Abstract

Using remote sensing reflectance (Rrs(λ), sr−1) and phycocyanin (PC, mg m−3) pigment data as well as other bio-optical data collected from two cruises in September and December 2009 in Lake Dianchi (a typical plateau lake of China), we developed a practical approach to estimate PC concentrations that could be applied directly to Landsat measurements. The visible and near-IR bands as well as their band ratios of simulated Landsat data were used as inputs to the algorithms, where the algorithm coefficients for each Landsat sensor were determined through multivariate regressions. The coefficients of determination (R2) between the Rrs-modeled and measured PC were all > 0.97 for the spectral bands corresponding to Landsat 8 OLI, Landsat 7 ETM + , Landsat 5 TM, and Landsat 4 TM, with mean absolute percentage errors (MAPE) < 10% for PC ranging between ~80 and 700 mg m−3 (n = 14). The algorithms were further evaluated using an independent data set (n = 14), yielding larger but still acceptable MAPE (~30%) for PC ranging between ~80 and 500 mg m−3. Application of the approach to Landsat 8 measurements over Lake Dianchi suggests potential use of the approach for periodical assessment of the lake’s bloom conditions, yet its empirical nature together with the lack of specific narrow bands on Landsat sensors to explicitly account for the PC absorption around 625 nm calls for extra caution when applied to other eutrophic lakes.

© 2015 Optical Society of America

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2014 (3)

L. Qi, C. Hu, H. Duan, J. Cannizzaro, and R. Ma, “A novel MERIS algorithm to derive cyanobacterial phycocyanin pigment concentrations in a eutrophic lake: Theoretical basis and practical considerations,” Remote Sens. Environ. 154, 298–317 (2014).
[Crossref]

B. B. Barnes, C. Hu, L. H. Kara, B. Slawomir, A. S. Bruce, P. David, and L. Brian, “Use of Landsat data to track historical water quality changes in Florida Keys marine environments,” Remote Sens. Environ. 140, 485–496 (2014).
[Crossref]

H. Duan, R. Ma, Y. Zhang, and S. A. Loiselle, “Are algal blooms occurring later in Lake Taihu? Climate local effects outcompete mitigation prevention,” J. Plankton Res. 36(3), 866–871 (2014).
[Crossref]

2013 (4)

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

C. Hu, L. Feng, and Z. Lee, “Uncertainties of SeaWiFS and MODIS remote sensing reflectance: Implications from clear water measurements,” Remote Sens. Environ. 133, 168–182 (2013).
[Crossref]

M. Wang, S. Son, Y. L. Zhang, and W. Shi, “Remote sensing of water optical property for China’s inland Lake Taihu using the SWIR atmospheric correction with 1640 and 2130nm bands,” IEEE J. Sel. Top. Appl. Ear. Observ. Remote Sens. 6(6), 2505–2516 (2013).
[Crossref]

D. Y. Sun, Y. M. Li, Q. Wang, J. Gao, C. Le, C. Huang, and S. Gong, “Hyperspectral remote sensing of the Pigment C-Phycocyanin in turbid inland waters, based on optical classification,” IEEE Trans. Geosci. Rem. Sens. 51(7), 3871–3883 (2013).
[Crossref]

2012 (1)

D. Y. Sun, Y. M. Li, Q. Wang, C. F. Le, H. Lv, C. C. Huang, and S. Q. Gong, “Specific inherent optical quantities of complex turbid inland waters, from the perspective of water classification,” Photochem. Photobiol. Sci. 11(8), 1299–1312 (2012).
[Crossref] [PubMed]

2011 (5)

M. Wang, W. Shi, and J. Tang, “Water property monitoring and assessment for China’s inland lake Taihu from MODIS-Aqua measurements,” Remote Sens. Environ. 115(3), 841–854 (2011).
[Crossref]

P. Dash, N. D. Walker, D. R. Mishra, C. Hu, J. L. Pinckney, and E. J. D’Sa, “Estimation of cyanobacterial pigments in a freshwater lake using OCM satellite data,” Remote Sens. Environ. 115(12), 3409–3423 (2011).
[Crossref]

M. W. Matthews, “A current review of empirical procedures of remote sensing in inland and near-coastal transitional waters,” Int. J. Remote Sens. 32(21), 6855–6899 (2011).
[Crossref]

R. Stone, “Ecology. China aims to turn tide against toxic lake pollution,” Science 333(6047), 1210–1211 (2011).
[Crossref] [PubMed]

H. W. Paerl, H. Xu, M. J. McCarthy, G. Zhu, B. Qin, Y. Li, and W. S. Gardner, “Controlling harmful cyanobacterial blooms in a hyper-eutrophic lake (Lake Taihu, China): The need for a dual nutrient (N & P) management strategy,” Water Res. 45(5), 1973–1983 (2011).
[Crossref] [PubMed]

2010 (4)

C. Hu, Z. Lee, R. Ma, K. Yu, D. Li, and S. Shang, “Moderate Resolution Imaging Spectroradiometer (MODIS) observations of cyanobacteria blooms in Taihu Lake, China,” J. Geophys. Res. 115(C4), C04002 (2010), doi:.
[Crossref]

P. D. Hunter, A. N. Tyler, L. Garvalho, G. A. Godd, and S. C. Maberly, “Hyperspectral remote sensing of cyanobacterial pigments as indicators for cell populations and toxins in eutrophic lakes,” Remote Sens. Environ. 114(11), 2705–2718 (2010).
[Crossref]

N. Feng, F. Mao, X. Y. Li, and A. D. Zhang, “Research on ecological security assessment of Dian Lake,” Environ. Sci. 31(2), 282–286 (2010).

D. Y. Sun, Y. M. Li, Q. Wang, C. F. Le, C. C. Huang, and S. Q. Gong, “Partitioning particulate scattering and absorption into contributions of phytoplankton and non-algal particles in winter in Lake Taihu (China),” Hydrobiologia 644(1), 337–349 (2010).
[Crossref]

2009 (5)

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

T. Kutser, “Passive optical remote sensing of cyanobacteria and other intense phytoplankton blooms in coastal and inland waters,” Int. J. Remote Sens. 30(17), 4401–4425 (2009).
[Crossref]

H. Duan, R. Ma, X. Xu, F. Kong, S. Zhang, W. Kong, J. Hao, and L. Shang, “Two-decade reconstruction of algal blooms in China’s Lake Taihu,” Environ. Sci. Technol. 43(10), 3522–3528 (2009).
[Crossref] [PubMed]

C. Le, Y. Li, Y. Zha, D. Sun, C. Huang, and H. Lu, “A four-band semi-analytical model for estimating chlorophyll a in highly turbid lakes: The case of Taihu Lake, China,” Remote Sens. Environ. 113(6), 1175–1182 (2009).
[Crossref]

P. D. Hunter, A. N. Tyler, D. J. Gilvear, and N. J. Willby, “Using remote sensing to aid the assessment of human health risks from blooms of potentially toxic cyanobacteria,” Environ. Sci. Technol. 43(7), 2627–2633 (2009).
[Crossref] [PubMed]

2008 (6)

A. Ruiz-Verdú, S. G. H. Simis, C. de Hoyos, H. J. Gons, and R. Peña-Martínez, “An evaluation of algorithms for the remote sensing of cyanobacterial biomass,” Remote Sens. Environ. 112(11), 3996–4008 (2008).
[Crossref]

H. J. Gons, M. T. Auer, and S. W. Effler, “MERIS satellite chlorophyll mapping of oligotrophic and eutrophic waters in the Laurentian Great Lakes,” Remote Sens. Environ. 112(11), 4098–4106 (2008).
[Crossref]

P. D. Hunter, A. N. Tyler, N. J. Willby, and D. J. Gilvear, “The spatial dynamics of vertical migration by Microcystis aeruginosa in a eutrophic shallow lake: a case study using high spatial resolution time-series airborne remote sensing,” Limnol. Oceanogr. 53(6), 2391–2406 (2008).
[Crossref]

N. Wan, L. Song, R. Wang, and J. Liu, “The spatio-temporal distribution of algal biomass in Dianchi Lake and its impact factors,” ACTA Hydrobiologica SINICA 32(2), 184–188 (2008).
[Crossref]

Y. Dai, S. Li, and X. Wang, “Measurement of analysis on the apparent optical properties of water in Chaohu Lake,” China Environ. Sci. 28, 979–983 (2008).

