Abstract

Remote sensing of chromophoric dissolved organic matter (CDOM) from satellite measurements for estuaries has been problematic due to optical complexity of estuarine waters and uncertainties in satellite-derived remote sensing reflectance (Rrs, sr−1). Here we demonstrate a hybrid approach to combine empirical and semi-analytical algorithms to derive CDOM absorption coefficient at 443 nm (ag(443), m−1) in a turbid estuary (Tampa Bay) from MODIS Aqua (MODISA) and SeaWiFS measurements. The approach first used a validated empirical algorithm and a modified quasi-analytical algorithm (QAA) to derive chlorophyll-a concentration (Chla, mg m−3) and particulate backscattering coefficient at 443 nm (bbp(443), m−1), respectively, from which phytoplankton pigment and non-algal particulate absorption coefficient at 443 nm (aph(443) and ad(443), m−1) were derived with pre-determined bio-optical relationships. Then, the modified QAA was used to estimate the total absorption coefficient at 443 nm (at(443), m−1). Finally, ag(443) was estimated as (at(443) - aph(443) - ad(443) – aw(443)) where aw(443) is the absorption coefficient of pure water (a constant). Using data collected from 71 field stations and 33 near-concurrent satellite-field matchup data pairs covering a large dynamic range (0.3 – 8 m−1), the approach showed ~23% RMS uncertainties in retrieving ag(443) when in situ Rrs data (N = 71) were used. The same approach applied to satellite Rrs yielded much higher uncertainties of ag(443) (~85%) due to large errors in the satellite-retrieved Rrs(443). When the Rrs(443) was derived from the satellite-retrieved Rrs(550) and then used in the hybrid approach, uncertainties in the retrieved ag(443) reduced to ~30% (N = 33). Application of the approach to MODISA and SeaWiFS data led to a 15-year time series of monthly mean ag(443) distributions in Tampa Bay between 1998 and 2012. This time series showed significant seasonal and annual variations regulated mainly by river discharge. Testing of the approach over another turbid estuary (Chesapeake Bay, the largest estuary in the U.S.) demonstrated the potential (~25% uncertainties for a limited ag(443) range) of using this approach to establish long-term environmental data records (EDRs) of CDOM distributions in other estuaries with similar optical complexity.

© 2013 OSA

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    [CrossRef]

2013

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, C. Kovach, C. J. Anastasiou, J. Zhao, and K. L. Carder, “Inherent and apparent optical properties of the complex estuarine waters of Tampa Bay: what controls light?” Estuar. Coast. Shelf Sci.117, 54–69 (2013a).
[CrossRef]

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, L. Feng, R. Boler, and C. Kovach, “Towards a long-term chlorophyll-a data record in a turbid estuary using MODIS observations,” Prog. Oceanogr.109, 90–103 (2013b).
[CrossRef]

N. C. Tehrani, E. J. D’Sa, C. L. Osburn, T. S. Bianchi, and B. A. Schaeffer, “Chromophoric dissolved organic matter and dissolved organic carbon from Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS) and MERIS Sensors: case Study for the Northern Gulf of Mexico,” Remote Sens.5(3), 1439–1464 (2013).
[CrossRef]

Q. Dong, S. Shang, and Z. Lee, “An algorithm to retrieve absorption coefficient of chromophoric dissolved organic matter from ocean color,” Remote Sens. Environ.128, 259–267 (2013).
[CrossRef]

C. Le, C. Hu, D. English, J. Cannizzaro, and C. Kovach, “Climate-driven chlorophyll-a changes in a turbid estuary: observations from satellites and implications for management’,” Remote Sens. Environ.130, 11–24 (2013c).
[CrossRef]

2012

S. Son and M. Wang, “Water properties in Chesapeake Bay from MODIS-Aqua measurements,” Remote Sens. Environ.123, 163–174 (2012).
[CrossRef]

E. A. Urquhat, B. F. Zaitchik, M. J. Hoffman, S. D. Guikema, and E. F. Geiger, “Remote sensed estimates of surface salinity in the Chesapeake Bay: a statistical approach,” Remote Sens. Environ.123, 522–531 (2012).
[CrossRef]

2011

K. Wolter and M. S. Timlin, “El Niño/Southern Oscillation behavior since 1871 as diagnosed in an extended multivariate ENSO index (MEI.ext),” Int. J. Climatol.31(7), 1074–1087 (2011).
[CrossRef]

W. Zhu, Q. Yu, Y. Tian, R. Chen, and G. B. Gardner, “Estimation of chromophoric dissolved organic matter in the Mississippi and Atchafalaya river plume regions using above-surface hyperspectral remote sensing,” J. Geophys. Res.116(C2), C02011 (2011), doi:.
[CrossRef]

S. P. Tiwari and P. Shanmugam, “An optical model for the remote sensing of coloured dissolved organic matter in coastal/ocean waters,” Estuar. Coast. Shelf Sci.93(4), 396–402 (2011).
[CrossRef]

2010

Z. Chen, C. Hu, F. E. Muller-Karger, and M. E. Luther, “Short-term variability of suspended sediment and phytoplankton in Tampa Bay, Florida: observations from a coastal oceanographic tower and ocean color satellites,” Estuar. Coast. Shelf Sci.89(1), 62–72 (2010).
[CrossRef]

F. Shen, Y. X. Zhou, D. J. Li, W. J. Zhu, and M. S. Salama, “Medium resolution imaging spectrometer (MERIS) estimation of chlorophyll-a concentration in the turbid sediment-laden waters of the Changjiang (Yangtze) Estuary,” Int. J. Remote Sens.31(17-18), 4635–4650 (2010).
[CrossRef]

G. C. Magny, W. Long, C. W. Brown, R. R. Hood, A. Huq, R. Murtugudde, and R. R. Colwell, “Predicting the distribution of Vibrio spp. in the Chesapeake Bay: a vibrio cholera case study,” EcoHealth (2010), doi:.
[CrossRef]

2009

D. Sun, Y. Li, Q. Wang, C. Le, C. Huang, and L. Wang, “Parameterization of water component absorption in an inland eutrophic lake and its seasonal variability: a case study in Lake Taihu,” Int. J. Remote Sens.30(13), 3549–3571 (2009).
[CrossRef]

P. J. Werdell, S. W. Bailey, B. A. Franz, L. W. Harding, G. C. Feldman, and C. R. McClain, “Regional and seasonal variability of chlorophyll-a in Chesapeake Bay as observed by SeaWiFS and MODIS-Aqua,” Remote Sens. Environ.113(6), 1319–1330 (2009).
[CrossRef]

M. Wang, S. Son, and L. W. Harding., “Retrieval of diffuse attenuation coefficient in the Chesapeake Bay and turbid ocean regions for satellite ocean color applications,” J. Geophys. Res.114(C10), C10011 (2009), doi:.
[CrossRef]

C. Le, Y. Li, Y. Zha, D. Sun, and B. Yin, “Validation of a quasi-analytical algorithm for highly turbid eutrophic water of Meiliang Bay in Taihu Lake, China,” IEEE Trans. Geosci. Rem. Sens.8, 2490–2500 (2009).

2008

C. C. Liu and R. L. Miller, “Spectrum matching method for estimating the chlorophyll-a concentration, CDOM ratio, and backscatter fraction from remote sensing of ocean color,” Can. J. Rem. Sens.34(4), 343–355 (2008).
[CrossRef]

A. Mannino, M. E. Russ, and S. B. Hooker, “Algorithm development and validation for satellite-derived distributions of DOC and CDOM in the US Middle Atlantic Bight,” J. Geophys. Res.113(C7), C07051 (2008), doi:.
[CrossRef]

D. G. Bowers and H. L. Brett, “The relationship between CDOM and salinity in estuaries: an analytical and graphical solution,” J. Mar. Syst.73(1-2), 1–7 (2008).
[CrossRef]

2007

Z. Chen, C. Hu, R. N. Conmy, F. E. Muller-Karger, and P. Swarzenski, “Colored dissolved organic matter in Tampa Bay, Florida,” Mar. Chem.104(1-2), 98–109 (2007a).
[CrossRef]

P. G. Coble, “Marine optical biogeochemistry: The chemistry of ocean color,” Chem. Rev.107(2), 402–418 (2007).
[CrossRef] [PubMed]

Z. Chen, F. E. Muller-Karger, and C. Hu, “Remote sensing of water clarity in Tampa Bay,” Remote Sens. Environ.109(2), 249–259 (2007b).
[CrossRef]

Z. Chen, C. Hu, and F. E. Muller-Karger, “Monitoring turbidity in Tampa Bay using MODIS/Aqua 250-m imagery,” Remote Sens. Environ.109(2), 207–220 (2007c).
[CrossRef]

Y. Qin, V. E. Brando, A. G. Dekker, and D. Blondeau-Patissier, “Validity of SeaDAS water constituents retrieval algorithms in Australian tropical coastal waters,” J. Geophys. Res. Lett.34(21), L21603 (2007), doi:.
[CrossRef]

M. Tzortziou, A. Subramanian, J. R. Herman, C. L. Gallegos, P. J. Neale, and L. W. Harding, “Remote sensing reflectance and inherent optical properties in the mid Chesapeake Bay,” Estuar. Coast. Shelf Sci.72(1-2), 16–32 (2007).
[CrossRef]

2006

R. H. Weisberg and L. Zheng, “Circulation of Tampa Bay driven by buoyancy, tides, and winds, as simulated using a finite volume coastal ocean model,” J. Geophys. Res.111(C1), C01005 (2006), doi:.
[CrossRef]

S. W. Bailey and P. J. Werdell, “A multi-sensor approach for the on-orbit validation of ocean color satellite data products,” Remote Sens. Environ.102(1-2), 12–23 (2006).
[CrossRef]

C. A. Stedmon, S. Markager, M. Søndergaard, T. Vang, A. Laubel, N. H. Borch, and A. Windelin, “Dissolved organic matter (DOM) export to a temperate estuary: seasonal variations and implications of land use,” Estuaries Coasts29, 388–400 (2006).

