Revisiting empirical ocean-colour algorithms for remote estimation of chlorophyll-a content on a global scale

References

• Abramowitz, M., and I. A. Stegun. 1964. Handbook of Mathematical Functions: With Formulas, Graphs, and Mathematical Tables. New York, NY: Dover.
   Google Scholar
• Bailey, S. W., and P. Jeremy Werdell. 2006. “A Multi-Sensor Approach for the On-Orbit Validation of Ocean Color Satellite Data Products.” Remote Sensing of Environment 102 (1–2): 12–23. doi:10.1016/j.rse.2006.01.015.
   Web of Science ®Google Scholar
• Behrenfeld, M. J., D. A. Siegel, and R. T. O’Malley. 2008. “Global Ocean Phytoplankton and Productivity.” Bulletin of the American Meteorological Society 89 (7): S56–S61.
   Google Scholar
• Belsey, D. A., E. Kuh, and R. E. Welsch. 1980. Regression Diagnostics: Identifying Influential Data and Sources of Collinearity. New York, NY: John Wiley.
   Google Scholar
• Boyce, D. G., M. R. Lewis, and B. Worm. 2010. “Global Phytoplankton Decline over the past Century.” Nature 466 (7306): 591–596. doi:10.1038/nature09268.
   PubMed Web of Science ®Google Scholar
• Brewin, R. J. W., S. Sathyendranath, D. Müller, C. Brockmann, P.-Y. Deschamps, E. Devred, R. Doerffer, N. Fomferra, B. Franz, and M. Grant. 2015. “The Ocean Colour Climate Change Initiative: III. A Round-Robin Comparison on In-Water Bio-Optical Algorithms.” Remote Sensing of Environment 162 (1): 271–294. doi:10.1016/j.rse.2013.09.016.
   Web of Science ®Google Scholar
• Calinski, T., and J. Harabasz. 1974. “A Dendrite Method for Cluster Analysis.” Communications in Statistics-theory and Methods 3 (1): 1–27. doi:10.1080/03610927408827101.
   Google Scholar
• Campbell, J. W. 1995. “The Lognormal Distribution as a Model for Bio-Optical Variability in the Sea.” Journal of Geophysical Research: Oceans 100 (C7): 13237–13254. doi:10.1029/95JC00458.
   Web of Science ®Google Scholar
• Cannizzaro, J. P., and K. L. Carder. 2006. “Estimating Chlorophyll a Concentrations from Remote-Sensing Reflectance in Optically Shallow Waters.” Remote Sensing of Environment 101 (1): 13–24. doi:10.1016/j.rse.2005.12.002.
   Web of Science ®Google Scholar
• Charlton, M., S. Fotheringham, and C. Brunsdon. 2009. “Geographically Weighted Regression.” White paper. National Centre for Geocomputation. National University of Ireland Maynooth.
   Google Scholar
• Chatterjee, S., and B. Price. 1977. Regression Analysis by Example. New York, NY: John Wiley & Sons.
   Google Scholar
• Darecki, M., and D. Stramski. 2004. “An Evaluation of MODIS and SeaWiFS Bio-Optical Algorithms in the Baltic Sea.” Remote Sensing of Environment 89 (3): 326–350. doi:10.1016/j.rse.2003.10.012.
   Web of Science ®Google Scholar
• De Amorim, R. C., and B. Mirkin. 2012. “Minkowski Metric, Feature Weighting and Anomalous Cluster Initializing in K-Means Clustering.” Pattern Recognition 45 (3): 1061–1075. doi:10.1016/j.patcog.2011.08.012.
   Web of Science ®Google Scholar
• Dierssen, H. M. 2010. “Perspectives on Empirical Approaches for Ocean Color Remote Sensing of Chlorophyll in a Changing Climate.” Proceedings of the National Academy of Sciences 107 (40): 17073–17078. doi:10.1073/pnas.0913800107.
   PubMed Web of Science ®Google Scholar
• Doney, S. C. 2006. “Oceanography: Plankton in a Warmer World.” Nature 444 (7120): 695–696. doi:10.1038/444695a.
   PubMed Web of Science ®Google Scholar
• Dzwonkowski, B., and X.-H. Yan. 2005. “Development and Application of a Neural Network Based Ocean Colour Algorithm in Coastal Waters.” International Journal of Remote Sensing 26 (6): 1175–1200. doi:10.1080/01431160512331326549.