K. Randolph, J. Wilson, L. Tedesco, L. Li, D. L. Pascual, and E. Soyeux, “Hyperspectral remote sensing of cyanobacteria in turbid productive water using optically active pigments, chlorophyll a and phycocyanin,” Remote Sens. Environ. 112(11), 4009–4019 (2008).
[Crossref]

2007 (3)

A. A. Gitelson, J. F. Schalles, and C. M. Hladik, “Remote chlorophyll-a retrieval in turbid, productive estuaries: Cheapeake Bay case study,” Remote Sens. Environ. 109(4), 464–472 (2007).
[Crossref]

S. G. H. Simis, A. Ruiz-Verdú, J. A. Domínguez-Gómez, R. Peña-Martinez, S. W. M. Peters, and H. J. Gons, “Influence of phytoplankton pigment composition on remote sensing of cyanobacterial biomass,” Remote Sens. Environ. 106(4), 414–427 (2007).
[Crossref]

Y. Huot, M. Babin, F. Bruyant, C. Grob, M. S. Twardowski, and H. Claustre, “Relationship between photosynthetic parameters and different proxies of phytoplankton biomass in the subtropical ocean,” Biogeosciences 4(5), 853–868 (2007).
[Crossref]

2006 (2)

Y. W. Chen, K. N. Chen, and Y. H. Hu, “Discussion on possible error for phytoplankton chlorophyll-a concentration analysis using hot-ethanol extraction method,” J. Lake Sci. 18(5), 550–552 (2006).

M. Zhang, Y. Li, and R. Wang, “Dynamic variation for the species of phytoplankton in Dianchi Lake, China,” J. Yunnan Univers. 28(1), 73–77 (2006).

2005 (5)

L. Gao, J. M. Zhou, H. Yang, and J. Chen, “Phosphorus fractions in sediment profiles and their potential contributions to eutrophication in Dianchi Lake,” Environ. Geolo. 48(7), 835–844 (2005).
[Crossref]

S. G. H. Simis, S. W. M. Peters, and H. J. Gons, “Remote sensing of the cyanobacteria pigment phycocyanin in turbid inland water,” Limnol. Oceanogr. 50(1), 237–245 (2005).
[Crossref]

H. Sasaki, T. Miyamura, S. Saitoh, and J. Ishizaka, “Seasonal variation of absorption by particles and colored dissolved organic matter (CDOM) in Funka Bay, southwestern Hokkaido, Japan,” Estuar. Coast. Shelf Sci. 64(2-3), 447–458 (2005).
[Crossref]

M. Wang and W. Shi, “Estimation of ocean contribution at the MODIS near-infrared wavelengths along the east coast of the U.S.: Two case studies,” Geophys. Res. Lett. 32, L13606 (2005) doi:136.
[Crossref]

G. Dall’Olmo and A. A. Gitelson, “Effect of bio-optical parameter variability on the remote estimation of chlorophyll-a concentration in turbid productive waters: experimental results,” Appl. Opt. 44(3), 412–422 (2005).
[Crossref] [PubMed]

2004 (2)

R. K. Vincent, X. Qin, R. Michael, L. McKay, J. Miner, K. Czajkowski, J. Savino, and T. Bridgeman, “Phycocyanin detection from LANDSAT TM data from mapping cyanobacterial blooms in Lake Erie,” Remote Sens. Environ. 89(3), 381–392 (2004).
[Crossref]

J. W. Tang, G. L. Tian, X. Y. Wang, X. M. Wang, and Q. J. Song, “Methods of water spectra measurement and analysis I: Above water method,” J. Remote Sens. 8(1), 37–44 (2004).

2003 (2)

G. Dall’Olmo, A.-A. Gitelson, and D.-C. Rundquist, “Towards a unified approach for the remote estimation of chlorophyll-a in both terrestrial vegetation and turbid productive waters,” Geophys. Res. Lett. 30(18), 1938 (2003), doi:.
[Crossref]

V. H. Smith, “Eutrophication of freshwater and coastal marine ecosystems: A global problem,” Environ. Sci. Pollut. Res. Int. 10(2), 126–139 (2003).
[Crossref] [PubMed]

2001 (2)

N. Johnson, C. Revenga, and J. Echeverria, “Ecology. Managing water for people and nature,” Science 292(5519), 1071–1072 (2001).
[Crossref] [PubMed]

C. Hu, F. E. Muller-Karger, S. Andrefouet, and K. L. Carder, “Atmospheric Correction and Cross-Calibration of Landsat-7/ETM+ Imagery over Aquatic Environments: A Multiplantform Approach Using SeaWiFS/MODIS,” Remote Sens. Environ. 78(1-2), 99–107 (2001).
[Crossref]

2000 (2)

W. Wu, “Eutrophication in Dianchi Lake and its algae resource,” Environ. Sci. Yunnan 19, 35–37 (2000).

J. F. Schalles and Y. Z. Yacobi, “Remote detection and seasonal patterns of phycocyanin, carotenoid and chlorophyll pigments in eutrophic waters,” Ergebnisser der Limnolgie 55, 153–168 (2000).

1999 (3)

H.-J. Gons, “Optical teledetection of chlorophyll a in turbid inland waters,” Environ. Sci. Technol. 33(7), 1127–1132 (1999).
[Crossref]

R. Sarada, M. G. Pillai, and G. A. Ravishankar, “Phycocyanin from Spirulina sp: influence of processing of biomass on phycocyanin yield, analysis of efficacy of extraction methods and stability studies on phycocyanin,” Process Biochem. 34(8), 795–801 (1999).
[Crossref]

C. D. Mobley, “Estimation of the remote-sensing reflectance from above-surface measurements,” Appl. Opt. 38(36), 7442–7455 (1999).
[Crossref] [PubMed]

1997 (1)

L. Han and D.-C. Rundquist, “Comparison of NIR/RED ratio and first derivative of reflectance in estimating algal-chlorophyll concentration: A case study in a turbid reservoir,” Remote Sens. Environ. 62(3), 253–261 (1997).
[Crossref]

1994 (3)

M. Wang and H. R. Gordon, “A simple, moderately accurate, atmospheric correction algorithm for SeaWiFS,” Remote Sens. Environ. 50(3), 231–239 (1994).
[Crossref]

S. Green and N. Blough, “Optical absorption and fluorescence properties of chomophoric dissolved organic matter in natural waters,” Limnol. Oceanogr. 39(8), 1903–1916 (1994).
[Crossref]

Z. P. Lee, K. L. Carder, S. K. Hawes, R. G. Steward, T. G. Peacock, and C. O. Davis, “Model for the interpretation of hyperspectral remote-sensing reflectance,” Appl. Opt. 33(24), 5721–5732 (1994).
[Crossref] [PubMed]

1993 (1)

J. S. Cleveland and A. D. Weidemann, “Quantifying absorption by aquatic particles: a multiple scattering correction for glass-fiber filters,” Limnol. Oceanogr. 38(6), 1321–1327 (1993).
[Crossref]

1992 (1)

A. A. Gitelson, “The peak near 700 nm on radiance spectra of algae and water: relationships of its magnitude and position with chlorophyll concentration,” Int. J. Remote Sens. 13(17), 3367–3373 (1992).
[Crossref]

1985 (1)

M. Kishino, N. Takahashi, N. Okami, and S. Ichimura, “Estimation of the spectral absorption coefficients of phytoplankton in the sea,” Bull. Mar. Sci. 37, 634–642 (1985).

1981 (1)

A. Bricaud, A. Morel, and L. Prieur, “Absorption by dissolved organic matter in the sea (yellow substance) in the UV and visible domain,” Limnol. Oceanogr. 26(1), 43–53 (1981).
[Crossref]

1967 (1)

C. J. Lorenzen, “Determination of chlorophyll and phaeopigments: spectrophotometric equations,” Limnol. Oceanogr. 12(2), 343–346 (1967).
[Crossref]

Andrefouet, S.

C. Hu, F. E. Muller-Karger, S. Andrefouet, and K. L. Carder, “Atmospheric Correction and Cross-Calibration of Landsat-7/ETM+ Imagery over Aquatic Environments: A Multiplantform Approach Using SeaWiFS/MODIS,” Remote Sens. Environ. 78(1-2), 99–107 (2001).
[Crossref]

Auer, M. T.

H. J. Gons, M. T. Auer, and S. W. Effler, “MERIS satellite chlorophyll mapping of oligotrophic and eutrophic waters in the Laurentian Great Lakes,” Remote Sens. Environ. 112(11), 4098–4106 (2008).
[Crossref]

Babin, M.

Y. Huot, M. Babin, F. Bruyant, C. Grob, M. S. Twardowski, and H. Claustre, “Relationship between photosynthetic parameters and different proxies of phytoplankton biomass in the subtropical ocean,” Biogeosciences 4(5), 853–868 (2007).
[Crossref]

Barnes, B. B.

B. B. Barnes, C. Hu, L. H. Kara, B. Slawomir, A. S. Bruce, P. David, and L. Brian, “Use of Landsat data to track historical water quality changes in Florida Keys marine environments,” Remote Sens. Environ. 140, 485–496 (2014).
[Crossref]

Blough, N.

S. Green and N. Blough, “Optical absorption and fluorescence properties of chomophoric dissolved organic matter in natural waters,” Limnol. Oceanogr. 39(8), 1903–1916 (1994).
[Crossref]

Brian, L.