K. Oubelkheir, L. A. Clementson, I. T. Webster, P. W. Ford, A. G. Dekker, L. C. Radke, and P. Daniel, “Using inherent optical properties to investigate biogeochemical dynamic in a tropical macrotidal coastal system,” J. Geophys. Res.111(C7), C07021 (2006), doi:.
[CrossRef]

2005

L. W. Harding, A. Magnuson, and M. E. Mallonee, “Bio-optical and remote sensing observations in Chesapeake Bay,” Estuar. Coast. Shelf Sci.62, 75–94 (2005).
[CrossRef]

J. Udy, M. Gall, B. Longstaff, K. Moore, C. Roelfsema, D. R. Spooner, and S. Albert, “Water quality monitoring: a combined approach to investigate gradients of change in the Great Barrier Reef, Australia,” Mar. Pollut. Bull.51(1-4), 224–238 (2005).
[CrossRef] [PubMed]

S. Maritorena and D. A. Siegel, “Consistent merging of satellite ocean color data sets using a bio-optical model,” Remote Sens. Environ.94, 429–440 (2005).
[CrossRef]

D. Doxaran, R. C. N. Cherukuru, and S. J. Lavender, “Use of reflectance band ratios to estimate suspended and dissolved matter concentrations in estuarine waters,” Int. J. Remote Sens.26(8), 1763–1769 (2005).
[CrossRef]

P. Kowalczuk, L. Olszewski, M. Darecki, and S. Kaczmarek, “Empirical relationships between coloured dissolved organic matter (CDOM) absorption and apparent optical properties in Baltic Sea waters,” Int. J. Remote Sens.26(2), 345–370 (2005).
[CrossRef]

L. W. Harding, A. Magnuson, and M. E. Mallonee, “SeaWiFS retrievals of chlorophyll in Chesapeake Bay and the mid-Atlantic bight,” Estuar. Coast. Shelf Sci.62(1-2), 75–94 (2005b).
[CrossRef]

2004

W. W. Gregg and N. W. Casey, “Global and regional evaluation of the SeaWiFS chlorophyll dataset,” Remote Sens. Environ.93(4), 463–479 (2004).
[CrossRef]

C. Hu, Z. Chen, T. D. Clayton, P. Swarzenski, J. C. Brock, and F. E. Muller-Karger, “Assessment of estuarine water-quality indicators using MODIS medium-resolution bands: initial results from Tampa Bay, FL,” Remote Sens. Environ.93(3), 423–441 (2004).
[CrossRef] [PubMed]

2003

V. R. Louis, E. Russek-Cohen, N. Choopun, I. N. G. Rivera, B. Gangle, S. C. Jiang, A. Rubin, J. A. Patz, A. Huq, and R. R. Colwell, “Predictability of Vibrio cholerae in Chesapeake Bay,” Appl. Environ. Microbiol.69(5), 2773–2785 (2003).
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E. J. D’Sa and R. L. Miller, “Bio-optical properties in waters influenced by the Mississippi River during low flow conditions,” Remote Sens. Environ.84(4), 538–549 (2003).
[CrossRef]

2002

D. A. Siegel, S. Maritorena, N. B. Nelson, D. A. Hansell, and M. Lorenzi-Kayser, “Global distribution and dynamics of colored dissolved and detrital organic materials,” J. Geophys. Res. 107, 3228, DOI:. (2002).
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Z. P. 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).
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2001

J. E. Cloern, “Our evolving conceptual model of the coastal eutrophication problem,” Mar. Ecol. Prog. Ser.210, 223–253 (2001).
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N. Schmidt, E. K. Lipp, J. B. Rose, and M. E. Luther, “ENSO influences on Seasonal Rainfall and River Discharger in Florida,” J. Clim.14(4), 615–628 (2001).
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C. Hu, K. L. Carder, and F. E. Muller-Karger, “How precise are SeaWiFS ocean color estimates? Implications of digitization-noise errors,” Remote Sens. Environ.76(2), 239–249 (2001).
[CrossRef]

1999

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.104(C3), 5403–5421 (1999).
[CrossRef]

1998

G. M. Ferrari and M. D. Dowell, “CDOM absorption characteristics with relation to fluorescence and salinity in coastal areas of the Southern Baltic Sea,” Estuar. Coast. Shelf Sci.47(1), 91–105 (1998).
[CrossRef]

H. Gao and R. G. Zepp, “Factors influencing photoreactions of dissolved organic matter in a coastal river of the southeastern United States,” Environ. Sci. Technol.32(19), 2940–2946 (1998).
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N. B. Nelson, D. A. Siegel, and A. F. Michaels, “Seasonal dynamics of colored dissolved material in the Sargasso Sea,” Deep Sea Res. Part I Oceanogr. Res. Pap.45(6), 931–957 (1998).
[CrossRef]

1997

1996

1985

J. Fischer, “On the information content of multispectral radiance measurements over an ocean,” Int. J. Remote Sens.6(5), 773–786 (1985).
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Albert, S.

J. Udy, M. Gall, B. Longstaff, K. Moore, C. Roelfsema, D. R. Spooner, and S. Albert, “Water quality monitoring: a combined approach to investigate gradients of change in the Great Barrier Reef, Australia,” Mar. Pollut. Bull.51(1-4), 224–238 (2005).
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Anastasiou, C. J.

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, C. Kovach, C. J. Anastasiou, J. Zhao, and K. L. Carder, “Inherent and apparent optical properties of the complex estuarine waters of Tampa Bay: what controls light?” Estuar. Coast. Shelf Sci.117, 54–69 (2013a).
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Arnone, R. A.

Bailey, S. W.

P. J. Werdell, S. W. Bailey, B. A. Franz, L. W. Harding, G. C. Feldman, and C. R. McClain, “Regional and seasonal variability of chlorophyll-a in Chesapeake Bay as observed by SeaWiFS and MODIS-Aqua,” Remote Sens. Environ.113(6), 1319–1330 (2009).
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S. W. Bailey and P. J. Werdell, “A multi-sensor approach for the on-orbit validation of ocean color satellite data products,” Remote Sens. Environ.102(1-2), 12–23 (2006).
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Bianchi, T. S.

N. C. Tehrani, E. J. D’Sa, C. L. Osburn, T. S. Bianchi, and B. A. Schaeffer, “Chromophoric dissolved organic matter and dissolved organic carbon from Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS) and MERIS Sensors: case Study for the Northern Gulf of Mexico,” Remote Sens.5(3), 1439–1464 (2013).
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Blondeau-Patissier, D.

Y. Qin, V. E. Brando, A. G. Dekker, and D. Blondeau-Patissier, “Validity of SeaDAS water constituents retrieval algorithms in Australian tropical coastal waters,” J. Geophys. Res. Lett.34(21), L21603 (2007), doi:.
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Boler, R.

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, L. Feng, R. Boler, and C. Kovach, “Towards a long-term chlorophyll-a data record in a turbid estuary using MODIS observations,” Prog. Oceanogr.109, 90–103 (2013b).
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Borch, N. H.

C. A. Stedmon, S. Markager, M. Søndergaard, T. Vang, A. Laubel, N. H. Borch, and A. Windelin, “Dissolved organic matter (DOM) export to a temperate estuary: seasonal variations and implications of land use,” Estuaries Coasts29, 388–400 (2006).

Bowers, D. G.

D. G. Bowers and H. L. Brett, “The relationship between CDOM and salinity in estuaries: an analytical and graphical solution,” J. Mar. Syst.73(1-2), 1–7 (2008).
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Brando, V. E.

Y. Qin, V. E. Brando, A. G. Dekker, and D. Blondeau-Patissier, “Validity of SeaDAS water constituents retrieval algorithms in Australian tropical coastal waters,” J. Geophys. Res. Lett.34(21), L21603 (2007), doi:.
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Brett, H. L.

D. G. Bowers and H. L. Brett, “The relationship between CDOM and salinity in estuaries: an analytical and graphical solution,” J. Mar. Syst.73(1-2), 1–7 (2008).
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Brock, J. C.

C. Hu, Z. Chen, T. D. Clayton, P. Swarzenski, J. C. Brock, and F. E. Muller-Karger, “Assessment of estuarine water-quality indicators using MODIS medium-resolution bands: initial results from Tampa Bay, FL,” Remote Sens. Environ.93(3), 423–441 (2004).
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Brown, C. W.

G. C. Magny, W. Long, C. W. Brown, R. R. Hood, A. Huq, R. Murtugudde, and R. R. Colwell, “Predicting the distribution of Vibrio spp. in the Chesapeake Bay: a vibrio cholera case study,” EcoHealth (2010), doi:.
[CrossRef]

Cannizzaro, J.

C. Le, C. Hu, D. English, J. Cannizzaro, and C. Kovach, “Climate-driven chlorophyll-a changes in a turbid estuary: observations from satellites and implications for management’,” Remote Sens. Environ.130, 11–24 (2013c).
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C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, C. Kovach, C. J. Anastasiou, J. Zhao, and K. L. Carder, “Inherent and apparent optical properties of the complex estuarine waters of Tampa Bay: what controls light?” Estuar. Coast. Shelf Sci.117, 54–69 (2013a).
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C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, L. Feng, R. Boler, and C. Kovach, “Towards a long-term chlorophyll-a data record in a turbid estuary using MODIS observations,” Prog. Oceanogr.109, 90–103 (2013b).
[CrossRef]

Carder, K. L.