   Web of Science ®Google Scholar
• Falkowski, P., R. J. Scholes, E. E. A. Boyle, J. Canadell, D. Canfield, J. Elser, N. Gruber, K. Hibbard, P. Högberg, and S. Linder. 2000. “The Global Carbon Cycle: A Test of Our Knowledge of Earth as a System.” Science 290 (5490): 291–296. doi:10.1126/science.290.5490.291.
   PubMed Web of Science ®Google Scholar
• Ferreira, A., C. A. E. Garcia, A. I. Dogliotti, and V. M. T. Garcia. 2013. “Bio-Optical Characteristics of the Patagonia Shelf Break Waters: Implications for Ocean Color Algorithms.” Remote Sensing of Environment 136: 416–432. doi:10.1016/j.rse.2013.05.022.
   Web of Science ®Google Scholar
• Field, C. B., M. J. Behrenfeld, J. T. Randerson, and P. Falkowski. 1998. “Primary Production of the Biosphere: Integrating Terrestrial and Oceanic Components.” Science 281 (5374): 237–240. doi:10.1016/j.rse.2004.12.006.
   PubMed Web of Science ®Google Scholar
• Fotheringham, A. S., M. Charlton, and C. Brunsdon. 1996. “The Geography of Parameter Space: An Investigation of Spatial Non-Stationarity.” International Journal of Geographical Information Systems 10 (5): 605–627. doi:10.1080/026937996137909.
   Web of Science ®Google Scholar
• Garcia, C. A. E., V. M. T. Garcia, and C. R. McClain. 2005. “Evaluation of SeaWiFS Chlorophyll Algorithms in the Southwestern Atlantic and Southern Oceans.” Remote Sensing of Environment 95 (1): 125–137. doi:10.1016/j.rse.2004.12.006.
   Web of Science ®Google Scholar
• Garver, S. A., and D. A. Siegel. 1997. “Inherent Optical Property Inversion of Ocean Color Spectra and Its Biogeochemical Interpretation: 1. Time Series from the Sargasso Sea.” Journal of Geophysical Research: Oceans 102: 18607–18625. doi:10.1029/96JC03243.
   Web of Science ®Google Scholar
• Gitelson, A. A., G. Dall’Olmo, W. Moses, D. C. Rundquist, T. Barrow, T. R. Fisher, D. Gurlin, and J. Holz. 2008. “A Simple Semi-Analytical Model for Remote Estimation of Chlorophyll-a in Turbid Waters: Validation.” Remote Sensing of Environment 112 (9): 3582–3593. doi:10.1016/j.rse.2008.04.015.
   Web of Science ®Google Scholar
• Gohin, F., J. N. Druon, and L. Lampert. 2002. “A Five Channel Chlorophyll Concentration Algorithm Applied to SeaWiFS Data Processed by Seadas in Coastal Waters.” International Journal of Remote Sensing 23 (8): 1639–1661. doi:10.1080/01431160110071879.
   Web of Science ®Google Scholar
• Gregg, W. W., and N. W. Casey. 2004. “Global and Regional Evaluation of the SeaWiFS Chlorophyll Data Set.” Remote Sensing of Environment 93 (4): 463–479. doi:10.1016/j.rse.2003.12.012.
   Web of Science ®Google Scholar
• Gregg, W. W., and M. E. Conkright. 2001. “Global Seasonal Climatologies of Ocean Chlorophyll: Blending In Situ and Satellite Data for the Coastal Zone Color Scanner Era.” Journal of Geophysical Research: Oceans 106 (C2): 2499–2515. doi:10.1029/1999JC000028.
   Web of Science ®Google Scholar
• Hoepffner, N. 1991. “Effect of Pigment Composition on Absorption Properties of Phytoplankton.” Mar. Ecol. Prog. Ser. 73: 11–23. doi:10.3354/meps073011.
   Web of Science ®Google Scholar
• Hofmann, M., B. Worm, S. Rahmstorf, and H. J. Schellnhuber. 2011. “Declining Ocean Chlorophyll under Unabated Anthropogenic CO2 Emissions.” Environmental Research Letters 6 (3): 034035. doi:10.1088/1748-9326/6/3/034035.
   Google Scholar
• Hu, C., and J. Campbell. 2014. “Oceanic Chlorophyll-A Content.” In Biophysical Applications of Satellite Remote Sensing, Springer Remote Sensing/Photogrammetry, edited by J. M. Hanes, 171–203. Berlin: Springer.
   Google Scholar
• Hu, C., Z. Lee, and B. Franz. 2012. “Chlorophyll A Algorithms for Oligotrophic Oceans: A Novel Approach Based on Three-Band Reflectance Difference.” Journal of Geophysical Research: Oceans 117 : C01011. doi:10.1029/2011JC007395.