B. B. Barnes, C. Hu, L. H. Kara, B. Slawomir, A. S. Bruce, P. David, and L. Brian, “Use of Landsat data to track historical water quality changes in Florida Keys marine environments,” Remote Sens. Environ. 140, 485–496 (2014).
[Crossref]

Bricaud, A.

A. Bricaud, A. Morel, and L. Prieur, “Absorption by dissolved organic matter in the sea (yellow substance) in the UV and visible domain,” Limnol. Oceanogr. 26(1), 43–53 (1981).
[Crossref]

Bridgeman, T.

R. K. Vincent, X. Qin, R. Michael, L. McKay, J. Miner, K. Czajkowski, J. Savino, and T. Bridgeman, “Phycocyanin detection from LANDSAT TM data from mapping cyanobacterial blooms in Lake Erie,” Remote Sens. Environ. 89(3), 381–392 (2004).
[Crossref]

Bruce, A. S.

B. B. Barnes, C. Hu, L. H. Kara, B. Slawomir, A. S. Bruce, P. David, and L. Brian, “Use of Landsat data to track historical water quality changes in Florida Keys marine environments,” Remote Sens. Environ. 140, 485–496 (2014).
[Crossref]

Bruyant, F.

Y. Huot, M. Babin, F. Bruyant, C. Grob, M. S. Twardowski, and H. Claustre, “Relationship between photosynthetic parameters and different proxies of phytoplankton biomass in the subtropical ocean,” Biogeosciences 4(5), 853–868 (2007).
[Crossref]

Cannizzaro, J.

L. Qi, C. Hu, H. Duan, J. Cannizzaro, and R. Ma, “A novel MERIS algorithm to derive cyanobacterial phycocyanin pigment concentrations in a eutrophic lake: Theoretical basis and practical considerations,” Remote Sens. Environ. 154, 298–317 (2014).
[Crossref]

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

Carder, K. L.

C. Hu, F. E. Muller-Karger, S. Andrefouet, and K. L. Carder, “Atmospheric Correction and Cross-Calibration of Landsat-7/ETM+ Imagery over Aquatic Environments: A Multiplantform Approach Using SeaWiFS/MODIS,” Remote Sens. Environ. 78(1-2), 99–107 (2001).
[Crossref]

Z. P. Lee, K. L. Carder, S. K. Hawes, R. G. Steward, T. G. Peacock, and C. O. Davis, “Model for the interpretation of hyperspectral remote-sensing reflectance,” Appl. Opt. 33(24), 5721–5732 (1994).
[Crossref] [PubMed]

Chen, J.

L. Gao, J. M. Zhou, H. Yang, and J. Chen, “Phosphorus fractions in sediment profiles and their potential contributions to eutrophication in Dianchi Lake,” Environ. Geolo. 48(7), 835–844 (2005).
[Crossref]

Chen, K. N.

Y. W. Chen, K. N. Chen, and Y. H. Hu, “Discussion on possible error for phytoplankton chlorophyll-a concentration analysis using hot-ethanol extraction method,” J. Lake Sci. 18(5), 550–552 (2006).

Chen, Y. W.

Y. W. Chen, K. N. Chen, and Y. H. Hu, “Discussion on possible error for phytoplankton chlorophyll-a concentration analysis using hot-ethanol extraction method,” J. Lake Sci. 18(5), 550–552 (2006).

Claustre, H.

Y. Huot, M. Babin, F. Bruyant, C. Grob, M. S. Twardowski, and H. Claustre, “Relationship between photosynthetic parameters and different proxies of phytoplankton biomass in the subtropical ocean,” Biogeosciences 4(5), 853–868 (2007).
[Crossref]

Cleveland, J. S.

J. S. Cleveland and A. D. Weidemann, “Quantifying absorption by aquatic particles: a multiple scattering correction for glass-fiber filters,” Limnol. Oceanogr. 38(6), 1321–1327 (1993).
[Crossref]

Czajkowski, K.

R. K. Vincent, X. Qin, R. Michael, L. McKay, J. Miner, K. Czajkowski, J. Savino, and T. Bridgeman, “Phycocyanin detection from LANDSAT TM data from mapping cyanobacterial blooms in Lake Erie,” Remote Sens. Environ. 89(3), 381–392 (2004).
[Crossref]

D’Sa, E. J.

P. Dash, N. D. Walker, D. R. Mishra, C. Hu, J. L. Pinckney, and E. J. D’Sa, “Estimation of cyanobacterial pigments in a freshwater lake using OCM satellite data,” Remote Sens. Environ. 115(12), 3409–3423 (2011).
[Crossref]

Dai, Y.

Y. Dai, S. Li, and X. Wang, “Measurement of analysis on the apparent optical properties of water in Chaohu Lake,” China Environ. Sci. 28, 979–983 (2008).

Dall’Olmo, G.

G. Dall’Olmo and A. A. Gitelson, “Effect of bio-optical parameter variability on the remote estimation of chlorophyll-a concentration in turbid productive waters: experimental results,” Appl. Opt. 44(3), 412–422 (2005).
[Crossref] [PubMed]

G. Dall’Olmo, A.-A. Gitelson, and D.-C. Rundquist, “Towards a unified approach for the remote estimation of chlorophyll-a in both terrestrial vegetation and turbid productive waters,” Geophys. Res. Lett. 30(18), 1938 (2003), doi:.
[Crossref]

Dash, P.

P. Dash, N. D. Walker, D. R. Mishra, C. Hu, J. L. Pinckney, and E. J. D’Sa, “Estimation of cyanobacterial pigments in a freshwater lake using OCM satellite data,” Remote Sens. Environ. 115(12), 3409–3423 (2011).
[Crossref]

David, P.

B. B. Barnes, C. Hu, L. H. Kara, B. Slawomir, A. S. Bruce, P. David, and L. Brian, “Use of Landsat data to track historical water quality changes in Florida Keys marine environments,” Remote Sens. Environ. 140, 485–496 (2014).
[Crossref]

Davis, C. O.

de Hoyos, C.

A. Ruiz-Verdú, S. G. H. Simis, C. de Hoyos, H. J. Gons, and R. Peña-Martínez, “An evaluation of algorithms for the remote sensing of cyanobacterial biomass,” Remote Sens. Environ. 112(11), 3996–4008 (2008).
[Crossref]

Domínguez-Gómez, J. A.

S. G. H. Simis, A. Ruiz-Verdú, J. A. Domínguez-Gómez, R. Peña-Martinez, S. W. M. Peters, and H. J. Gons, “Influence of phytoplankton pigment composition on remote sensing of cyanobacterial biomass,” Remote Sens. Environ. 106(4), 414–427 (2007).
[Crossref]

Duan, H.

L. Qi, C. Hu, H. Duan, J. Cannizzaro, and R. Ma, “A novel MERIS algorithm to derive cyanobacterial phycocyanin pigment concentrations in a eutrophic lake: Theoretical basis and practical considerations,” Remote Sens. Environ. 154, 298–317 (2014).
[Crossref]

H. Duan, R. Ma, Y. Zhang, and S. A. Loiselle, “Are algal blooms occurring later in Lake Taihu? Climate local effects outcompete mitigation prevention,” J. Plankton Res. 36(3), 866–871 (2014).
[Crossref]

H. Duan, R. Ma, X. Xu, F. Kong, S. Zhang, W. Kong, J. Hao, and L. Shang, “Two-decade reconstruction of algal blooms in China’s Lake Taihu,” Environ. Sci. Technol. 43(10), 3522–3528 (2009).
[Crossref] [PubMed]

Echeverria, J.

N. Johnson, C. Revenga, and J. Echeverria, “Ecology. Managing water for people and nature,” Science 292(5519), 1071–1072 (2001).
[Crossref] [PubMed]

Effler, S. W.

H. J. Gons, M. T. Auer, and S. W. Effler, “MERIS satellite chlorophyll mapping of oligotrophic and eutrophic waters in the Laurentian Great Lakes,” Remote Sens. Environ. 112(11), 4098–4106 (2008).
[Crossref]

English, D.

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

Feng, L.

C. Hu, L. Feng, and Z. Lee, “Uncertainties of SeaWiFS and MODIS remote sensing reflectance: Implications from clear water measurements,” Remote Sens. Environ. 133, 168–182 (2013).
[Crossref]

Feng, N.

N. Feng, F. Mao, X. Y. Li, and A. D. Zhang, “Research on ecological security assessment of Dian Lake,” Environ. Sci. 31(2), 282–286 (2010).

Gao, J.

D. Y. Sun, Y. M. Li, Q. Wang, J. Gao, C. Le, C. Huang, and S. Gong, “Hyperspectral remote sensing of the Pigment C-Phycocyanin in turbid inland waters, based on optical classification,” IEEE Trans. Geosci. Rem. Sens. 51(7), 3871–3883 (2013).
[Crossref]

Gao, L.

L. Gao, J. M. Zhou, H. Yang, and J. Chen, “Phosphorus fractions in sediment profiles and their potential contributions to eutrophication in Dianchi Lake,” Environ. Geolo. 48(7), 835–844 (2005).
[Crossref]

Gardner, W. S.