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, C. Kovach, C. J. Anastasiou, J. Zhao, and K. L. Carder, “Inherent and apparent optical properties of the complex estuarine waters of Tampa Bay: what controls light?” Estuar. Coast. Shelf Sci.117, 54–69 (2013a).
[CrossRef]

Z. P. 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]

C. Hu, K. L. Carder, and F. E. Muller-Karger, “How precise are SeaWiFS ocean color estimates? Implications of digitization-noise errors,” Remote Sens. Environ.76(2), 239–249 (2001).
[CrossRef]

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.104(C3), 5403–5421 (1999).
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Z. P. Lee, K. L. Carder, T. G. Peacock, C. O. Davis, and J. L. Mueller, “Method to derive ocean absorption coefficients from remote-sensing reflectance,” Appl. Opt.35(3), 453–462 (1996).
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W. W. Gregg and N. W. Casey, “Global and regional evaluation of the SeaWiFS chlorophyll dataset,” Remote Sens. Environ.93(4), 463–479 (2004).
[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.104(C3), 5403–5421 (1999).
[CrossRef]

Chen, R.

W. Zhu, Q. Yu, Y. Tian, R. Chen, and G. B. Gardner, “Estimation of chromophoric dissolved organic matter in the Mississippi and Atchafalaya river plume regions using above-surface hyperspectral remote sensing,” J. Geophys. Res.116(C2), C02011 (2011), doi:.
[CrossRef]

Chen, Z.

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, L. Feng, R. Boler, and C. Kovach, “Towards a long-term chlorophyll-a data record in a turbid estuary using MODIS observations,” Prog. Oceanogr.109, 90–103 (2013b).
[CrossRef]

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, C. Kovach, C. J. Anastasiou, J. Zhao, and K. L. Carder, “Inherent and apparent optical properties of the complex estuarine waters of Tampa Bay: what controls light?” Estuar. Coast. Shelf Sci.117, 54–69 (2013a).
[CrossRef]

Z. Chen, C. Hu, F. E. Muller-Karger, and M. E. Luther, “Short-term variability of suspended sediment and phytoplankton in Tampa Bay, Florida: observations from a coastal oceanographic tower and ocean color satellites,” Estuar. Coast. Shelf Sci.89(1), 62–72 (2010).
[CrossRef]

Z. Chen, F. E. Muller-Karger, and C. Hu, “Remote sensing of water clarity in Tampa Bay,” Remote Sens. Environ.109(2), 249–259 (2007b).
[CrossRef]

Z. Chen, C. Hu, R. N. Conmy, F. E. Muller-Karger, and P. Swarzenski, “Colored dissolved organic matter in Tampa Bay, Florida,” Mar. Chem.104(1-2), 98–109 (2007a).
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Z. Chen, C. Hu, and F. E. Muller-Karger, “Monitoring turbidity in Tampa Bay using MODIS/Aqua 250-m imagery,” Remote Sens. Environ.109(2), 207–220 (2007c).
[CrossRef]

C. Hu, Z. Chen, T. D. Clayton, P. Swarzenski, J. C. Brock, and F. E. Muller-Karger, “Assessment of estuarine water-quality indicators using MODIS medium-resolution bands: initial results from Tampa Bay, FL,” Remote Sens. Environ.93(3), 423–441 (2004).
[CrossRef] [PubMed]

Cherukuru, R. C. N.

D. Doxaran, R. C. N. Cherukuru, and S. J. Lavender, “Use of reflectance band ratios to estimate suspended and dissolved matter concentrations in estuarine waters,” Int. J. Remote Sens.26(8), 1763–1769 (2005).
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Choopun, N.

V. R. Louis, E. Russek-Cohen, N. Choopun, I. N. G. Rivera, B. Gangle, S. C. Jiang, A. Rubin, J. A. Patz, A. Huq, and R. R. Colwell, “Predictability of Vibrio cholerae in Chesapeake Bay,” Appl. Environ. Microbiol.69(5), 2773–2785 (2003).
[CrossRef] [PubMed]

Clayton, T. D.

C. Hu, Z. Chen, T. D. Clayton, P. Swarzenski, J. C. Brock, and F. E. Muller-Karger, “Assessment of estuarine water-quality indicators using MODIS medium-resolution bands: initial results from Tampa Bay, FL,” Remote Sens. Environ.93(3), 423–441 (2004).
[CrossRef] [PubMed]

Clementson, L. A.

K. Oubelkheir, L. A. Clementson, I. T. Webster, P. W. Ford, A. G. Dekker, L. C. Radke, and P. Daniel, “Using inherent optical properties to investigate biogeochemical dynamic in a tropical macrotidal coastal system,” J. Geophys. Res.111(C7), C07021 (2006), doi:.
[CrossRef]

Cloern, J. E.

J. E. Cloern, “Our evolving conceptual model of the coastal eutrophication problem,” Mar. Ecol. Prog. Ser.210, 223–253 (2001).
[CrossRef]

Coble, P. G.

P. G. Coble, “Marine optical biogeochemistry: The chemistry of ocean color,” Chem. Rev.107(2), 402–418 (2007).
[CrossRef] [PubMed]

Colwell, R. R.

G. C. Magny, W. Long, C. W. Brown, R. R. Hood, A. Huq, R. Murtugudde, and R. R. Colwell, “Predicting the distribution of Vibrio spp. in the Chesapeake Bay: a vibrio cholera case study,” EcoHealth (2010), doi:.
[CrossRef]

V. R. Louis, E. Russek-Cohen, N. Choopun, I. N. G. Rivera, B. Gangle, S. C. Jiang, A. Rubin, J. A. Patz, A. Huq, and R. R. Colwell, “Predictability of Vibrio cholerae in Chesapeake Bay,” Appl. Environ. Microbiol.69(5), 2773–2785 (2003).
[CrossRef] [PubMed]

Conmy, R. N.

Z. Chen, C. Hu, R. N. Conmy, F. E. Muller-Karger, and P. Swarzenski, “Colored dissolved organic matter in Tampa Bay, Florida,” Mar. Chem.104(1-2), 98–109 (2007a).
[CrossRef]

D’Sa, E. J.

N. C. Tehrani, E. J. D’Sa, C. L. Osburn, T. S. Bianchi, and B. A. Schaeffer, “Chromophoric dissolved organic matter and dissolved organic carbon from Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS) and MERIS Sensors: case Study for the Northern Gulf of Mexico,” Remote Sens.5(3), 1439–1464 (2013).
[CrossRef]

E. J. D’Sa and R. L. Miller, “Bio-optical properties in waters influenced by the Mississippi River during low flow conditions,” Remote Sens. Environ.84(4), 538–549 (2003).
[CrossRef]

Daniel, P.

K. Oubelkheir, L. A. Clementson, I. T. Webster, P. W. Ford, A. G. Dekker, L. C. Radke, and P. Daniel, “Using inherent optical properties to investigate biogeochemical dynamic in a tropical macrotidal coastal system,” J. Geophys. Res.111(C7), C07021 (2006), doi:.
[CrossRef]

Darecki, M.

P. Kowalczuk, L. Olszewski, M. Darecki, and S. Kaczmarek, “Empirical relationships between coloured dissolved organic matter (CDOM) absorption and apparent optical properties in Baltic Sea waters,” Int. J. Remote Sens.26(2), 345–370 (2005).
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Davis, C. O.

Dekker, A. G.

Y. Qin, V. E. Brando, A. G. Dekker, and D. Blondeau-Patissier, “Validity of SeaDAS water constituents retrieval algorithms in Australian tropical coastal waters,” J. Geophys. Res. Lett.34(21), L21603 (2007), doi:.
[CrossRef]

K. Oubelkheir, L. A. Clementson, I. T. Webster, P. W. Ford, A. G. Dekker, L. C. Radke, and P. Daniel, “Using inherent optical properties to investigate biogeochemical dynamic in a tropical macrotidal coastal system,” J. Geophys. Res.111(C7), C07021 (2006), doi:.
[CrossRef]

Dong, Q.

Q. Dong, S. Shang, and Z. Lee, “An algorithm to retrieve absorption coefficient of chromophoric dissolved organic matter from ocean color,” Remote Sens. Environ.128, 259–267 (2013).
[CrossRef]

Dowell, M. D.

G. M. Ferrari and M. D. Dowell, “CDOM absorption characteristics with relation to fluorescence and salinity in coastal areas of the Southern Baltic Sea,” Estuar. Coast. Shelf Sci.47(1), 91–105 (1998).
[CrossRef]

Doxaran, D.

D. Doxaran, R. C. N. Cherukuru, and S. J. Lavender, “Use of reflectance band ratios to estimate suspended and dissolved matter concentrations in estuarine waters,” Int. J. Remote Sens.26(8), 1763–1769 (2005).
[CrossRef]

English, D.

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, L. Feng, R. Boler, and C. Kovach, “Towards a long-term chlorophyll-a data record in a turbid estuary using MODIS observations,” Prog. Oceanogr.109, 90–103 (2013b).
[CrossRef]

C. Le, C. Hu, D. English, J. Cannizzaro, and C. Kovach, “Climate-driven chlorophyll-a changes in a turbid estuary: observations from satellites and implications for management’,” Remote Sens. Environ.130, 11–24 (2013c).
[CrossRef]

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, C. Kovach, C. J. Anastasiou, J. Zhao, and K. L. Carder, “Inherent and apparent optical properties of the complex estuarine waters of Tampa Bay: what controls light?” Estuar. Coast. Shelf Sci.117, 54–69 (2013a).
[CrossRef]

Feldman, G. C.