   Web of Science ®Google Scholar
• Huot, Y., B. A. Franz, and M. Fradette. 2013. “Estimating Variability in the Quantum Yield of Sun-Induced Chlorophyll Fluorescence: A Global Analysis of Oceanic Waters.” Remote Sensing of Environment 132: 238–253. doi:10.1016/j.rse.2013.01.003.
   Web of Science ®Google Scholar
• Hurvich, C. M., J. S. Simonoff, and C.-L. Tsai. 1998. “Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion.” Journal of the Royal Statistical Society: Series B (Statistical Methodology) 60 (2): 271–293. doi:10.1111/1467-9868.00125.
   Web of Science ®Google Scholar
• IOCCG. 2006. “Remote Sensing of Inherent Optical Properties: Fundamentals, Tests of Algorithms, and Applications.” Reports of the International Ocean-Colour Coordinating Group. No. 5, Dartmouth, Canada: IOCCG.
   Google Scholar
• Johnson, R., P. G. Strutton, S. W. Wright, A. McMinn, and K. M. Meiners. 2013. “Three Improved Satellite Chlorophyll Algorithms for the Southern Ocean.” Journal of Geophysical Research: Oceans 118: 3694–3703.
   Web of Science ®Google Scholar
• Kahru, M., S. T. Gille, R. Murtugudde, P. G. Strutton, M. Manzano-Sarabia, H. Wang, and B. G. Mitchell. 2010. “Global Correlations between Winds and Ocean Chlorophyll.” Journal of Geophysical Research: Oceans 115 : C12040. doi:10.1029/2010JC006500.
   Web of Science ®Google Scholar
• Kim, T.-W., R. G. Najjar, and K. Lee. 2014. “Influence of Precipitation Events on Phytoplankton Biomass in Coastal Waters of the Eastern United States.” Global Biogeochemical Cycles 28 (1): 1–13. doi:10.1002/2013GB004712.
   Web of Science ®Google Scholar
• Kutner, M. H., C. Nachtsheim, and J. Neter. 2004. Applied Linear Regression Models. New York, NY: McGraw-Hill/Irwin.
   Google Scholar
• Le, C., Y. Li, Y. Zha, D. Sun, C. Huang, and H. Lu. 2009. “A Four-Band Semi-Analytical Model for Estimating Chlorophyll A in Highly Turbid Lakes: The Case of Taihu Lake, China.” Remote Sensing of Environment 113 (6): 1175–1182. doi:10.1016/j.rse.2009.02.005.
   Web of Science ®Google Scholar
• Lesht, B. M., R. P. Barbiero, and G. J. Warren. 2013. “A Band-Ratio Algorithm for Retrieving Open-Lake Chlorophyll Values from Satellite Observations of the Great Lakes.” Journal of Great Lakes Research 39 (1): 138–152. doi:10.1016/j.jglr.2012.12.007.
   Web of Science ®Google Scholar
• Lohrenz, S. E., G. L. Fahnenstiel, D. F. Millie, O. M. E. Schofield, T. Johengen, and T. Bergmann. 2004. “Spring Phytoplankton Photosynthesis, Growth, and Primary Production and Relationships to a Recurrent Coastal Sediment Plume and River Inputs in Southeastern Lake Michigan.” Journal of Geophysical Research: Oceans 109 : C10S14. doi:10.1029/2004JC002383.
   Web of Science ®Google Scholar
• Maritorena, S., and D. A. Siegel. 2005. “Consistent Merging of Satellite Ocean Color Data Sets Using a Bio-Optical Model.” Remote Sensing of Environment 94 (4): 429–440. doi:10.1016/j.rse.2004.08.014.
   Web of Science ®Google Scholar
• Maritorena, S., D. A. Siegel, and A. R. Peterson. 2002. “Optimization of a Semianalytical Ocean Color Model for Global-Scale Applications.” Applied Optics 41 (15): 2705–2714. doi:10.1364/AO.41.002705.
   PubMed Web of Science ®Google Scholar
• Marrari, M., C. Hu, and K. Daly. 2006. “Validation of SeaWiFS Chlorophyll A Concentrations in the Southern Ocean: A Revisit.” Remote Sensing of Environment 105 (4): 367–375. doi:10.1016/j.rse.2006.07.008.
   Web of Science ®Google Scholar
• Massy, W. F. 1965. “Principal Components Regression in Exploratory Statistical Research.” Journal of the American Statistical Association 60 (309): 234–256. doi:10.1080/01621459.1965.10480787.