H. W. Paerl, H. Xu, M. J. McCarthy, G. Zhu, B. Qin, Y. Li, and W. S. Gardner, “Controlling harmful cyanobacterial blooms in a hyper-eutrophic lake (Lake Taihu, China): The need for a dual nutrient (N & P) management strategy,” Water Res. 45(5), 1973–1983 (2011).
[Crossref] [PubMed]

Garvalho, L.

P. D. Hunter, A. N. Tyler, L. Garvalho, G. A. Godd, and S. C. Maberly, “Hyperspectral remote sensing of cyanobacterial pigments as indicators for cell populations and toxins in eutrophic lakes,” Remote Sens. Environ. 114(11), 2705–2718 (2010).
[Crossref]

Gilvear, D. J.

P. D. Hunter, A. N. Tyler, D. J. Gilvear, and N. J. Willby, “Using remote sensing to aid the assessment of human health risks from blooms of potentially toxic cyanobacteria,” Environ. Sci. Technol. 43(7), 2627–2633 (2009).
[Crossref] [PubMed]

P. D. Hunter, A. N. Tyler, N. J. Willby, and D. J. Gilvear, “The spatial dynamics of vertical migration by Microcystis aeruginosa in a eutrophic shallow lake: a case study using high spatial resolution time-series airborne remote sensing,” Limnol. Oceanogr. 53(6), 2391–2406 (2008).
[Crossref]

Gitelson, A. A.

A. A. Gitelson, J. F. Schalles, and C. M. Hladik, “Remote chlorophyll-a retrieval in turbid, productive estuaries: Cheapeake Bay case study,” Remote Sens. Environ. 109(4), 464–472 (2007).
[Crossref]

G. Dall’Olmo and A. A. Gitelson, “Effect of bio-optical parameter variability on the remote estimation of chlorophyll-a concentration in turbid productive waters: experimental results,” Appl. Opt. 44(3), 412–422 (2005).
[Crossref] [PubMed]

A. A. Gitelson, “The peak near 700 nm on radiance spectra of algae and water: relationships of its magnitude and position with chlorophyll concentration,” Int. J. Remote Sens. 13(17), 3367–3373 (1992).
[Crossref]

Gitelson, A.-A.

G. Dall’Olmo, A.-A. Gitelson, and D.-C. Rundquist, “Towards a unified approach for the remote estimation of chlorophyll-a in both terrestrial vegetation and turbid productive waters,” Geophys. Res. Lett. 30(18), 1938 (2003), doi:.
[Crossref]

Godd, G. A.

P. D. Hunter, A. N. Tyler, L. Garvalho, G. A. Godd, and S. C. Maberly, “Hyperspectral remote sensing of cyanobacterial pigments as indicators for cell populations and toxins in eutrophic lakes,” Remote Sens. Environ. 114(11), 2705–2718 (2010).
[Crossref]

Gong, S.

D. Y. Sun, Y. M. Li, Q. Wang, J. Gao, C. Le, C. Huang, and S. Gong, “Hyperspectral remote sensing of the Pigment C-Phycocyanin in turbid inland waters, based on optical classification,” IEEE Trans. Geosci. Rem. Sens. 51(7), 3871–3883 (2013).
[Crossref]

Gong, S. Q.

D. Y. Sun, Y. M. Li, Q. Wang, C. F. Le, H. Lv, C. C. Huang, and S. Q. Gong, “Specific inherent optical quantities of complex turbid inland waters, from the perspective of water classification,” Photochem. Photobiol. Sci. 11(8), 1299–1312 (2012).
[Crossref] [PubMed]

D. Y. Sun, Y. M. Li, Q. Wang, C. F. Le, C. C. Huang, and S. Q. Gong, “Partitioning particulate scattering and absorption into contributions of phytoplankton and non-algal particles in winter in Lake Taihu (China),” Hydrobiologia 644(1), 337–349 (2010).
[Crossref]

Gons, H. J.

A. Ruiz-Verdú, S. G. H. Simis, C. de Hoyos, H. J. Gons, and R. Peña-Martínez, “An evaluation of algorithms for the remote sensing of cyanobacterial biomass,” Remote Sens. Environ. 112(11), 3996–4008 (2008).
[Crossref]

H. J. Gons, M. T. Auer, and S. W. Effler, “MERIS satellite chlorophyll mapping of oligotrophic and eutrophic waters in the Laurentian Great Lakes,” Remote Sens. Environ. 112(11), 4098–4106 (2008).
[Crossref]

S. G. H. Simis, A. Ruiz-Verdú, J. A. Domínguez-Gómez, R. Peña-Martinez, S. W. M. Peters, and H. J. Gons, “Influence of phytoplankton pigment composition on remote sensing of cyanobacterial biomass,” Remote Sens. Environ. 106(4), 414–427 (2007).
[Crossref]

S. G. H. Simis, S. W. M. Peters, and H. J. Gons, “Remote sensing of the cyanobacteria pigment phycocyanin in turbid inland water,” Limnol. Oceanogr. 50(1), 237–245 (2005).
[Crossref]

Gons, H.-J.

H.-J. Gons, “Optical teledetection of chlorophyll a in turbid inland waters,” Environ. Sci. Technol. 33(7), 1127–1132 (1999).
[Crossref]

Gordon, H. R.

M. Wang and H. R. Gordon, “A simple, moderately accurate, atmospheric correction algorithm for SeaWiFS,” Remote Sens. Environ. 50(3), 231–239 (1994).
[Crossref]

Green, S.

S. Green and N. Blough, “Optical absorption and fluorescence properties of chomophoric dissolved organic matter in natural waters,” Limnol. Oceanogr. 39(8), 1903–1916 (1994).
[Crossref]

Grob, C.

Y. Huot, M. Babin, F. Bruyant, C. Grob, M. S. Twardowski, and H. Claustre, “Relationship between photosynthetic parameters and different proxies of phytoplankton biomass in the subtropical ocean,” Biogeosciences 4(5), 853–868 (2007).
[Crossref]

Han, L.

L. Han and D.-C. Rundquist, “Comparison of NIR/RED ratio and first derivative of reflectance in estimating algal-chlorophyll concentration: A case study in a turbid reservoir,” Remote Sens. Environ. 62(3), 253–261 (1997).
[Crossref]

Hao, J.

H. Duan, R. Ma, X. Xu, F. Kong, S. Zhang, W. Kong, J. Hao, and L. Shang, “Two-decade reconstruction of algal blooms in China’s Lake Taihu,” Environ. Sci. Technol. 43(10), 3522–3528 (2009).
[Crossref] [PubMed]

Hawes, S. K.

Hladik, C. M.

A. A. Gitelson, J. F. Schalles, and C. M. Hladik, “Remote chlorophyll-a retrieval in turbid, productive estuaries: Cheapeake Bay case study,” Remote Sens. Environ. 109(4), 464–472 (2007).
[Crossref]

Hu, C.

B. B. Barnes, C. Hu, L. H. Kara, B. Slawomir, A. S. Bruce, P. David, and L. Brian, “Use of Landsat data to track historical water quality changes in Florida Keys marine environments,” Remote Sens. Environ. 140, 485–496 (2014).
[Crossref]

L. Qi, C. Hu, H. Duan, J. Cannizzaro, and R. Ma, “A novel MERIS algorithm to derive cyanobacterial phycocyanin pigment concentrations in a eutrophic lake: Theoretical basis and practical considerations,” Remote Sens. Environ. 154, 298–317 (2014).
[Crossref]

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

C. Hu, L. Feng, and Z. Lee, “Uncertainties of SeaWiFS and MODIS remote sensing reflectance: Implications from clear water measurements,” Remote Sens. Environ. 133, 168–182 (2013).
[Crossref]

P. Dash, N. D. Walker, D. R. Mishra, C. Hu, J. L. Pinckney, and E. J. D’Sa, “Estimation of cyanobacterial pigments in a freshwater lake using OCM satellite data,” Remote Sens. Environ. 115(12), 3409–3423 (2011).
[Crossref]

C. Hu, Z. Lee, R. Ma, K. Yu, D. Li, and S. Shang, “Moderate Resolution Imaging Spectroradiometer (MODIS) observations of cyanobacteria blooms in Taihu Lake, China,” J. Geophys. Res. 115(C4), C04002 (2010), doi:.
[Crossref]

C. Hu, F. E. Muller-Karger, S. Andrefouet, and K. L. Carder, “Atmospheric Correction and Cross-Calibration of Landsat-7/ETM+ Imagery over Aquatic Environments: A Multiplantform Approach Using SeaWiFS/MODIS,” Remote Sens. Environ. 78(1-2), 99–107 (2001).
[Crossref]

Hu, Y. H.

Y. W. Chen, K. N. Chen, and Y. H. Hu, “Discussion on possible error for phytoplankton chlorophyll-a concentration analysis using hot-ethanol extraction method,” J. Lake Sci. 18(5), 550–552 (2006).