P. J. Werdell, S. W. Bailey, B. A. Franz, L. W. Harding, G. C. Feldman, and C. R. McClain, “Regional and seasonal variability of chlorophyll-a in Chesapeake Bay as observed by SeaWiFS and MODIS-Aqua,” Remote Sens. Environ.113(6), 1319–1330 (2009).
[CrossRef]

Feng, L.

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, L. Feng, R. Boler, and C. Kovach, “Towards a long-term chlorophyll-a data record in a turbid estuary using MODIS observations,” Prog. Oceanogr.109, 90–103 (2013b).
[CrossRef]

Ferrari, G. M.

G. M. Ferrari and M. D. Dowell, “CDOM absorption characteristics with relation to fluorescence and salinity in coastal areas of the Southern Baltic Sea,” Estuar. Coast. Shelf Sci.47(1), 91–105 (1998).
[CrossRef]

Fischer, J.

J. Fischer, “On the information content of multispectral radiance measurements over an ocean,” Int. J. Remote Sens.6(5), 773–786 (1985).
[CrossRef]

Ford, P. W.

K. Oubelkheir, L. A. Clementson, I. T. Webster, P. W. Ford, A. G. Dekker, L. C. Radke, and P. Daniel, “Using inherent optical properties to investigate biogeochemical dynamic in a tropical macrotidal coastal system,” J. Geophys. Res.111(C7), C07021 (2006), doi:.
[CrossRef]

Franz, B. A.

P. J. Werdell, S. W. Bailey, B. A. Franz, L. W. Harding, G. C. Feldman, and C. R. McClain, “Regional and seasonal variability of chlorophyll-a in Chesapeake Bay as observed by SeaWiFS and MODIS-Aqua,” Remote Sens. Environ.113(6), 1319–1330 (2009).
[CrossRef]

Fry, E. S.

Gall, M.

J. Udy, M. Gall, B. Longstaff, K. Moore, C. Roelfsema, D. R. Spooner, and S. Albert, “Water quality monitoring: a combined approach to investigate gradients of change in the Great Barrier Reef, Australia,” Mar. Pollut. Bull.51(1-4), 224–238 (2005).
[CrossRef] [PubMed]

Gallegos, C. L.

M. Tzortziou, A. Subramanian, J. R. Herman, C. L. Gallegos, P. J. Neale, and L. W. Harding, “Remote sensing reflectance and inherent optical properties in the mid Chesapeake Bay,” Estuar. Coast. Shelf Sci.72(1-2), 16–32 (2007).
[CrossRef]

Gangle, B.

V. R. Louis, E. Russek-Cohen, N. Choopun, I. N. G. Rivera, B. Gangle, S. C. Jiang, A. Rubin, J. A. Patz, A. Huq, and R. R. Colwell, “Predictability of Vibrio cholerae in Chesapeake Bay,” Appl. Environ. Microbiol.69(5), 2773–2785 (2003).
[CrossRef] [PubMed]

Gao, H.

H. Gao and R. G. Zepp, “Factors influencing photoreactions of dissolved organic matter in a coastal river of the southeastern United States,” Environ. Sci. Technol.32(19), 2940–2946 (1998).
[CrossRef]

Gardner, G. B.

W. Zhu, Q. Yu, Y. Tian, R. Chen, and G. B. Gardner, “Estimation of chromophoric dissolved organic matter in the Mississippi and Atchafalaya river plume regions using above-surface hyperspectral remote sensing,” J. Geophys. Res.116(C2), C02011 (2011), doi:.
[CrossRef]

Geiger, E. F.

E. A. Urquhat, B. F. Zaitchik, M. J. Hoffman, S. D. Guikema, and E. F. Geiger, “Remote sensed estimates of surface salinity in the Chesapeake Bay: a statistical approach,” Remote Sens. Environ.123, 522–531 (2012).
[CrossRef]

Gregg, W. W.

W. W. Gregg and N. W. Casey, “Global and regional evaluation of the SeaWiFS chlorophyll dataset,” Remote Sens. Environ.93(4), 463–479 (2004).
[CrossRef]

Guikema, S. D.

E. A. Urquhat, B. F. Zaitchik, M. J. Hoffman, S. D. Guikema, and E. F. Geiger, “Remote sensed estimates of surface salinity in the Chesapeake Bay: a statistical approach,” Remote Sens. Environ.123, 522–531 (2012).
[CrossRef]

Hansell, D. A.

D. A. Siegel, S. Maritorena, N. B. Nelson, D. A. Hansell, and M. Lorenzi-Kayser, “Global distribution and dynamics of colored dissolved and detrital organic materials,” J. Geophys. Res. 107, 3228, DOI:. (2002).
[CrossRef]

Harding, L. W.

M. Wang, S. Son, and L. W. Harding., “Retrieval of diffuse attenuation coefficient in the Chesapeake Bay and turbid ocean regions for satellite ocean color applications,” J. Geophys. Res.114(C10), C10011 (2009), doi:.
[CrossRef]

P. J. Werdell, S. W. Bailey, B. A. Franz, L. W. Harding, G. C. Feldman, and C. R. McClain, “Regional and seasonal variability of chlorophyll-a in Chesapeake Bay as observed by SeaWiFS and MODIS-Aqua,” Remote Sens. Environ.113(6), 1319–1330 (2009).
[CrossRef]

M. Tzortziou, A. Subramanian, J. R. Herman, C. L. Gallegos, P. J. Neale, and L. W. Harding, “Remote sensing reflectance and inherent optical properties in the mid Chesapeake Bay,” Estuar. Coast. Shelf Sci.72(1-2), 16–32 (2007).
[CrossRef]

L. W. Harding, A. Magnuson, and M. E. Mallonee, “SeaWiFS retrievals of chlorophyll in Chesapeake Bay and the mid-Atlantic bight,” Estuar. Coast. Shelf Sci.62(1-2), 75–94 (2005b).
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L. W. Harding, A. Magnuson, and M. E. Mallonee, “Bio-optical and remote sensing observations in Chesapeake Bay,” Estuar. Coast. Shelf Sci.62, 75–94 (2005).
[CrossRef]

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.104(C3), 5403–5421 (1999).
[CrossRef]

Herman, J. R.

M. Tzortziou, A. Subramanian, J. R. Herman, C. L. Gallegos, P. J. Neale, and L. W. Harding, “Remote sensing reflectance and inherent optical properties in the mid Chesapeake Bay,” Estuar. Coast. Shelf Sci.72(1-2), 16–32 (2007).
[CrossRef]

Hoffman, M. J.

E. A. Urquhat, B. F. Zaitchik, M. J. Hoffman, S. D. Guikema, and E. F. Geiger, “Remote sensed estimates of surface salinity in the Chesapeake Bay: a statistical approach,” Remote Sens. Environ.123, 522–531 (2012).
[CrossRef]

Hood, R. R.

G. C. Magny, W. Long, C. W. Brown, R. R. Hood, A. Huq, R. Murtugudde, and R. R. Colwell, “Predicting the distribution of Vibrio spp. in the Chesapeake Bay: a vibrio cholera case study,” EcoHealth (2010), doi:.
[CrossRef]

Hooker, S. B.

A. Mannino, M. E. Russ, and S. B. Hooker, “Algorithm development and validation for satellite-derived distributions of DOC and CDOM in the US Middle Atlantic Bight,” J. Geophys. Res.113(C7), C07051 (2008), doi:.
[CrossRef]

Hu, C.

C. Le, C. Hu, D. English, J. Cannizzaro, and C. Kovach, “Climate-driven chlorophyll-a changes in a turbid estuary: observations from satellites and implications for management’,” Remote Sens. Environ.130, 11–24 (2013c).
[CrossRef]

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, L. Feng, R. Boler, and C. Kovach, “Towards a long-term chlorophyll-a data record in a turbid estuary using MODIS observations,” Prog. Oceanogr.109, 90–103 (2013b).
[CrossRef]

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, C. Kovach, C. J. Anastasiou, J. Zhao, and K. L. Carder, “Inherent and apparent optical properties of the complex estuarine waters of Tampa Bay: what controls light?” Estuar. Coast. Shelf Sci.117, 54–69 (2013a).
[CrossRef]

Z. Chen, C. Hu, F. E. Muller-Karger, and M. E. Luther, “Short-term variability of suspended sediment and phytoplankton in Tampa Bay, Florida: observations from a coastal oceanographic tower and ocean color satellites,” Estuar. Coast. Shelf Sci.89(1), 62–72 (2010).
[CrossRef]

Z. Chen, F. E. Muller-Karger, and C. Hu, “Remote sensing of water clarity in Tampa Bay,” Remote Sens. Environ.109(2), 249–259 (2007b).
[CrossRef]

Z. Chen, C. Hu, R. N. Conmy, F. E. Muller-Karger, and P. Swarzenski, “Colored dissolved organic matter in Tampa Bay, Florida,” Mar. Chem.104(1-2), 98–109 (2007a).
[CrossRef]

Z. Chen, C. Hu, and F. E. Muller-Karger, “Monitoring turbidity in Tampa Bay using MODIS/Aqua 250-m imagery,” Remote Sens. Environ.109(2), 207–220 (2007c).
[CrossRef]

C. Hu, Z. Chen, T. D. Clayton, P. Swarzenski, J. C. Brock, and F. E. Muller-Karger, “Assessment of estuarine water-quality indicators using MODIS medium-resolution bands: initial results from Tampa Bay, FL,” Remote Sens. Environ.93(3), 423–441 (2004).
[CrossRef] [PubMed]

C. Hu, K. L. Carder, and F. E. Muller-Karger, “How precise are SeaWiFS ocean color estimates? Implications of digitization-noise errors,” Remote Sens. Environ.76(2), 239–249 (2001).
[CrossRef]

Huang, C.

