of the ocean from observations of MODIS,” Appl. Opt. 50(19), 3168–3186 (2011).
[Crossref] [PubMed]

N. Pahlevan, Z. Lee, C. Hu, and J. R. Schott, “Diurnal remote sensing of coastal/oceanic waters: a radiometric analysis for Geostationary Coastal and Air Pollution Events,” Appl. Opt. 53(4), 648–665 (2014).
[Crossref] [PubMed]

Cont. Shelf Res. (1)

S. Vadakke-Chanat and P. Shanmugam, “Modelling the contributions of phytoplankton and non-algal particles to spectral scattering properties in near-shore and lagoon waters,” Cont. Shelf Res. 135, 35–46 (2017).
[Crossref]

Deep Sea Res. Part I Oceanogr. Res. Pap. (1)

L. Lazzara, A. Bricaud, and H. Claustre, “Spectral absorption and fluorescence excitation properties of phytoplanktonic populations at a mesotrophic and an oligotrophic site in the tropical North Atlantic (EUMELI program),” Deep Sea Res. Part I Oceanogr. Res. Pap. 43(8), 1215–1240 (1996).
[Crossref]

Deep Sea Res. Part II Top. Stud. Oceanogr. (1)

J. E. Chaves, P. J. Werdell, C. W. Proctor, A. R. Neeley, S. A. Freeman, C. S. Thomas, and S. B. Hooker, “Assessment of ocean color data records from MODIS-Aqua in the western Arctic Ocean,” Deep Sea Res. Part II Top. Stud. Oceanogr. 118, 32–43 (2015).
[Crossref]

Ecol. Modell. (1)

L. Gross, S. Thiria, and R. Frouin, “Applying artificial neural network methodology to ocean color remote sensing,” Ecol. Modell. 120(2–3), 237–246 (1999).
[Crossref]

Hupo Kexue (1)

L. Sun, X. Wang, M. Guo, and J.W Tang, “MODIS ocean color product validation around the Yellow Sea and East China Sea,” Hupo Kexue 21(2), 298–306 (2009).
[Crossref]

IEEE Trans. Geosci. Remote Sens. (1)

S. Vadakke-Chanat, P. Shanmugam, and Y. H. Ahn, “A Model for Deriving the Spectral Backscattering Properties of Particles in Inland and Marine Waters From In Situ and Remote Sensing Data,” IEEE Trans. Geosci. Remote Sens. 55(3), 1461–1476 (2017).
[Crossref]

ISPRS J. Photogramm. Remote Sens. (1)

F. Watanabe, D. R. Mishra, I. Astuti, T. Rodrigues, E. Alcântara, N. N. Imai, and C. Barbosa, “Parametrization and calibration of a quasi-analytical algorithm for tropical eutrophic waters,” ISPRS J. Photogramm. Remote Sens. 121(C), 28–47 (2016).
[Crossref]

J. Appl. Remote Sens. (1)

H. Li, X. He, Y. Bai, X. Y. Chen, F. Gong, Q. K. Zhu, and Z. F. Hu, “Assessment of satellite-based chlorophyll-a retrieval algorithms for high sun zenith angle conditions,” J. Appl. Remote Sens. 11(1), 012004 (2017).
[Crossref]

J. Geophys. Res. D Atmospheres (3)

K. L. Carder, F. R. Chen, Z. P. Lee, S. K. Hawes, and D. Kamykowski, “Semianalytic Moderate-Resolution Imaging Spectrometer Algorithms for Chlorophyll A and Absorption with Bio-Optical Domains Based on Nitrate-Depletion Temperatures,” J. Geophys. Res. D Atmospheres 104(C3), 5403–5421 (1999).
[Crossref]

T. Zhang, F. Fell, and Z. S. Liu, “Evaluating the performance of artificial neural network techniques for pigment retrieval from ocean color in Case I waters,” J. Geophys. Res. D Atmospheres 108(C9), 1–12 (2003).
[Crossref]

H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, and D. K. Clark, “A semianalytic radiance model of ocean color,” J. Geophys. Res. D Atmospheres 93(D9), 10909–10924 (1988).
[Crossref]

J. Geophys. Res. Oceans (6)

Z. P. Lee, A. Weidemann, and J. Kindle, “Euphotic zone depth: Its derivation and implication to ocean-color remote sensing,” J. Geophys. Res. Oceans 112(C3), 1–12 (2007).

K. L. Carder, S. K. Hawes, K. A. Baker, R. C. Smith, R. G. Steward, and B. G. Mitchell, “Reflectance model for quantifying chlorophyll a in the presence of productivity degradation products,” J. Geophys. Res. Oceans 96(C11), 20599–20611 (1991).
[Crossref]

Z. Hu, D. P. Wang, D. Pan, X. He, Y. Miyazawa, Y. Bai, D. Wang, and F. Gong, “Mapping surface tidal currents and Changjiang plume in the East China Sea from Geostationary Ocean Color Imager,” J. Geophys. Res. Oceans 121(3), 1563–1572 (2016).
[Crossref]

A. Morel and S. Maritorena, “Bio-optical properties of oceanic waters: A reappraisal,” J. Geophys. Res. Oceans 106(C4), 7163–7180 (2001).
[Crossref]

J. E. O’Reilly, S. Maritorena, B. G. Mitchell, D. A. Siegel, K. L. Carder, S. A. Garver, M. Kahru, and C. McClain, “Ocean color chlorophyll algorithms for SeaWiFS,” J. Geophys. Res. Oceans 103(C11), 24937–24953 (1998).
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J. K. Choi, Y. J. Park, and J. H. Ahn, “GOCI, the world’s first geostationary ocean color observation satellite, for the monitoring of temporal variability in coastal water turbidity,” J. Geophys. Res. Oceans 117(C9), 1–14 (2012).