Huang, C.

D. Y. Sun, Y. M. Li, Q. Wang, J. Gao, C. Le, C. Huang, and S. Gong, “Hyperspectral remote sensing of the Pigment C-Phycocyanin in turbid inland waters, based on optical classification,” IEEE Trans. Geosci. Rem. Sens. 51(7), 3871–3883 (2013).
[Crossref]

C. Le, Y. Li, Y. Zha, D. Sun, C. Huang, and H. Lu, “A four-band semi-analytical model for estimating chlorophyll a in highly turbid lakes: The case of Taihu Lake, China,” Remote Sens. Environ. 113(6), 1175–1182 (2009).
[Crossref]

Huang, C. C.

D. Y. Sun, Y. M. Li, Q. Wang, C. F. Le, H. Lv, C. C. Huang, and S. Q. Gong, “Specific inherent optical quantities of complex turbid inland waters, from the perspective of water classification,” Photochem. Photobiol. Sci. 11(8), 1299–1312 (2012).
[Crossref] [PubMed]

D. Y. Sun, Y. M. Li, Q. Wang, C. F. Le, C. C. Huang, and S. Q. Gong, “Partitioning particulate scattering and absorption into contributions of phytoplankton and non-algal particles in winter in Lake Taihu (China),” Hydrobiologia 644(1), 337–349 (2010).
[Crossref]

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

Hunter, P. D.

P. D. Hunter, A. N. Tyler, L. Garvalho, G. A. Godd, and S. C. Maberly, “Hyperspectral remote sensing of cyanobacterial pigments as indicators for cell populations and toxins in eutrophic lakes,” Remote Sens. Environ. 114(11), 2705–2718 (2010).
[Crossref]

P. D. Hunter, A. N. Tyler, D. J. Gilvear, and N. J. Willby, “Using remote sensing to aid the assessment of human health risks from blooms of potentially toxic cyanobacteria,” Environ. Sci. Technol. 43(7), 2627–2633 (2009).
[Crossref] [PubMed]

P. D. Hunter, A. N. Tyler, N. J. Willby, and D. J. Gilvear, “The spatial dynamics of vertical migration by Microcystis aeruginosa in a eutrophic shallow lake: a case study using high spatial resolution time-series airborne remote sensing,” Limnol. Oceanogr. 53(6), 2391–2406 (2008).
[Crossref]

Huot, Y.

Y. Huot, M. Babin, F. Bruyant, C. Grob, M. S. Twardowski, and H. Claustre, “Relationship between photosynthetic parameters and different proxies of phytoplankton biomass in the subtropical ocean,” Biogeosciences 4(5), 853–868 (2007).
[Crossref]

Ichimura, S.

M. Kishino, N. Takahashi, N. Okami, and S. Ichimura, “Estimation of the spectral absorption coefficients of phytoplankton in the sea,” Bull. Mar. Sci. 37, 634–642 (1985).

Ishizaka, J.

H. Sasaki, T. Miyamura, S. Saitoh, and J. Ishizaka, “Seasonal variation of absorption by particles and colored dissolved organic matter (CDOM) in Funka Bay, southwestern Hokkaido, Japan,” Estuar. Coast. Shelf Sci. 64(2-3), 447–458 (2005).
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Kong, F.

H. Duan, R. Ma, X. Xu, F. Kong, S. Zhang, W. Kong, J. Hao, and L. Shang, “Two-decade reconstruction of algal blooms in China’s Lake Taihu,” Environ. Sci. Technol. 43(10), 3522–3528 (2009).
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H. Duan, R. Ma, X. Xu, F. Kong, S. Zhang, W. Kong, J. Hao, and L. Shang, “Two-decade reconstruction of algal blooms in China’s Lake Taihu,” Environ. Sci. Technol. 43(10), 3522–3528 (2009).
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C. Le, C. Hu, J. Cannizzaro, D. English, and C. Kovach, “Climate-driven chlorophyll a changes in a turbid estuary: Observation from satellites and implications for management,” Remote Sens. Environ. 130, 11–24 (2013).
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C. Le, Y. Li, Y. Zha, D. Sun, C. Huang, and H. Lu, “A four-band semi-analytical model for estimating chlorophyll a in highly turbid lakes: The case of Taihu Lake, China,” Remote Sens. Environ. 113(6), 1175–1182 (2009).
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D. Y. Sun, Y. M. Li, Q. Wang, C. F. Le, H. Lv, C. C. Huang, and S. Q. Gong, “Specific inherent optical quantities of complex turbid inland waters, from the perspective of water classification,” Photochem. Photobiol. Sci. 11(8), 1299–1312 (2012).
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D. Y. Sun, Y. M. Li, Q. Wang, C. F. Le, C. C. Huang, and L. Z. Wang, “Parameterization of water component absorption in inland entrophic lake and its seasonal variability, a case study in Lake Taihu,” Int. J. Remote Sens. 30(13), 3549–3571 (2009).
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Li, D.

C. Hu, Z. Lee, R. Ma, K. Yu, D. Li, and S. Shang, “Moderate Resolution Imaging Spectroradiometer (MODIS) observations of cyanobacteria blooms in Taihu Lake, China,” J. Geophys. Res. 115(C4), C04002 (2010), doi:.
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H. W. Paerl, H. Xu, M. J. McCarthy, G. Zhu, B. Qin, Y. Li, and W. S. Gardner, “Controlling harmful cyanobacterial blooms in a hyper-eutrophic lake (Lake Taihu, China): The need for a dual nutrient (N & P) management strategy,” Water Res. 45(5), 1973–1983 (2011).
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H. W. Paerl, H. Xu, M. J. McCarthy, G. Zhu, B. Qin, Y. Li, and W. S. Gardner, “Controlling harmful cyanobacterial blooms in a hyper-eutrophic lake (Lake Taihu, China): The need for a dual nutrient (N & P) management strategy,” Water Res. 45(5), 1973–1983 (2011).
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L. Qi, C. Hu, H. Duan, J. Cannizzaro, and R. Ma, “A novel MERIS algorithm to derive cyanobacterial phycocyanin pigment concentrations in a eutrophic lake: Theoretical basis and practical considerations,” Remote Sens. Environ. 154, 298–317 (2014).
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H. Duan, R. Ma, X. Xu, F. Kong, S. Zhang, W. Kong, J. Hao, and L. Shang, “Two-decade reconstruction of algal blooms in China’s Lake Taihu,” Environ. Sci. Technol. 43(10), 3522–3528 (2009).
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B. B. Barnes, C. Hu, L. H. Kara, B. Slawomir, A. S. Bruce, P. David, and L. Brian, “Use of Landsat data to track historical water quality changes in Florida Keys marine environments,” Remote Sens. Environ. 140, 485–496 (2014).
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D. Y. Sun, Y. M. Li, Q. Wang, J. Gao, C. Le, C. Huang, and S. Gong, “Hyperspectral remote sensing of the Pigment C-Phycocyanin in turbid inland waters, based on optical classification,” IEEE Trans. Geosci. Rem. Sens. 51(7), 3871–3883 (2013).
[Crossref]

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M. Kishino, N. Takahashi, N. Okami, and S. Ichimura, “Estimation of the spectral absorption coefficients of phytoplankton in the sea,” Bull. Mar. Sci. 37, 634–642 (1985).

Tang, J.

M. Wang, W. Shi, and J. Tang, “Water property monitoring and assessment for China’s inland lake Taihu from MODIS-Aqua measurements,” Remote Sens. Environ. 115(3), 841–854 (2011).
[Crossref]

Tang, J. W.

J. W. Tang, G. L. Tian, X. Y. Wang, X. M. Wang, and Q. J. Song, “Methods of water spectra measurement and analysis I: Above water method,” J. Remote Sens. 8(1), 37–44 (2004).

Tedesco, L.

K. Randolph, J. Wilson, L. Tedesco, L. Li, D. L. Pascual, and E. Soyeux, “Hyperspectral remote sensing of cyanobacteria in turbid productive water using optically active pigments, chlorophyll a and phycocyanin,” Remote Sens. Environ. 112(11), 4009–4019 (2008).
[Crossref]

Tian, G. L.

J. W. Tang, G. L. Tian, X. Y. Wang, X. M. Wang, and Q. J. Song, “Methods of water spectra measurement and analysis I: Above water method,” J. Remote Sens. 8(1), 37–44 (2004).

Twardowski, M. S.

Y. Huot, M. Babin, F. Bruyant, C. Grob, M. S. Twardowski, and H. Claustre, “Relationship between photosynthetic parameters and different proxies of phytoplankton biomass in the subtropical ocean,” Biogeosciences 4(5), 853–868 (2007).
[Crossref]

Tyler, A. N.