D. Sun, Y. Li, Q. Wang, C. Le, C. Huang, and L. Wang, “Parameterization of water component absorption in an inland eutrophic lake and its seasonal variability: a case study in Lake Taihu,” Int. J. Remote Sens.30(13), 3549–3571 (2009).
[CrossRef]

Huq, A.

G. C. Magny, W. Long, C. W. Brown, R. R. Hood, A. Huq, R. Murtugudde, and R. R. Colwell, “Predicting the distribution of Vibrio spp. in the Chesapeake Bay: a vibrio cholera case study,” EcoHealth (2010), doi:.
[CrossRef]

V. R. Louis, E. Russek-Cohen, N. Choopun, I. N. G. Rivera, B. Gangle, S. C. Jiang, A. Rubin, J. A. Patz, A. Huq, and R. R. Colwell, “Predictability of Vibrio cholerae in Chesapeake Bay,” Appl. Environ. Microbiol.69(5), 2773–2785 (2003).
[CrossRef] [PubMed]

Jiang, S. C.

V. R. Louis, E. Russek-Cohen, N. Choopun, I. N. G. Rivera, B. Gangle, S. C. Jiang, A. Rubin, J. A. Patz, A. Huq, and R. R. Colwell, “Predictability of Vibrio cholerae in Chesapeake Bay,” Appl. Environ. Microbiol.69(5), 2773–2785 (2003).
[CrossRef] [PubMed]

Kaczmarek, S.

P. Kowalczuk, L. Olszewski, M. Darecki, and S. Kaczmarek, “Empirical relationships between coloured dissolved organic matter (CDOM) absorption and apparent optical properties in Baltic Sea waters,” Int. J. Remote Sens.26(2), 345–370 (2005).
[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.104(C3), 5403–5421 (1999).
[CrossRef]

Kovach, C.

C. Le, C. Hu, D. English, J. Cannizzaro, and C. Kovach, “Climate-driven chlorophyll-a changes in a turbid estuary: observations from satellites and implications for management’,” Remote Sens. Environ.130, 11–24 (2013c).
[CrossRef]

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, C. Kovach, C. J. Anastasiou, J. Zhao, and K. L. Carder, “Inherent and apparent optical properties of the complex estuarine waters of Tampa Bay: what controls light?” Estuar. Coast. Shelf Sci.117, 54–69 (2013a).
[CrossRef]

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, L. Feng, R. Boler, and C. Kovach, “Towards a long-term chlorophyll-a data record in a turbid estuary using MODIS observations,” Prog. Oceanogr.109, 90–103 (2013b).
[CrossRef]

Kowalczuk, P.

P. Kowalczuk, L. Olszewski, M. Darecki, and S. Kaczmarek, “Empirical relationships between coloured dissolved organic matter (CDOM) absorption and apparent optical properties in Baltic Sea waters,” Int. J. Remote Sens.26(2), 345–370 (2005).
[CrossRef]

Laubel, A.

C. A. Stedmon, S. Markager, M. Søndergaard, T. Vang, A. Laubel, N. H. Borch, and A. Windelin, “Dissolved organic matter (DOM) export to a temperate estuary: seasonal variations and implications of land use,” Estuaries Coasts29, 388–400 (2006).

Lavender, S. J.

D. Doxaran, R. C. N. Cherukuru, and S. J. Lavender, “Use of reflectance band ratios to estimate suspended and dissolved matter concentrations in estuarine waters,” Int. J. Remote Sens.26(8), 1763–1769 (2005).
[CrossRef]

Le, C.

C. Le, C. Hu, D. English, J. Cannizzaro, and C. Kovach, “Climate-driven chlorophyll-a changes in a turbid estuary: observations from satellites and implications for management’,” Remote Sens. Environ.130, 11–24 (2013c).
[CrossRef]

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, C. Kovach, C. J. Anastasiou, J. Zhao, and K. L. Carder, “Inherent and apparent optical properties of the complex estuarine waters of Tampa Bay: what controls light?” Estuar. Coast. Shelf Sci.117, 54–69 (2013a).
[CrossRef]

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, L. Feng, R. Boler, and C. Kovach, “Towards a long-term chlorophyll-a data record in a turbid estuary using MODIS observations,” Prog. Oceanogr.109, 90–103 (2013b).
[CrossRef]

C. Le, Y. Li, Y. Zha, D. Sun, and B. Yin, “Validation of a quasi-analytical algorithm for highly turbid eutrophic water of Meiliang Bay in Taihu Lake, China,” IEEE Trans. Geosci. Rem. Sens.8, 2490–2500 (2009).

D. Sun, Y. Li, Q. Wang, C. Le, C. Huang, and L. Wang, “Parameterization of water component absorption in an inland eutrophic lake and its seasonal variability: a case study in Lake Taihu,” Int. J. Remote Sens.30(13), 3549–3571 (2009).
[CrossRef]

Lee, Z.

Q. Dong, S. Shang, and Z. Lee, “An algorithm to retrieve absorption coefficient of chromophoric dissolved organic matter from ocean color,” Remote Sens. Environ.128, 259–267 (2013).
[CrossRef]

Lee, Z. P.

Li, D. J.

F. Shen, Y. X. Zhou, D. J. Li, W. J. Zhu, and M. S. Salama, “Medium resolution imaging spectrometer (MERIS) estimation of chlorophyll-a concentration in the turbid sediment-laden waters of the Changjiang (Yangtze) Estuary,” Int. J. Remote Sens.31(17-18), 4635–4650 (2010).
[CrossRef]

Li, Y.

D. Sun, Y. Li, Q. Wang, C. Le, C. Huang, and L. Wang, “Parameterization of water component absorption in an inland eutrophic lake and its seasonal variability: a case study in Lake Taihu,” Int. J. Remote Sens.30(13), 3549–3571 (2009).
[CrossRef]

C. Le, Y. Li, Y. Zha, D. Sun, and B. Yin, “Validation of a quasi-analytical algorithm for highly turbid eutrophic water of Meiliang Bay in Taihu Lake, China,” IEEE Trans. Geosci. Rem. Sens.8, 2490–2500 (2009).

Lipp, E. K.

N. Schmidt, E. K. Lipp, J. B. Rose, and M. E. Luther, “ENSO influences on Seasonal Rainfall and River Discharger in Florida,” J. Clim.14(4), 615–628 (2001).
[CrossRef]

Liu, C. C.

C. C. Liu and R. L. Miller, “Spectrum matching method for estimating the chlorophyll-a concentration, CDOM ratio, and backscatter fraction from remote sensing of ocean color,” Can. J. Rem. Sens.34(4), 343–355 (2008).
[CrossRef]

Long, W.

G. C. Magny, W. Long, C. W. Brown, R. R. Hood, A. Huq, R. Murtugudde, and R. R. Colwell, “Predicting the distribution of Vibrio spp. in the Chesapeake Bay: a vibrio cholera case study,” EcoHealth (2010), doi:.
[CrossRef]

Longstaff, B.

J. Udy, M. Gall, B. Longstaff, K. Moore, C. Roelfsema, D. R. Spooner, and S. Albert, “Water quality monitoring: a combined approach to investigate gradients of change in the Great Barrier Reef, Australia,” Mar. Pollut. Bull.51(1-4), 224–238 (2005).
[CrossRef] [PubMed]

Lorenzi-Kayser, M.

D. A. Siegel, S. Maritorena, N. B. Nelson, D. A. Hansell, and M. Lorenzi-Kayser, “Global distribution and dynamics of colored dissolved and detrital organic materials,” J. Geophys. Res. 107, 3228, DOI:. (2002).
[CrossRef]

Louis, V. R.

V. R. Louis, E. Russek-Cohen, N. Choopun, I. N. G. Rivera, B. Gangle, S. C. Jiang, A. Rubin, J. A. Patz, A. Huq, and R. R. Colwell, “Predictability of Vibrio cholerae in Chesapeake Bay,” Appl. Environ. Microbiol.69(5), 2773–2785 (2003).
[CrossRef] [PubMed]

Luther, M. E.

Z. Chen, C. Hu, F. E. Muller-Karger, and M. E. Luther, “Short-term variability of suspended sediment and phytoplankton in Tampa Bay, Florida: observations from a coastal oceanographic tower and ocean color satellites,” Estuar. Coast. Shelf Sci.89(1), 62–72 (2010).
[CrossRef]

N. Schmidt, E. K. Lipp, J. B. Rose, and M. E. Luther, “ENSO influences on Seasonal Rainfall and River Discharger in Florida,” J. Clim.14(4), 615–628 (2001).
[CrossRef]

Magnuson, A.

L. W. Harding, A. Magnuson, and M. E. Mallonee, “SeaWiFS retrievals of chlorophyll in Chesapeake Bay and the mid-Atlantic bight,” Estuar. Coast. Shelf Sci.62(1-2), 75–94 (2005b).
[CrossRef]

L. W. Harding, A. Magnuson, and M. E. Mallonee, “Bio-optical and remote sensing observations in Chesapeake Bay,” Estuar. Coast. Shelf Sci.62, 75–94 (2005).
[CrossRef]

Magny, G. C.

G. C. Magny, W. Long, C. W. Brown, R. R. Hood, A. Huq, R. Murtugudde, and R. R. Colwell, “Predicting the distribution of Vibrio spp. in the Chesapeake Bay: a vibrio cholera case study,” EcoHealth (2010), doi:.
[CrossRef]

Mallonee, M. E.