   Web of Science ®Google Scholar
• McClain, C. R. 2000. SeaWiFS Postlaunch Calibration and Validation Analyses. Greenbelt, MD: Goddard Space Flight Center.
   Google Scholar
• McKee, D., A. Cunningham, and A. Dudek. 2007. “Optical Water Type Discrimination and Tuning Remote Sensing Band-Ratio Algorithms: Application to Retrieval of Chlorophyll and K D (490) in the Irish and Celtic Seas.” Estuarine, Coastal and Shelf Science 73 (3–4): 827–834. doi:10.1016/j.ecss.2007.03.028.
   Web of Science ®Google Scholar
• Moore, J. K., M. R. Abbott, J. G. Richman, W. O. Smith, T. J. Cowles, K. H. Coale, W. D. Gardner, and R. T. Barber. 1999. “SeaWiFS Satellite Ocean Color Data from the Southern Ocean.” Geophysical Research Letters 26 (10): 1465–1468. doi:10.1029/1999GL900242.
   Web of Science ®Google Scholar
• Moore, T. S., J. W. Campbell, and M. D. Dowell. 2009. “A Class-Based Approach to Characterizing and Mapping the Uncertainty of the MODIS Ocean Chlorophyll Product.” Remote Sensing of Environment 113 (11): 2424–2430. doi:10.1016/j.rse.2009.07.016.
   Web of Science ®Google Scholar
• Morel, A., and S. Maritorena. 2001. “Bio-Optical Properties of Oceanic Waters: A Reappraisal.” Journal of Geophysical Research: Oceans 106 (C4): 7163–7180. doi:10.1029/2000JC000319.
   Web of Science ®Google Scholar
• O’Reilly, J. E., S. Maritorena, D. A. Siegel, M. C. O’Brien, D. Toole, B. G. Mitchell, M. Kahru, F. P. Chavez, P. Strutton, and G. F. Cota. 2000. “Ocean Color Chlorophyll a Algorithms for SeaWiFS OC2, and OC4: Version 4.” SeaWiFS Postlaunch Calibration and Validation Analyses, Part 3: 9–23.
   Google Scholar
• Odriozola, A. L., R. Varela, C. Hu, Y. Astor, L. Lorenzoni, and F. E. Müller-Karger. 2007. “On the Absorption of Light in the Orinoco River Plume.” Continental Shelf Research 27 (10–11): 1447–1464. doi:10.1016/j.csr.2007.01.012.
   Web of Science ®Google Scholar
• Pomeroy, L. R. 1974. “The Ocean’s Food Web, a Changing Paradigm.” Bioscience 24 (9): 499–504. doi:10.2307/1296885.
   Web of Science ®Google Scholar
• Racault, M.-F., S. Sathyendranath, and T. Platt. 2014. “Impact of Missing Data on the Estimation of Ecological Indicators from Satellite Ocean-Colour Time-Series.” Remote Sensing of Environment 152: 15–28. doi:10.1016/j.rse.2014.05.016.
   Web of Science ®Google Scholar
• Rawlings, J. O., S. G. Pantula, and D. A. Dickey. 1998. Applied Regression Analysis: A Research Tool. New York, NY: Springer.
   Google Scholar
• Satheesh, S. K., and J. Srinivasan. 2002. “Enhanced Aerosol Loading over Arabian Sea during the Pre-Monsoon Season: Natural or Anthropogenic?” Geophysical Research Letters 29: 21–24. doi:10.1029/2002GL015687.
   Web of Science ®Google Scholar
• Sathyendranath, S., G. Cota, V. Stuart, H. Maass, and T. Platt. 2001. “Remote Sensing of Phytoplankton Pigments: A Comparison of Empirical and Theoretical Approaches.” International Journal of Remote Sensing 22 (2–3): 249–273. doi:10.1080/014311601449925.
   Web of Science ®Google Scholar
• Sauer, M. J., C. S. Roesler, P. J. Werdell, and A. Barnard. 2012. “Under the Hood of Satellite Empirical Chlorophyll a Algorithms: Revealing the Dependencies of Maximum Band Ratio Algorithms on Inherent Optical Properties.” Optics Express 20 (19): 20920–20933. doi:10.1364/OE.20.020920.
   PubMed Web of Science ®Google Scholar
• Schlüter, L., K. T. Lohbeck, M. A. Gutowska, J. P. Gröger, U. Riebesell, and T. B. H. Reusch. 2014. “Adaptation of a Globally Important Coccolithophore to Ocean Warming and Acidification.” Nature Climate Change 4 (11): 1024–1030. doi:10.1038/nclimate2379.