P. D. Hunter, A. N. Tyler, L. Garvalho, G. A. Godd, and S. C. Maberly, “Hyperspectral remote sensing of cyanobacterial pigments as indicators for cell populations and toxins in eutrophic lakes,” Remote Sens. Environ. 114(11), 2705–2718 (2010).
[Crossref]

P. D. Hunter, A. N. Tyler, D. J. Gilvear, and N. J. Willby, “Using remote sensing to aid the assessment of human health risks from blooms of potentially toxic cyanobacteria,” Environ. Sci. Technol. 43(7), 2627–2633 (2009).
[Crossref] [PubMed]

P. D. Hunter, A. N. Tyler, N. J. Willby, and D. J. Gilvear, “The spatial dynamics of vertical migration by Microcystis aeruginosa in a eutrophic shallow lake: a case study using high spatial resolution time-series airborne remote sensing,” Limnol. Oceanogr. 53(6), 2391–2406 (2008).
[Crossref]

Vincent, R. K.

R. K. Vincent, X. Qin, R. Michael, L. McKay, J. Miner, K. Czajkowski, J. Savino, and T. Bridgeman, “Phycocyanin detection from LANDSAT TM data from mapping cyanobacterial blooms in Lake Erie,” Remote Sens. Environ. 89(3), 381–392 (2004).
[Crossref]

Walker, N. D.

P. Dash, N. D. Walker, D. R. Mishra, C. Hu, J. L. Pinckney, and E. J. D’Sa, “Estimation of cyanobacterial pigments in a freshwater lake using OCM satellite data,” Remote Sens. Environ. 115(12), 3409–3423 (2011).
[Crossref]

Wan, N.

N. Wan, L. Song, R. Wang, and J. Liu, “The spatio-temporal distribution of algal biomass in Dianchi Lake and its impact factors,” ACTA Hydrobiologica SINICA 32(2), 184–188 (2008).
[Crossref]

Wang, L. Z.

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

Wang, M.

M. Wang, S. Son, Y. L. Zhang, and W. Shi, “Remote sensing of water optical property for China’s inland Lake Taihu using the SWIR atmospheric correction with 1640 and 2130nm bands,” IEEE J. Sel. Top. Appl. Ear. Observ. Remote Sens. 6(6), 2505–2516 (2013).
[Crossref]

M. Wang, W. Shi, and J. Tang, “Water property monitoring and assessment for China’s inland lake Taihu from MODIS-Aqua measurements,” Remote Sens. Environ. 115(3), 841–854 (2011).
[Crossref]

M. Wang and W. Shi, “Estimation of ocean contribution at the MODIS near-infrared wavelengths along the east coast of the U.S.: Two case studies,” Geophys. Res. Lett. 32, L13606 (2005) doi:136.
[Crossref]

M. Wang and H. R. Gordon, “A simple, moderately accurate, atmospheric correction algorithm for SeaWiFS,” Remote Sens. Environ. 50(3), 231–239 (1994).
[Crossref]

Wang, Q.

D. Y. Sun, Y. M. Li, Q. Wang, J. Gao, C. Le, C. Huang, and S. Gong, “Hyperspectral remote sensing of the Pigment C-Phycocyanin in turbid inland waters, based on optical classification,” IEEE Trans. Geosci. Rem. Sens. 51(7), 3871–3883 (2013).
[Crossref]

D. Y. Sun, Y. M. Li, Q. Wang, C. F. Le, H. Lv, C. C. Huang, and S. Q. Gong, “Specific inherent optical quantities of complex turbid inland waters, from the perspective of water classification,” Photochem. Photobiol. Sci. 11(8), 1299–1312 (2012).
[Crossref] [PubMed]

D. Y. Sun, Y. M. Li, Q. Wang, C. F. Le, C. C. Huang, and S. Q. Gong, “Partitioning particulate scattering and absorption into contributions of phytoplankton and non-algal particles in winter in Lake Taihu (China),” Hydrobiologia 644(1), 337–349 (2010).
[Crossref]

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

Wang, R.

N. Wan, L. Song, R. Wang, and J. Liu, “The spatio-temporal distribution of algal biomass in Dianchi Lake and its impact factors,” ACTA Hydrobiologica SINICA 32(2), 184–188 (2008).
[Crossref]

M. Zhang, Y. Li, and R. Wang, “Dynamic variation for the species of phytoplankton in Dianchi Lake, China,” J. Yunnan Univers. 28(1), 73–77 (2006).

Wang, X.

Y. Dai, S. Li, and X. Wang, “Measurement of analysis on the apparent optical properties of water in Chaohu Lake,” China Environ. Sci. 28, 979–983 (2008).

Wang, X. M.

J. W. Tang, G. L. Tian, X. Y. Wang, X. M. Wang, and Q. J. Song, “Methods of water spectra measurement and analysis I: Above water method,” J. Remote Sens. 8(1), 37–44 (2004).

Wang, X. Y.

J. W. Tang, G. L. Tian, X. Y. Wang, X. M. Wang, and Q. J. Song, “Methods of water spectra measurement and analysis I: Above water method,” J. Remote Sens. 8(1), 37–44 (2004).

Weidemann, A. D.

J. S. Cleveland and A. D. Weidemann, “Quantifying absorption by aquatic particles: a multiple scattering correction for glass-fiber filters,” Limnol. Oceanogr. 38(6), 1321–1327 (1993).
[Crossref]

Willby, N. J.

P. D. Hunter, A. N. Tyler, D. J. Gilvear, and N. J. Willby, “Using remote sensing to aid the assessment of human health risks from blooms of potentially toxic cyanobacteria,” Environ. Sci. Technol. 43(7), 2627–2633 (2009).
[Crossref] [PubMed]

P. D. Hunter, A. N. Tyler, N. J. Willby, and D. J. Gilvear, “The spatial dynamics of vertical migration by Microcystis aeruginosa in a eutrophic shallow lake: a case study using high spatial resolution time-series airborne remote sensing,” Limnol. Oceanogr. 53(6), 2391–2406 (2008).
[Crossref]

Wilson, J.

K. Randolph, J. Wilson, L. Tedesco, L. Li, D. L. Pascual, and E. Soyeux, “Hyperspectral remote sensing of cyanobacteria in turbid productive water using optically active pigments, chlorophyll a and phycocyanin,” Remote Sens. Environ. 112(11), 4009–4019 (2008).
[Crossref]

Wu, W.

W. Wu, “Eutrophication in Dianchi Lake and its algae resource,” Environ. Sci. Yunnan 19, 35–37 (2000).

Xu, H.

H. W. Paerl, H. Xu, M. J. McCarthy, G. Zhu, B. Qin, Y. Li, and W. S. Gardner, “Controlling harmful cyanobacterial blooms in a hyper-eutrophic lake (Lake Taihu, China): The need for a dual nutrient (N & P) management strategy,” Water Res. 45(5), 1973–1983 (2011).
[Crossref] [PubMed]

Xu, X.

H. Duan, R. Ma, X. Xu, F. Kong, S. Zhang, W. Kong, J. Hao, and L. Shang, “Two-decade reconstruction of algal blooms in China’s Lake Taihu,” Environ. Sci. Technol. 43(10), 3522–3528 (2009).
[Crossref] [PubMed]

Yacobi, Y. Z.

J. F. Schalles and Y. Z. Yacobi, “Remote detection and seasonal patterns of phycocyanin, carotenoid and chlorophyll pigments in eutrophic waters,” Ergebnisser der Limnolgie 55, 153–168 (2000).

Yang, H.

L. Gao, J. M. Zhou, H. Yang, and J. Chen, “Phosphorus fractions in sediment profiles and their potential contributions to eutrophication in Dianchi Lake,” Environ. Geolo. 48(7), 835–844 (2005).
[Crossref]

Yu, K.

C. Hu, Z. Lee, R. Ma, K. Yu, D. Li, and S. Shang, “Moderate Resolution Imaging Spectroradiometer (MODIS) observations of cyanobacteria blooms in Taihu Lake, China,” J. Geophys. Res. 115(C4), C04002 (2010), doi:.
[Crossref]

Zha, Y.

C. Le, Y. Li, Y. Zha, D. Sun, C. Huang, and H. Lu, “A four-band semi-analytical model for estimating chlorophyll a in highly turbid lakes: The case of Taihu Lake, China,” Remote Sens. Environ. 113(6), 1175–1182 (2009).
[Crossref]

Zhang, A. D.

N. Feng, F. Mao, X. Y. Li, and A. D. Zhang, “Research on ecological security assessment of Dian Lake,” Environ. Sci. 31(2), 282–286 (2010).

Zhang, M.

M. Zhang, Y. Li, and R. Wang, “Dynamic variation for the species of phytoplankton in Dianchi Lake, China,” J. Yunnan Univers. 28(1), 73–77 (2006).

Zhang, S.

H. Duan, R. Ma, X. Xu, F. Kong, S. Zhang, W. Kong, J. Hao, and L. Shang, “Two-decade reconstruction of algal blooms in China’s Lake Taihu,” Environ. Sci. Technol. 43(10), 3522–3528 (2009).
[Crossref] [PubMed]

Zhang, Y.