L. W. Harding, A. Magnuson, and M. E. Mallonee, “SeaWiFS retrievals of chlorophyll in Chesapeake Bay and the mid-Atlantic bight,” Estuar. Coast. Shelf Sci.62(1-2), 75–94 (2005b).
[CrossRef]

L. W. Harding, A. Magnuson, and M. E. Mallonee, “Bio-optical and remote sensing observations in Chesapeake Bay,” Estuar. Coast. Shelf Sci.62, 75–94 (2005).
[CrossRef]

Mannino, A.

A. Mannino, M. E. Russ, and S. B. Hooker, “Algorithm development and validation for satellite-derived distributions of DOC and CDOM in the US Middle Atlantic Bight,” J. Geophys. Res.113(C7), C07051 (2008), doi:.
[CrossRef]

Maritorena, S.

S. Maritorena and D. A. Siegel, “Consistent merging of satellite ocean color data sets using a bio-optical model,” Remote Sens. Environ.94, 429–440 (2005).
[CrossRef]

D. A. Siegel, S. Maritorena, N. B. Nelson, D. A. Hansell, and M. Lorenzi-Kayser, “Global distribution and dynamics of colored dissolved and detrital organic materials,” J. Geophys. Res. 107, 3228, DOI:. (2002).
[CrossRef]

Markager, S.

C. A. Stedmon, S. Markager, M. Søndergaard, T. Vang, A. Laubel, N. H. Borch, and A. Windelin, “Dissolved organic matter (DOM) export to a temperate estuary: seasonal variations and implications of land use,” Estuaries Coasts29, 388–400 (2006).

McClain, C. R.

P. J. Werdell, S. W. Bailey, B. A. Franz, L. W. Harding, G. C. Feldman, and C. R. McClain, “Regional and seasonal variability of chlorophyll-a in Chesapeake Bay as observed by SeaWiFS and MODIS-Aqua,” Remote Sens. Environ.113(6), 1319–1330 (2009).
[CrossRef]

Michaels, A. F.

N. B. Nelson, D. A. Siegel, and A. F. Michaels, “Seasonal dynamics of colored dissolved material in the Sargasso Sea,” Deep Sea Res. Part I Oceanogr. Res. Pap.45(6), 931–957 (1998).
[CrossRef]

Miller, R. L.

C. C. Liu and R. L. Miller, “Spectrum matching method for estimating the chlorophyll-a concentration, CDOM ratio, and backscatter fraction from remote sensing of ocean color,” Can. J. Rem. Sens.34(4), 343–355 (2008).
[CrossRef]

E. J. D’Sa and R. L. Miller, “Bio-optical properties in waters influenced by the Mississippi River during low flow conditions,” Remote Sens. Environ.84(4), 538–549 (2003).
[CrossRef]

Moore, K.

J. Udy, M. Gall, B. Longstaff, K. Moore, C. Roelfsema, D. R. Spooner, and S. Albert, “Water quality monitoring: a combined approach to investigate gradients of change in the Great Barrier Reef, Australia,” Mar. Pollut. Bull.51(1-4), 224–238 (2005).
[CrossRef] [PubMed]

Mueller, J. L.

Muller-Karger, F. E.

Z. Chen, C. Hu, F. E. Muller-Karger, and M. E. Luther, “Short-term variability of suspended sediment and phytoplankton in Tampa Bay, Florida: observations from a coastal oceanographic tower and ocean color satellites,” Estuar. Coast. Shelf Sci.89(1), 62–72 (2010).
[CrossRef]

Z. Chen, F. E. Muller-Karger, and C. Hu, “Remote sensing of water clarity in Tampa Bay,” Remote Sens. Environ.109(2), 249–259 (2007b).
[CrossRef]

Z. Chen, C. Hu, R. N. Conmy, F. E. Muller-Karger, and P. Swarzenski, “Colored dissolved organic matter in Tampa Bay, Florida,” Mar. Chem.104(1-2), 98–109 (2007a).
[CrossRef]

Z. Chen, C. Hu, and F. E. Muller-Karger, “Monitoring turbidity in Tampa Bay using MODIS/Aqua 250-m imagery,” Remote Sens. Environ.109(2), 207–220 (2007c).
[CrossRef]

C. Hu, Z. Chen, T. D. Clayton, P. Swarzenski, J. C. Brock, and F. E. Muller-Karger, “Assessment of estuarine water-quality indicators using MODIS medium-resolution bands: initial results from Tampa Bay, FL,” Remote Sens. Environ.93(3), 423–441 (2004).
[CrossRef] [PubMed]

C. Hu, K. L. Carder, and F. E. Muller-Karger, “How precise are SeaWiFS ocean color estimates? Implications of digitization-noise errors,” Remote Sens. Environ.76(2), 239–249 (2001).
[CrossRef]

Murtugudde, R.

G. C. Magny, W. Long, C. W. Brown, R. R. Hood, A. Huq, R. Murtugudde, and R. R. Colwell, “Predicting the distribution of Vibrio spp. in the Chesapeake Bay: a vibrio cholera case study,” EcoHealth (2010), doi:.
[CrossRef]

Neale, P. J.

M. Tzortziou, A. Subramanian, J. R. Herman, C. L. Gallegos, P. J. Neale, and L. W. Harding, “Remote sensing reflectance and inherent optical properties in the mid Chesapeake Bay,” Estuar. Coast. Shelf Sci.72(1-2), 16–32 (2007).
[CrossRef]

Nelson, N. B.

D. A. Siegel, S. Maritorena, N. B. Nelson, D. A. Hansell, and M. Lorenzi-Kayser, “Global distribution and dynamics of colored dissolved and detrital organic materials,” J. Geophys. Res. 107, 3228, DOI:. (2002).
[CrossRef]

N. B. Nelson, D. A. Siegel, and A. F. Michaels, “Seasonal dynamics of colored dissolved material in the Sargasso Sea,” Deep Sea Res. Part I Oceanogr. Res. Pap.45(6), 931–957 (1998).
[CrossRef]

Olszewski, L.

P. Kowalczuk, L. Olszewski, M. Darecki, and S. Kaczmarek, “Empirical relationships between coloured dissolved organic matter (CDOM) absorption and apparent optical properties in Baltic Sea waters,” Int. J. Remote Sens.26(2), 345–370 (2005).
[CrossRef]

Osburn, C. L.

N. C. Tehrani, E. J. D’Sa, C. L. Osburn, T. S. Bianchi, and B. A. Schaeffer, “Chromophoric dissolved organic matter and dissolved organic carbon from Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS) and MERIS Sensors: case Study for the Northern Gulf of Mexico,” Remote Sens.5(3), 1439–1464 (2013).
[CrossRef]

Oubelkheir, K.

K. Oubelkheir, L. A. Clementson, I. T. Webster, P. W. Ford, A. G. Dekker, L. C. Radke, and P. Daniel, “Using inherent optical properties to investigate biogeochemical dynamic in a tropical macrotidal coastal system,” J. Geophys. Res.111(C7), C07021 (2006), doi:.
[CrossRef]

Patz, J. A.

V. R. Louis, E. Russek-Cohen, N. Choopun, I. N. G. Rivera, B. Gangle, S. C. Jiang, A. Rubin, J. A. Patz, A. Huq, and R. R. Colwell, “Predictability of Vibrio cholerae in Chesapeake Bay,” Appl. Environ. Microbiol.69(5), 2773–2785 (2003).
[CrossRef] [PubMed]

Peacock, T. G.

Pope, R. M.

Qin, Y.

Y. Qin, V. E. Brando, A. G. Dekker, and D. Blondeau-Patissier, “Validity of SeaDAS water constituents retrieval algorithms in Australian tropical coastal waters,” J. Geophys. Res. Lett.34(21), L21603 (2007), doi:.
[CrossRef]

Radke, L. C.

K. Oubelkheir, L. A. Clementson, I. T. Webster, P. W. Ford, A. G. Dekker, L. C. Radke, and P. Daniel, “Using inherent optical properties to investigate biogeochemical dynamic in a tropical macrotidal coastal system,” J. Geophys. Res.111(C7), C07021 (2006), doi:.
[CrossRef]

Rivera, I. N. G.

V. R. Louis, E. Russek-Cohen, N. Choopun, I. N. G. Rivera, B. Gangle, S. C. Jiang, A. Rubin, J. A. Patz, A. Huq, and R. R. Colwell, “Predictability of Vibrio cholerae in Chesapeake Bay,” Appl. Environ. Microbiol.69(5), 2773–2785 (2003).
[CrossRef] [PubMed]

Roelfsema, C.

J. Udy, M. Gall, B. Longstaff, K. Moore, C. Roelfsema, D. R. Spooner, and S. Albert, “Water quality monitoring: a combined approach to investigate gradients of change in the Great Barrier Reef, Australia,” Mar. Pollut. Bull.51(1-4), 224–238 (2005).
[CrossRef] [PubMed]

Rose, J. B.

N. Schmidt, E. K. Lipp, J. B. Rose, and M. E. Luther, “ENSO influences on Seasonal Rainfall and River Discharger in Florida,” J. Clim.14(4), 615–628 (2001).
[CrossRef]

Rubin, A.

V. R. Louis, E. Russek-Cohen, N. Choopun, I. N. G. Rivera, B. Gangle, S. C. Jiang, A. Rubin, J. A. Patz, A. Huq, and R. R. Colwell, “Predictability of Vibrio cholerae in Chesapeake Bay,” Appl. Environ. Microbiol.69(5), 2773–2785 (2003).
[CrossRef] [PubMed]

Russ, M. E.