   Web of Science ®Google Scholar
• Schwarz, G. 1978. “Estimating the Dimension of a Model.” The Annals of Statistics 6 (2): 461–464. doi:10.1214/aos/1176344136.
   Web of Science ®Google Scholar
• Siegel, D. A., S. Maritorena, N. B. Nelson, M. J. Behrenfeld, and C. R. McClain. 2005b. “Colored Dissolved Organic Matter and Its Influence on the Satellite‐Based Characterization of the Ocean Biosphere.” Geophysical Research Letters 32: L20605. doi:10.1029/2005GL024310.
   Google Scholar
• Siegel, D. A., S. Maritorena, N. B. Nelson, and M. J. Behrenfeld. 2005a. “Independence and Interdependencies among Global Ocean Color Properties: Reassessing the Bio‐Optical Assumption.” Journal of Geophysical Research: Oceans 110: C07011. doi:10.1029/2004JC002527.
   Web of Science ®Google Scholar
• Szeto, M., P. J. Werdell, T. S. Moore, and J. W. Campbell. 2011. “Are the World’s Oceans Optically Different?” Journal of Geophysical Research: Oceans 116: C00H04. doi:10.1029/2011JC007230.
   Web of Science ®Google Scholar
• Tang, S., C. Michel, and P. Larouche. 2012. “Development of an Explicit Algorithm for Remote Sensing Estimation of Chlorophyll a Using Symbolic Regression.” Optics Letters 37 (15): 3165–3167. doi:10.1364/OL.37.003165.
   PubMed Web of Science ®Google Scholar
• Toseland, A. D. S. J., S. J. Daines, J. R. Clark, A. Kirkham, J. Strauss, C. Uhlig, T. M. Lenton, K. Valentin, G. A. Pearson, and V. Moulton. 2013. “The Impact of Temperature on Marine Phytoplankton Resource Allocation and Metabolism.” Nature Climate Change 3 (11): 979–984. doi:10.1038/nclimate1989.
   Web of Science ®Google Scholar
• Tukey, J. W. 1977. Exploratory Data Analysis. Reading, MA: Addison-Wesley.
   Google Scholar
• van de Poll, W. H., G. Kulk, K. R. Timmermans, C. P. D. Brussaard, H. J. Van Der Woerd, M. J. Kehoe, K. D. A. Mojica, R. J. W. Visser, P. D. Rozema, and A. G. J. Buma. 2013. “Phytoplankton Chlorophyll a Biomass, Composition, and Productivity along a Temperature and Stratification Gradient in the Northeast Atlantic Ocean.” Biogeosciences 10 (6): 4227–4240. doi:10.5194/bg-10-4227-2013.
   Web of Science ®Google Scholar
• Viollier, M., P. Y. Deschamps, and P. Lecomte. 1978. “Airborne Remote Sensing of Chlorophyll Content under Cloudy Sky as Applied to the Tropical Waters in the Gulf of Guinea.” Remote Sensing of Environment 7 (3): 235–248. doi:10.1016/0034-4257(78)90035-4.
   Web of Science ®Google Scholar
• Werdell, P. J., and S. W. Bailey. 2005. “An Improved In-Situ Bio-Optical Data Set for Ocean Color Algorithm Development and Satellite Data Product Validation.” Remote Sensing of Environment 98 (1): 122–140. doi:10.1016/j.rse.2005.07.001.
   Web of Science ®Google Scholar
• Werdell, P. J., B. A. Franz, S. W. Bailey, G. C. Feldman, E. Boss, V. E. Brando, M. Dowell, T. Hirata, S. J. Lavender, and Z. Lee. 2013. “Generalized Ocean Color Inversion Model for Retrieving Marine Inherent Optical Properties.” Applied Optics 52 (10): 2019–2037. doi:10.1364/AO.52.002019.
   PubMed Web of Science ®Google Scholar
• Wold, H. 1966. “Estimation of Principal Components and Related Models by Iterative Least Squares.” Multivariate Analysis 1: 391–420.
   Google Scholar
• Woodward, R. B., W. A. Ayer, J. M. Beaton, F. Bickelhaupt, R. Bonnett, P. Buchschacher, G. L. Closs, H. Dutler, J. Hannah, and F. P. Hauck. 1990. “The Total Synthesis of Chlorophyll A.” Tetrahedron 46 (22): 7599–7659. doi:10.1016/0040-4020(90)80003-Z.
   Web of Science ®Google Scholar