H. Duan, R. Ma, Y. Zhang, and S. A. Loiselle, “Are algal blooms occurring later in Lake Taihu? Climate local effects outcompete mitigation prevention,” J. Plankton Res. 36(3), 866–871 (2014).
[Crossref]

Zhang, Y. L.

M. Wang, S. Son, Y. L. Zhang, and W. Shi, “Remote sensing of water optical property for China’s inland Lake Taihu using the SWIR atmospheric correction with 1640 and 2130nm bands,” IEEE J. Sel. Top. Appl. Ear. Observ. Remote Sens. 6(6), 2505–2516 (2013).
[Crossref]

Zhou, J. M.

L. Gao, J. M. Zhou, H. Yang, and J. Chen, “Phosphorus fractions in sediment profiles and their potential contributions to eutrophication in Dianchi Lake,” Environ. Geolo. 48(7), 835–844 (2005).
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Zhu, G.

H. W. Paerl, H. Xu, M. J. McCarthy, G. Zhu, B. Qin, Y. Li, and W. S. Gardner, “Controlling harmful cyanobacterial blooms in a hyper-eutrophic lake (Lake Taihu, China): The need for a dual nutrient (N & P) management strategy,” Water Res. 45(5), 1973–1983 (2011).
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ACTA Hydrobiologica SINICA (1)

N. Wan, L. Song, R. Wang, and J. Liu, “The spatio-temporal distribution of algal biomass in Dianchi Lake and its impact factors,” ACTA Hydrobiologica SINICA 32(2), 184–188 (2008).
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Appl. Opt. (3)

Biogeosciences (1)

Y. Huot, M. Babin, F. Bruyant, C. Grob, M. S. Twardowski, and H. Claustre, “Relationship between photosynthetic parameters and different proxies of phytoplankton biomass in the subtropical ocean,” Biogeosciences 4(5), 853–868 (2007).
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Bull. Mar. Sci. (1)

M. Kishino, N. Takahashi, N. Okami, and S. Ichimura, “Estimation of the spectral absorption coefficients of phytoplankton in the sea,” Bull. Mar. Sci. 37, 634–642 (1985).

China Environ. Sci. (1)

Y. Dai, S. Li, and X. Wang, “Measurement of analysis on the apparent optical properties of water in Chaohu Lake,” China Environ. Sci. 28, 979–983 (2008).

Environ. Geolo. (1)

L. Gao, J. M. Zhou, H. Yang, and J. Chen, “Phosphorus fractions in sediment profiles and their potential contributions to eutrophication in Dianchi Lake,” Environ. Geolo. 48(7), 835–844 (2005).
[Crossref]

Environ. Sci. (1)

N. Feng, F. Mao, X. Y. Li, and A. D. Zhang, “Research on ecological security assessment of Dian Lake,” Environ. Sci. 31(2), 282–286 (2010).

Environ. Sci. Pollut. Res. Int. (1)

V. H. Smith, “Eutrophication of freshwater and coastal marine ecosystems: A global problem,” Environ. Sci. Pollut. Res. Int. 10(2), 126–139 (2003).
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H.-J. Gons, “Optical teledetection of chlorophyll a in turbid inland waters,” Environ. Sci. Technol. 33(7), 1127–1132 (1999).
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P. D. Hunter, A. N. Tyler, D. J. Gilvear, and N. J. Willby, “Using remote sensing to aid the assessment of human health risks from blooms of potentially toxic cyanobacteria,” Environ. Sci. Technol. 43(7), 2627–2633 (2009).
[Crossref] [PubMed]

H. Duan, R. Ma, X. Xu, F. Kong, S. Zhang, W. Kong, J. Hao, and L. Shang, “Two-decade reconstruction of algal blooms in China’s Lake Taihu,” Environ. Sci. Technol. 43(10), 3522–3528 (2009).
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Environ. Sci. Yunnan (1)

W. Wu, “Eutrophication in Dianchi Lake and its algae resource,” Environ. Sci. Yunnan 19, 35–37 (2000).

Ergebnisser der Limnolgie (1)

J. F. Schalles and Y. Z. Yacobi, “Remote detection and seasonal patterns of phycocyanin, carotenoid and chlorophyll pigments in eutrophic waters,” Ergebnisser der Limnolgie 55, 153–168 (2000).

Estuar. Coast. Shelf Sci. (1)

H. Sasaki, T. Miyamura, S. Saitoh, and J. Ishizaka, “Seasonal variation of absorption by particles and colored dissolved organic matter (CDOM) in Funka Bay, southwestern Hokkaido, Japan,” Estuar. Coast. Shelf Sci. 64(2-3), 447–458 (2005).
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M. Wang and W. Shi, “Estimation of ocean contribution at the MODIS near-infrared wavelengths along the east coast of the U.S.: Two case studies,” Geophys. Res. Lett. 32, L13606 (2005) doi:136.
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G. Dall’Olmo, A.-A. Gitelson, and D.-C. Rundquist, “Towards a unified approach for the remote estimation of chlorophyll-a in both terrestrial vegetation and turbid productive waters,” Geophys. Res. Lett. 30(18), 1938 (2003), doi:.
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Hydrobiologia (1)

D. Y. Sun, Y. M. Li, Q. Wang, C. F. Le, C. C. Huang, and S. Q. Gong, “Partitioning particulate scattering and absorption into contributions of phytoplankton and non-algal particles in winter in Lake Taihu (China),” Hydrobiologia 644(1), 337–349 (2010).
[Crossref]

IEEE J. Sel. Top. Appl. Ear. Observ. Remote Sens. (1)

M. Wang, S. Son, Y. L. Zhang, and W. Shi, “Remote sensing of water optical property for China’s inland Lake Taihu using the SWIR atmospheric correction with 1640 and 2130nm bands,” IEEE J. Sel. Top. Appl. Ear. Observ. Remote Sens. 6(6), 2505–2516 (2013).
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IEEE Trans. Geosci. Rem. Sens. (1)

D. Y. Sun, Y. M. Li, Q. Wang, J. Gao, C. Le, C. Huang, and S. Gong, “Hyperspectral remote sensing of the Pigment C-Phycocyanin in turbid inland waters, based on optical classification,” IEEE Trans. Geosci. Rem. Sens. 51(7), 3871–3883 (2013).
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D. Y. Sun, Y. M. Li, Q. Wang, C. F. Le, C. C. Huang, and L. Z. Wang, “Parameterization of water component absorption in inland entrophic lake and its seasonal variability, a case study in Lake Taihu,” Int. J. Remote Sens. 30(13), 3549–3571 (2009).
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J. Geophys. Res. (1)

C. Hu, Z. Lee, R. Ma, K. Yu, D. Li, and S. Shang, “Moderate Resolution Imaging Spectroradiometer (MODIS) observations of cyanobacteria blooms in Taihu Lake, China,” J. Geophys. Res. 115(C4), C04002 (2010), doi:.
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Y. W. Chen, K. N. Chen, and Y. H. Hu, “Discussion on possible error for phytoplankton chlorophyll-a concentration analysis using hot-ethanol extraction method,” J. Lake Sci. 18(5), 550–552 (2006).

J. Plankton Res. (1)

H. Duan, R. Ma, Y. Zhang, and S. A. Loiselle, “Are algal blooms occurring later in Lake Taihu? Climate local effects outcompete mitigation prevention,” J. Plankton Res. 36(3), 866–871 (2014).
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J. Remote Sens. (1)

J. W. Tang, G. L. Tian, X. Y. Wang, X. M. Wang, and Q. J. Song, “Methods of water spectra measurement and analysis I: Above water method,” J. Remote Sens. 8(1), 37–44 (2004).

J. Yunnan Univers. (1)

M. Zhang, Y. Li, and R. Wang, “Dynamic variation for the species of phytoplankton in Dianchi Lake, China,” J. Yunnan Univers. 28(1), 73–77 (2006).