A. Mannino, M. E. Russ, and S. B. Hooker, “Algorithm development and validation for satellite-derived distributions of DOC and CDOM in the US Middle Atlantic Bight,” J. Geophys. Res.113(C7), C07051 (2008), doi:.
[CrossRef]

Russek-Cohen, E.

V. R. Louis, E. Russek-Cohen, N. Choopun, I. N. G. Rivera, B. Gangle, S. C. Jiang, A. Rubin, J. A. Patz, A. Huq, and R. R. Colwell, “Predictability of Vibrio cholerae in Chesapeake Bay,” Appl. Environ. Microbiol.69(5), 2773–2785 (2003).
[CrossRef] [PubMed]

Salama, M. S.

F. Shen, Y. X. Zhou, D. J. Li, W. J. Zhu, and M. S. Salama, “Medium resolution imaging spectrometer (MERIS) estimation of chlorophyll-a concentration in the turbid sediment-laden waters of the Changjiang (Yangtze) Estuary,” Int. J. Remote Sens.31(17-18), 4635–4650 (2010).
[CrossRef]

Schaeffer, B. A.

N. C. Tehrani, E. J. D’Sa, C. L. Osburn, T. S. Bianchi, and B. A. Schaeffer, “Chromophoric dissolved organic matter and dissolved organic carbon from Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS) and MERIS Sensors: case Study for the Northern Gulf of Mexico,” Remote Sens.5(3), 1439–1464 (2013).
[CrossRef]

Schmidt, N.

N. Schmidt, E. K. Lipp, J. B. Rose, and M. E. Luther, “ENSO influences on Seasonal Rainfall and River Discharger in Florida,” J. Clim.14(4), 615–628 (2001).
[CrossRef]

Shang, S.

Q. Dong, S. Shang, and Z. Lee, “An algorithm to retrieve absorption coefficient of chromophoric dissolved organic matter from ocean color,” Remote Sens. Environ.128, 259–267 (2013).
[CrossRef]

Shanmugam, P.

S. P. Tiwari and P. Shanmugam, “An optical model for the remote sensing of coloured dissolved organic matter in coastal/ocean waters,” Estuar. Coast. Shelf Sci.93(4), 396–402 (2011).
[CrossRef]

Shen, F.

F. Shen, Y. X. Zhou, D. J. Li, W. J. Zhu, and M. S. Salama, “Medium resolution imaging spectrometer (MERIS) estimation of chlorophyll-a concentration in the turbid sediment-laden waters of the Changjiang (Yangtze) Estuary,” Int. J. Remote Sens.31(17-18), 4635–4650 (2010).
[CrossRef]

Siegel, D. A.

S. Maritorena and D. A. Siegel, “Consistent merging of satellite ocean color data sets using a bio-optical model,” Remote Sens. Environ.94, 429–440 (2005).
[CrossRef]

D. A. Siegel, S. Maritorena, N. B. Nelson, D. A. Hansell, and M. Lorenzi-Kayser, “Global distribution and dynamics of colored dissolved and detrital organic materials,” J. Geophys. Res. 107, 3228, DOI:. (2002).
[CrossRef]

N. B. Nelson, D. A. Siegel, and A. F. Michaels, “Seasonal dynamics of colored dissolved material in the Sargasso Sea,” Deep Sea Res. Part I Oceanogr. Res. Pap.45(6), 931–957 (1998).
[CrossRef]

Son, S.

S. Son and M. Wang, “Water properties in Chesapeake Bay from MODIS-Aqua measurements,” Remote Sens. Environ.123, 163–174 (2012).
[CrossRef]

M. Wang, S. Son, and L. W. Harding., “Retrieval of diffuse attenuation coefficient in the Chesapeake Bay and turbid ocean regions for satellite ocean color applications,” J. Geophys. Res.114(C10), C10011 (2009), doi:.
[CrossRef]

Søndergaard, M.

C. A. Stedmon, S. Markager, M. Søndergaard, T. Vang, A. Laubel, N. H. Borch, and A. Windelin, “Dissolved organic matter (DOM) export to a temperate estuary: seasonal variations and implications of land use,” Estuaries Coasts29, 388–400 (2006).

Spooner, D. R.

J. Udy, M. Gall, B. Longstaff, K. Moore, C. Roelfsema, D. R. Spooner, and S. Albert, “Water quality monitoring: a combined approach to investigate gradients of change in the Great Barrier Reef, Australia,” Mar. Pollut. Bull.51(1-4), 224–238 (2005).
[CrossRef] [PubMed]

Stedmon, C. A.

C. A. Stedmon, S. Markager, M. Søndergaard, T. Vang, A. Laubel, N. H. Borch, and A. Windelin, “Dissolved organic matter (DOM) export to a temperate estuary: seasonal variations and implications of land use,” Estuaries Coasts29, 388–400 (2006).

Subramanian, A.

M. Tzortziou, A. Subramanian, J. R. Herman, C. L. Gallegos, P. J. Neale, and L. W. Harding, “Remote sensing reflectance and inherent optical properties in the mid Chesapeake Bay,” Estuar. Coast. Shelf Sci.72(1-2), 16–32 (2007).
[CrossRef]

Sun, D.

D. Sun, Y. Li, Q. Wang, C. Le, C. Huang, and L. Wang, “Parameterization of water component absorption in an inland eutrophic lake and its seasonal variability: a case study in Lake Taihu,” Int. J. Remote Sens.30(13), 3549–3571 (2009).
[CrossRef]

C. Le, Y. Li, Y. Zha, D. Sun, and B. Yin, “Validation of a quasi-analytical algorithm for highly turbid eutrophic water of Meiliang Bay in Taihu Lake, China,” IEEE Trans. Geosci. Rem. Sens.8, 2490–2500 (2009).

Swarzenski, P.

Z. Chen, C. Hu, R. N. Conmy, F. E. Muller-Karger, and P. Swarzenski, “Colored dissolved organic matter in Tampa Bay, Florida,” Mar. Chem.104(1-2), 98–109 (2007a).
[CrossRef]

C. Hu, Z. Chen, T. D. Clayton, P. Swarzenski, J. C. Brock, and F. E. Muller-Karger, “Assessment of estuarine water-quality indicators using MODIS medium-resolution bands: initial results from Tampa Bay, FL,” Remote Sens. Environ.93(3), 423–441 (2004).
[CrossRef] [PubMed]

Tehrani, N. C.

N. C. Tehrani, E. J. D’Sa, C. L. Osburn, T. S. Bianchi, and B. A. Schaeffer, “Chromophoric dissolved organic matter and dissolved organic carbon from Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS) and MERIS Sensors: case Study for the Northern Gulf of Mexico,” Remote Sens.5(3), 1439–1464 (2013).
[CrossRef]

Tian, Y.

W. Zhu, Q. Yu, Y. Tian, R. Chen, and G. B. Gardner, “Estimation of chromophoric dissolved organic matter in the Mississippi and Atchafalaya river plume regions using above-surface hyperspectral remote sensing,” J. Geophys. Res.116(C2), C02011 (2011), doi:.
[CrossRef]

Timlin, M. S.

K. Wolter and M. S. Timlin, “El Niño/Southern Oscillation behavior since 1871 as diagnosed in an extended multivariate ENSO index (MEI.ext),” Int. J. Climatol.31(7), 1074–1087 (2011).
[CrossRef]

Tiwari, S. P.

S. P. Tiwari and P. Shanmugam, “An optical model for the remote sensing of coloured dissolved organic matter in coastal/ocean waters,” Estuar. Coast. Shelf Sci.93(4), 396–402 (2011).
[CrossRef]

Tzortziou, M.

M. Tzortziou, A. Subramanian, J. R. Herman, C. L. Gallegos, P. J. Neale, and L. W. Harding, “Remote sensing reflectance and inherent optical properties in the mid Chesapeake Bay,” Estuar. Coast. Shelf Sci.72(1-2), 16–32 (2007).
[CrossRef]

Udy, J.

J. Udy, M. Gall, B. Longstaff, K. Moore, C. Roelfsema, D. R. Spooner, and S. Albert, “Water quality monitoring: a combined approach to investigate gradients of change in the Great Barrier Reef, Australia,” Mar. Pollut. Bull.51(1-4), 224–238 (2005).
[CrossRef] [PubMed]

Urquhat, E. A.

E. A. Urquhat, B. F. Zaitchik, M. J. Hoffman, S. D. Guikema, and E. F. Geiger, “Remote sensed estimates of surface salinity in the Chesapeake Bay: a statistical approach,” Remote Sens. Environ.123, 522–531 (2012).
[CrossRef]

Vang, T.

C. A. Stedmon, S. Markager, M. Søndergaard, T. Vang, A. Laubel, N. H. Borch, and A. Windelin, “Dissolved organic matter (DOM) export to a temperate estuary: seasonal variations and implications of land use,” Estuaries Coasts29, 388–400 (2006).

Wang, L.

D. Sun, Y. Li, Q. Wang, C. Le, C. Huang, and L. Wang, “Parameterization of water component absorption in an inland eutrophic lake and its seasonal variability: a case study in Lake Taihu,” Int. J. Remote Sens.30(13), 3549–3571 (2009).
[CrossRef]

Wang, M.