Ocean Science Journal. (1)

J. H. Ryu, H. J. Han, S. Cho, Y.-J. Park, and Y.-H. Ahn, “Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS),” Ocean Science Journal. 47(3), 223–233 (2012).
[Crossref]

Remote Sens. Environ. (5)

G. Volpe, R. Santoleri, V. Vellucci, M. Ribera d’Alcalà, S. Marullo, and F. D’Ortenzio, “The colour of the Mediterranean Sea: Global versus regional bio-optical algorithms evaluation and implication for satellite chlorophyll estimates,” Remote Sens. Environ. 107(4), 625–638 (2007).
[Crossref]

P. J. Werdell and S. W. Bailey, “An improved in-situ bio-optical data set for ocean color algorithm development and satellite data product validation,” Remote Sens. Environ. 98(1), 122–140 (2005).
[Crossref]

R. K. Singh and P. Shanmugam, “A novel method for estimation of aerosol radiance and its extrapolation in the atmospheric correction of satellite data over optically complex oceanic waters,” Remote Sens. Environ. 142(1), 188–206 (2014).
[Crossref]

X. He, Y. Bai, D. Pan, N. Huang, X. Dong, J. Chen, C.-T. A. Chen, and Q. Cui, “Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters,” Remote Sens. Environ. 133(12), 225–239 (2013).
[Crossref]

I. Ioannou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, “Deriving ocean color products using neural networks,” Remote Sens. Environ. 134(7), 78–91 (2013).
[Crossref]

Remote Sensing of Environment (1)

X He, K Stamnes, Y Bai, W Li, and D Wang, “Effects of Earth curvature on atmospheric correction for ocean color remote sensing,” Remote Sensing of Environment.  209,118–133. (2018)

Sci. Rep. (1)

X. He, D. Pan, Y. Bai, D. Wang, and Z. Hao, “A new simple concept for ocean colour remote sensing using parallel polarisation radiance,” Sci. Rep. 4(6168), 3748 (2014).
[PubMed]

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Figures (13)

Fig. 1
Fig. 1 Map showing the sampling stations for the SeaBASS-NOMAD in situ data set. The cruise names are shown along transects and sample stations. The background color represents the bathymetry.
Fig. 2
Fig. 2 Percentage of samples for each sun zenith angle range.
Fig. 3
Fig. 3 Map showing the study region using GOCI data. The red rectangle is the target area.
Fig. 4
Fig. 4 Flowchart showing the implementation and assessment process.
Fig. 5
Fig. 5 Comparison between the retrieved Chla by QAA and GSM01 models and in situ data.
Fig. 6
Fig. 6 Averaged APD values for QAA and GSM01 models under different solar zenith angle ranges.
Fig. 7
Fig. 7 Comparisons of the results of QAA and GSM01 models and in situ Chla for two solar zenith angle regimes (30°–40°; 70°–90°).
Fig. 8
Fig. 8 Comparison of the retrieved u(443 nm) at SZA = 30° and 80°.
Fig. 9
Fig. 9 Comparisons between the retrieved u(443nm) by the NN-algorithm and the “known” u(443nm) values. The inputted Rrs data were the independent simulated data (not used in the NN training process) with different noise levels (ε) from 0% to 30% adding to the simulated Rrs.
Fig. 10
Fig. 10 Comparison of the performances of the retrieved u(443nm) between the NN-algorithm and the traditional conversion method (Eqs. (2)-(3)). The input Rrs are the simulated data set which are not used in the NN training.
Fig. 11
Fig. 11 Comparison between the retrieved u(443nm) by NN-algorithm and in situ u(443nm). The SeaBASS-NOMAD data set consisting of 78 samples was used here.
Fig. 12
Fig. 12 Comparison of the retrieved and in situ Chla for the SeaBASS-NOMAD data set. Top panels represent the results at all SZA conditions, whereas bottom panels represent the results for SZA>70°.
Fig. 13
Fig. 13 Comparison of the GOCI-retrieved hourly Chla by the QAA, GSM01, QAA-NN and GSM01-NN models in the basin of the Sea of Japan on 2 Feb. 2015.

Tables (4)

Tables Icon

Table 1 Statistical results for the QAA and GSM01 models

Tables Icon

Table 2 Comparison of the model performances at two different solar zenith angle regimes (30°-40°;70°-90°)

Tables Icon

Table 3 Comparison of the retrieved u(λ) by NN-algorithm (with 10% noise adding to the Rrs) with the inputted u(λ) at different wavelengths

Tables Icon

Table 4 Comparison of the performance of the retrieved chla between the original models (QAA and GSM01) and the improved models (QAA-NN and GSM01-NN) under high SZA (>70°).

Equations (9)

Equations on this page are rendered with MathJax. Learn more.

cos ( θ s ) = sin ( ϕ ) × cos ( δ ) + cos ( ϕ ) × cos ( δ ) × cos ( h )
L w n ( λ ) = t F 0 ( λ ) n w 2 i = 1 2 g i [ u ( λ ) ] i
u ( λ ) = b b ( λ ) a ( λ ) + b b ( λ )
Chla = D × exp { arc t a n h[ ln ( a ϕ * ( 443 nm ) / ( A × B ) ] / C }
r rs = R rs T + γ Q R rs
L wn = ( 1 ρ ) ( 1 ρ ¯ ) F 0 R n w 2 Q ( 1 r R )
R M S E = i = 1 N ( Y i X i ) 2 N
A P D ( % ) = 100 % × 1 N i = 1 N | Y i X i | X i
R P D ( % ) = 100 % × 1 N i = 1 N Y i X i X i

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