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P. D. Hunter, A. N. Tyler, N. J. Willby, and D. J. Gilvear, “The spatial dynamics of vertical migration by Microcystis aeruginosa in a eutrophic shallow lake: a case study using high spatial resolution time-series airborne remote sensing,” Limnol. Oceanogr. 53(6), 2391–2406 (2008).
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S. G. H. Simis, S. W. M. Peters, and H. J. Gons, “Remote sensing of the cyanobacteria pigment phycocyanin in turbid inland water,” Limnol. Oceanogr. 50(1), 237–245 (2005).
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J. S. Cleveland and A. D. Weidemann, “Quantifying absorption by aquatic particles: a multiple scattering correction for glass-fiber filters,” Limnol. Oceanogr. 38(6), 1321–1327 (1993).
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D. Y. Sun, Y. M. Li, Q. Wang, C. F. Le, H. Lv, C. C. Huang, and S. Q. Gong, “Specific inherent optical quantities of complex turbid inland waters, from the perspective of water classification,” Photochem. Photobiol. Sci. 11(8), 1299–1312 (2012).
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R. Sarada, M. G. Pillai, and G. A. Ravishankar, “Phycocyanin from Spirulina sp: influence of processing of biomass on phycocyanin yield, analysis of efficacy of extraction methods and stability studies on phycocyanin,” Process Biochem. 34(8), 795–801 (1999).
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S. G. H. Simis, A. Ruiz-Verdú, J. A. Domínguez-Gómez, R. Peña-Martinez, S. W. M. Peters, and H. J. Gons, “Influence of phytoplankton pigment composition on remote sensing of cyanobacterial biomass,” Remote Sens. Environ. 106(4), 414–427 (2007).
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M. Wang, W. Shi, and J. Tang, “Water property monitoring and assessment for China’s inland lake Taihu from MODIS-Aqua measurements,” Remote Sens. Environ. 115(3), 841–854 (2011).
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C. Hu, F. E. Muller-Karger, S. Andrefouet, and K. L. Carder, “Atmospheric Correction and Cross-Calibration of Landsat-7/ETM+ Imagery over Aquatic Environments: A Multiplantform Approach Using SeaWiFS/MODIS,” Remote Sens. Environ. 78(1-2), 99–107 (2001).
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B. B. Barnes, C. Hu, L. H. Kara, B. Slawomir, A. S. Bruce, P. David, and L. Brian, “Use of Landsat data to track historical water quality changes in Florida Keys marine environments,” Remote Sens. Environ. 140, 485–496 (2014).
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A. A. Gitelson, J. F. Schalles, and C. M. Hladik, “Remote chlorophyll-a retrieval in turbid, productive estuaries: Cheapeake Bay case study,” Remote Sens. Environ. 109(4), 464–472 (2007).
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C. Le, C. Hu, J. Cannizzaro, D. English, and C. Kovach, “Climate-driven chlorophyll a changes in a turbid estuary: Observation from satellites and implications for management,” Remote Sens. Environ. 130, 11–24 (2013).
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C. Hu, L. Feng, and Z. Lee, “Uncertainties of SeaWiFS and MODIS remote sensing reflectance: Implications from clear water measurements,” Remote Sens. Environ. 133, 168–182 (2013).
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K. Randolph, J. Wilson, L. Tedesco, L. Li, D. L. Pascual, and E. Soyeux, “Hyperspectral remote sensing of cyanobacteria in turbid productive water using optically active pigments, chlorophyll a and phycocyanin,” Remote Sens. Environ. 112(11), 4009–4019 (2008).
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R. K. Vincent, X. Qin, R. Michael, L. McKay, J. Miner, K. Czajkowski, J. Savino, and T. Bridgeman, “Phycocyanin detection from LANDSAT TM data from mapping cyanobacterial blooms in Lake Erie,” Remote Sens. Environ. 89(3), 381–392 (2004).
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A. Ruiz-Verdú, S. G. H. Simis, C. de Hoyos, H. J. Gons, and R. Peña-Martínez, “An evaluation of algorithms for the remote sensing of cyanobacterial biomass,” Remote Sens. Environ. 112(11), 3996–4008 (2008).
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C. Le, Y. Li, Y. Zha, D. Sun, C. Huang, and H. Lu, “A four-band semi-analytical model for estimating chlorophyll a in highly turbid lakes: The case of Taihu Lake, China,” Remote Sens. Environ. 113(6), 1175–1182 (2009).
[Crossref]

P. D. Hunter, A. N. Tyler, L. Garvalho, G. A. Godd, and S. C. Maberly, “Hyperspectral remote sensing of cyanobacterial pigments as indicators for cell populations and toxins in eutrophic lakes,” Remote Sens. Environ. 114(11), 2705–2718 (2010).
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P. Dash, N. D. Walker, D. R. Mishra, C. Hu, J. L. Pinckney, and E. J. D’Sa, “Estimation of cyanobacterial pigments in a freshwater lake using OCM satellite data,” Remote Sens. Environ. 115(12), 3409–3423 (2011).
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Figures (9)

Fig. 1
Fig. 1

Eutrophication levels of typical inland lakes of China in 2013 (China’s Environmental Bulletin, 2013). The dotted lines on the x-axis denote lakes that are not shown due to the limited space.

Fig. 2
Fig. 2

Location of Lake Dianchi in China, with sampling stations overlaid on a background Red-Green-Blue image of Landsat 8 OLI collected on 23 April 2014.

Fig. 3
Fig. 3

Schematic flow chart showing the steps to derive Rrs(λ) from Landsat-measured ρt(λ) (Eqs. (2-5). ρrc(λ) in the chart is equal to ρt(λ) – ρr(λ).

Fig. 4
Fig. 4

PC and Chla measured from discrete sampling stations of Lake Dianchi during two cruise surveys in September and December 2009. Note that the first 3 stations are in the north of the lake (see Fig. 2).

Fig. 5
Fig. 5

A: Individual Rrs(λ) spectra from in situ measurements in Lake Dianchi. B: Normalized Rrs(λ) by 675nm (i.e., Rrs(λ)/Rrs(675)). C: Contributions of OSM and ISM to TSM in Lake Dianchi (n = 28). D: Relationship between field-measured PC and Chla in Lake Dianchi. Blue: Sep. 2009; Red: Dec. 2009. E: Mean absorption contribution of phytoplankton pigments, non-algal particles, and CDOM to the total absorption (at-w, excluding pure water), determined from the 28 water samples of Lake Dianchi. The dashed rectangles denote the Landsat 8 OLI band positions.

Fig. 6
Fig. 6

Scatter-plots of PC model calibration between measured and modeled PC (n = 14). The model used simulated Landsat Rrs and multivariate regression analysis (Eq. (10), with coefficients listed in Table 3).

Fig. 7
Fig. 7

Scatter-plots of PC model validation between measured and model-predicted PC. An independent data set (n = 14) was used in the validation.

Fig. 8
Fig. 8

Atmosphere and water properties derived from Landsat 8 OLI data collected on 23 April 2014.

Fig. 9
Fig. 9

Performance of three existing PC-retrieval models over the field-collected data from Lake Dianchi. Two results were obtained for each model: the model calibration result (left column) using 14 samples, and the model validation result using 14 other independent samples. These samples were the same as those used for the development and validation of the new PC-retrieval model in this study. A and B: Band ratio quadratic model [20]; C and D: Spectral slope exponential model [21]; E and F: Semi-analytical model [15].

Tables (5)

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Table 1 Statistics of the water quality parameters observed in Lake Dianchi from two cruise surveys in September and December 2009. SD: Standard deviation; CV: Coefficient of variation (%).

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Table 2 Spectral bands for the Landsat sensors, whose RSR functions were obtained from USGS and used to simulate Landsat-measured Rrs using field-measured Rrs (Eq. (9).

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Table 3 Coefficients of the multivariate regression model to estimate PC from simulated Landsat Rrs.

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Table 4 Coefficients of the multivariate regression for different PC/Chla ratio ranges. Group I (n = 19): PC:Chla<2.6; Group II (n = 9): PC:Chla>2.6. The mean PC:Chla ratio of all data in this study was 2.6 (Table 1). The input Rrs data were from in situ measurements but simulated to account for Landsat 8 OLI bandwidth.

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Table 5 Coefficients of the multivariate regression models for Chla, TSM, OSM, and ISM.

Equations (10)

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R rs (λ)=( L t r L sky )/(π L p / ρ p )
ρ t (λ)= ρ r (λ)+ ρ a (λ)+t(λ)T(λ)π R rs (λ)
ε( λ 1 , λ 0 ) ρ a ( λ 1 ) ρ a ( λ 0 ) = ρ t ( λ 1 ) ρ r ( λ 1 ) ρ t ( λ 0 ) ρ r ( λ 0 )
ε(λ, λ 0 )=exp[c( λ 0 λ)]
t(λ)=exp( τ r (λ) 2cosθ ) and T(λ)=exp( τ r (λ) 2cos θ 0 )
R 2 = i=1 n (P C pred i 1 n i=1 n P C meas i ) 2 i=1 n (P C meas i 1 n i=1 n P C meas i ) 2
MAPE= 1 n i=1 n | P C meas i P C pred i P C meas i | *100%
R E i = (P C meas i P C pred i ) P C meas i *100%
R rs (bi)= λ m λ n RSR(λ)* R rs_meas (λ)dλ λ m λ n RSR(λ)dλ
Lo g 10 (PC)= K 0 + K 1 R rs (b1)+ K 2 R rs (b2)+ K 3 R rs (b3)+ K 4 R rs (b4)+ K 5 R rs (b4)/ R rs (b3) + K 6 R rs (b4)/ R rs (b2)+ K 7 R rs (b4)/ R rs (b1)+ K 8 R rs (b3)/ R rs (b2) + K 9 R rs (b3)/ R rs (b1)+ K 10 R rs (b2)/ R rs (b1)

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