S. Son and M. Wang, “Water properties in Chesapeake Bay from MODIS-Aqua measurements,” Remote Sens. Environ.123, 163–174 (2012).
[CrossRef]

M. Wang, S. Son, and L. W. Harding., “Retrieval of diffuse attenuation coefficient in the Chesapeake Bay and turbid ocean regions for satellite ocean color applications,” J. Geophys. Res.114(C10), C10011 (2009), doi:.
[CrossRef]

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D. Sun, Y. Li, Q. Wang, C. Le, C. Huang, and L. Wang, “Parameterization of water component absorption in an inland eutrophic lake and its seasonal variability: a case study in Lake Taihu,” Int. J. Remote Sens.30(13), 3549–3571 (2009).
[CrossRef]

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[CrossRef]

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W. Zhu, Q. Yu, Y. Tian, R. Chen, and G. B. Gardner, “Estimation of chromophoric dissolved organic matter in the Mississippi and Atchafalaya river plume regions using above-surface hyperspectral remote sensing,” J. Geophys. Res.116(C2), C02011 (2011), doi:.
[CrossRef]

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E. A. Urquhat, B. F. Zaitchik, M. J. Hoffman, S. D. Guikema, and E. F. Geiger, “Remote sensed estimates of surface salinity in the Chesapeake Bay: a statistical approach,” Remote Sens. Environ.123, 522–531 (2012).
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Int. J. Climatol.

K. Wolter and M. S. Timlin, “El Niño/Southern Oscillation behavior since 1871 as diagnosed in an extended multivariate ENSO index (MEI.ext),” Int. J. Climatol.31(7), 1074–1087 (2011).
[CrossRef]

Int. J. Remote Sens.

D. Sun, Y. Li, Q. Wang, C. Le, C. Huang, and L. Wang, “Parameterization of water component absorption in an inland eutrophic lake and its seasonal variability: a case study in Lake Taihu,” Int. J. Remote Sens.30(13), 3549–3571 (2009).
[CrossRef]

F. Shen, Y. X. Zhou, D. J. Li, W. J. Zhu, and M. S. Salama, “Medium resolution imaging spectrometer (MERIS) estimation of chlorophyll-a concentration in the turbid sediment-laden waters of the Changjiang (Yangtze) Estuary,” Int. J. Remote Sens.31(17-18), 4635–4650 (2010).
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[CrossRef]

M. Wang, S. Son, and L. W. Harding., “Retrieval of diffuse attenuation coefficient in the Chesapeake Bay and turbid ocean regions for satellite ocean color applications,” J. Geophys. Res.114(C10), C10011 (2009), doi:.
[CrossRef]

K. Oubelkheir, L. A. Clementson, I. T. Webster, P. W. Ford, A. G. Dekker, L. C. Radke, and P. Daniel, “Using inherent optical properties to investigate biogeochemical dynamic in a tropical macrotidal coastal system,” J. Geophys. Res.111(C7), C07021 (2006), doi:.
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Mar. Chem.

Z. Chen, C. Hu, R. N. Conmy, F. E. Muller-Karger, and P. Swarzenski, “Colored dissolved organic matter in Tampa Bay, Florida,” Mar. Chem.104(1-2), 98–109 (2007a).
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J. Udy, M. Gall, B. Longstaff, K. Moore, C. Roelfsema, D. R. Spooner, and S. Albert, “Water quality monitoring: a combined approach to investigate gradients of change in the Great Barrier Reef, Australia,” Mar. Pollut. Bull.51(1-4), 224–238 (2005).
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Prog. Oceanogr.

C. Le, C. Hu, D. English, J. Cannizzaro, Z. Chen, L. Feng, R. Boler, and C. Kovach, “Towards a long-term chlorophyll-a data record in a turbid estuary using MODIS observations,” Prog. Oceanogr.109, 90–103 (2013b).
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Remote Sens.

N. C. Tehrani, E. J. D’Sa, C. L. Osburn, T. S. Bianchi, and B. A. Schaeffer, “Chromophoric dissolved organic matter and dissolved organic carbon from Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS) and MERIS Sensors: case Study for the Northern Gulf of Mexico,” Remote Sens.5(3), 1439–1464 (2013).
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Figures (12)

Fig. 1
Fig. 1

(a) Study area of Tampa Bay, Florida, USA, in the eastern Gulf of Mexico (inset figure). Following convention, Tampa Bay is divided into four segments separated by the dotted lines: Old Tampa Bay (OTB), Hillsborough Bay (HB), Middle Tampa Bay (MTB), and Lower Tampa Bay (LTB). Several major rivers that discharge into Tampa Bay are also annotated: Alafia River (AR), Hillsborough River (HR), Little Manatee River (LMR), and Manatee River (MR). (b) Station locations in Tampa Bay where bio-optical data were collected between October 2004 and November 2010.

Fig. 2
Fig. 2

Schematic flow chart showing the hybrid approach for deriving ag(443) from Rrs(λ). The gray dashed arrows indicate the steps in the original QAA. The bold text shows the processing not provided in the original QAA. The step numbers (Sx) correspond to those listed in Table 1.

Fig. 3
Fig. 3

Comparisons between measured and Rrs(λ)-derived (a) Chla, (b) at-w(443), (c) ad(443), and (d) ag(443) for Tampa Bay. Rrs(λ)-derived values were obtained using the hybrid approach with in situ Rrs(λ) as input. Algorithm performance is summarized in Table 2.

Fig. 4
Fig. 4

(a) Comparison between in situ measured Rrs(λ) and MODISA-derived Rrs(λ) at 443nm and 547nm; (b) Relationship between in situ Rrs(443) and in situ Rrs(550). All data were collected in Tampa Bay.

Fig. 5
Fig. 5

Comparisons between measured and Rrs(λ)-derived (a) Chla, (b) at-w(443), (c) ad(443), and (d) ag(443) for Tampa Bay. Rrs(λ)-derived values were obtained using the hybrid approach with satellite Rrs(λ) as input. Algorithm performance is summarized in Table 2.

Fig. 6
Fig. 6

(a) In situ ag(443) (m−1) estimated from CDOM fluorescence that was measured during a cruise survey on 17 April 2008 in LTB, where the same transect was measured three times with an underway flow-through system between 16:45 and 20:30 GMT; (b) ag(443) derived from MODISA Rrs on the same day (19:05 GMT) using the hybrid approach, with the cruise track overlaid as a red line; (c) Comparison between in situ measured ag(443) and MODISA-derived ag(443) along the transect.

Fig. 7
Fig. 7

Monthly mean ag(443) (m−1) in Tampa Bay derived from a combined SeaWiFS and MODISA climatology (1997-2002: SeaWiFS; 2003 – 2010, SeaWiFS and MODISA; 2011-2012: MODISA).

Fig. 8
Fig. 8

(a) Monthly means and standard deviations of ag(443) (m−1) in Tampa Bay for individual bay segments (HB, OTB, MTB, and LTB) derived from a combined SeaWiFS and MODISA climatology (1997-2002: SeaWiFS; 2003 – 2010, SeaWiFS and MODISA; 2011-2012: MODISA); (b) Monthly means and standard deviations of river discharge from the four main rivers (AR, HR, LMR, and MR) for the same period.

Fig. 9
Fig. 9

Annual mean ag(443) (m−1) in Tampa Bay derived from a combined SeaWiFS and MODISA climatology (1998-2002: SeaWiFS; 2003-2010, SeaWiFS and MODISA; 2011-2012: MODISA).

Fig. 10
Fig. 10

Annual means and standard deviations of (a) ag(443) and (b) Chla for individual bay segments (HB, OTB, MTB, and LTB) derived from a combined SeaWiFS and MODISA climatology (1997-2002: SeaWiFS; 2003 – 2010, SeaWiFS and MODISA; 2011-2012: MODISA) using the hybrid CDOM-retrieval approach and the RGCI algorithm, respectively. (c) Climatological annual means and standard deviations of river discharge from the four main rivers (AR, HR, LMR, and MR) for the same period (discharge data for 2012 was not available).

Fig. 11
Fig. 11

Comparisons between in situ measured and in situ Rrs(λ)-derived (a) Chla, (b) at-w(443), (c) ad(443), and (d) ag(443) using the hybrid approach in Chesapeake Bay.

Fig. 12
Fig. 12

(a) Relationship between field-measured salinity and ag(443) along a transect in LTB on 17 April 2008 (see Fig. 6(b) for transect location); (b) Relationship between field-measured salinity and MODISA-derived ag(443) in Tampa Bay. Salinity data in (b) were collected once a month by EPCHC from January 2007 to September 2010, and ag(443) was derived from MODISA Rrs(λ) measurements using the hybrid algorithm on the same day as the field measurements.

Tables (2)

Tables Icon

Table 1 Steps of the hybrid approach for deriving ag(443) from Rrs(λ). See Fig. 2 for a schematic flow chart of these steps.

Tables Icon

Table 2 Algorithm performance statistics for Tampa Bay using the hybrid approach with both in situ and satellite-derived Rrs data as input

Equations (12)

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

MRE( % )= 1 N | X measured X derived |/ X measured *100
RMSE( % )= 1 N [( X measured X derived )/ X measured ] 2 *100
r rs (λ)= Rrs(λ) 0.52+1.7Rrs(λ)
R(λ)=0.02+ [0.007+0.68 r rs (λ)] 0.5 0.34
a t ( 670 )= a g ( 670 ) + a d ( 670 ) + a ph ( 670 ) + a w ( 670 )» a ph ( 670 ) + a w ( 670 ),
a ph ( 670 )=A Chla B
b bp (670)= R(670)* a t (670) 1R(670) b bw (670)
b bp (443)= b bp (670) (443/670) Y
a t (443)= [1R(443)]*[ b bp (443)+ b bw (443)] R(443)
a ph ( 443 ) =0.051*chl a 0.74 ,
a d ( 443 ) =3.32* b bp (443)+0.0098
a g ( 443 )= a t ( 443 ) a d ( 443 ) a ph ( 443 ) a w ( 443 ).

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