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Canadian Journal of Remote Sensing
Journal canadien de télédétection
Volume 49, 2023 - Issue 1
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Research Article

Comparative Analysis of Empirical and Machine Learning Models for Chla Extraction Using Sentinel-2 and Landsat OLI Data: Opportunities, Limitations, and Challenges

Analyse comparative de modèles empiriques et d’apprentissage automatique pour l’extraction de la Chla à l’aide des données Sentinel-2 et Landsat OLI: opportunités, limites et défis

Amir M. Chegooniana Department of Geography and Environmental Management, University of Waterloo, 200 University Avenue West Waterloo, ON N2L 3G1, Canada;b Institute of Environmental Change and Society, University of Regina, 3737 Wascana Parkway, Regina, SK S4S 0A2, CanadaCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0003-0862-2763View further author information
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Nima Pahlevanc NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA;d Science Systems and Applications, Inc. (SSAI), Lanham, MD 20706, USAORCID Iconhttps://orcid.org/0000-0002-5454-5212View further author information
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Kiana Zolfagharia Department of Geography and Environmental Management, University of Waterloo, 200 University Avenue West Waterloo, ON N2L 3G1, CanadaORCID Iconhttps://orcid.org/0000-0002-4392-7143View further author information
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Peter R. Leavittb Institute of Environmental Change and Society, University of Regina, 3737 Wascana Parkway, Regina, SK S4S 0A2, CanadaORCID Iconhttps://orcid.org/0000-0001-9805-9307View further author information
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John-Mark Daviese Saskatchewan Water Security Agency, #10-3904 Millar Avenue, Saskatoon, SK S7P 0B1, Canada;f School of Environment and Sustainability, University of Saskatchewan, 105 Administration Place, Saskatoon, SK S7N 5A2, CanadaORCID Iconhttps://orcid.org/0000-0001-8884-0976View further author information
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Helen M. Baulchf School of Environment and Sustainability, University of Saskatchewan, 105 Administration Place, Saskatoon, SK S7N 5A2, CanadaORCID Iconhttps://orcid.org/0000-0001-9018-4998View further author information
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Claude R. Duguaya Department of Geography and Environmental Management, University of Waterloo, 200 University Avenue West Waterloo, ON N2L 3G1, Canada;g H2O Geomatics Inc., 151 Charles St W #100, Kitchener, ON N2G 1H6, CanadaORCID Iconhttps://orcid.org/0000-0002-1044-5850View further author information
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Article: 2215333 | Received 25 Aug 2022, Accepted 04 May 2023, Published online: 06 Jun 2023

References

  • Allan, M.G., Hamilton, D.P., Hicks, B.J., and Brabyn, L. 2011. “Landsat remote sensing of chlorophyll a concentrations in central North Island lakes of New Zealand.” International Journal of Remote Sensing, Vol. 32(No. 7): pp. 2037–2055. doi:10.1080/01431161003645840.
  • Ansper, A., and Alikas, K. 2018. “Retrieval of chlorophyll a from Sentinel-2 MSI data for the European Union water framework directive reporting purposes.” Remote Sensing, Vol. 11(No. 1): pp. 64. doi:10.3390/rs11010064.
  • Babin, M., Stramski, D., Ferrari, G.M., Claustre, H., Bricaud, A., Obolensky, G., and Hoepffner, N. 2003. “Variations in the light absorption coefficients of phytoplankton, nonalgal particles, and dissolved organic matter in coastal waters around Europe.” Journal of Geophysical Research, Vol. 108(No. C7): pp. 3211. doi:10.1029/2001JC000882.
  • Beck, R., Zhan, S., Liu, H., Tong, S., Yang, B., Xu, M., Ye, Z., et al. 2016. “Comparison of satellite reflectance algorithms for estimating chlorophyll-a in a temperate reservoir using coincident hyperspectral aircraft imagery and dense coincident surface observations.” Remote Sensing of Environment, Vol. 178: pp. 15–30. doi:10.1016/j.rse.2016.03.002.
  • Binding, C., Pizzolato, L., and Zeng, C. 2021. “EOLakeWatch; delivering a comprehensive suite of remote sensing algal bloom indices for enhanced monitoring of Canadian eutrophic lakes.” Ecological Indicators, Vol. 121: pp. 106999. doi:10.1016/j.ecolind.2020.106999.
  • Binding, C.E., Greenberg, T.A., and Bukata, R.P. 2011. “Time series analysis of algal blooms in Lake of the Woods using the MERIS maximum chlorophyll index.” Journal of Plankton Research, Vol. 33(No. 12): pp. 1847–1852. doi:10.1093/plankt/fbr079.
  • Bresciani, M., Cazzaniga, I., Austoni, M., Sforzi, T., Buzzi, F., Morabito, G., and Giardino, C. 2018. “Mapping phytoplankton blooms in deep subalpine lakes from Sentinel-2A and Landsat-8.” Hydrobiologia, Vol. 824(No. 1): pp. 197–214. doi:10.1007/s10750-017-3462-2.
  • Bryan, A.F., Werdell, P.J., Gerhard, M., Sean, W.B., Robert, E.E. Jr., Gene, C.F., Ewa, J.K., Charles, R.M., Frederick, S.P., and Donna, T. 2005. “The continuity of ocean color measurements from SeaWiFS to MODIS.” In Proc. SPIE.
  • Bulgarelli, B., and Zibordi, G. 2018. “On the detectability of adjacency effects in ocean color remote sensing of mid-latitude coastal environments by SeaWiFS, MODIS-A, MERIS, OLCI, OLI and MSI.” Remote Sensing of Environment, Vol. 209: pp. 423–438. doi:10.1016/j.rse.2017.12.021.
  • Camps-Valls, G., Gómez-Chova, L., Muñoz-Marí, J., Vila-Francés, J., Amorós-López, J., and Calpe-Maravilla, J. 2006. “Retrieval of oceanic chlorophyll concentration with relevance vector machines.” Remote Sensing of Environment, Vol. 105: pp. 23–33.
  • Cao, Z., Ma, R., Duan, H., Pahlevan, N., Melack, J., Shen, M., and Xue, K. 2020. “A machine learning approach to estimate chlorophyll-a from Landsat-8 measurements in inland lakes.” Remote Sensing of Environment, Vol. 248: pp. 111974. doi:10.1016/j.rse.2020.111974.
  • Cao, Z., Ma, R., Duan, H., and Xue, K. 2019. “Effects of broad bandwidth on the remote sensing of inland waters: Implications for high spatial resolution satellite data applications.” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 153: pp. 110–122. doi:10.1016/j.isprsjprs.2019.05.001.
  • Carder, K.L., Chen, F., Lee, Z., Hawes, S., and Kamykowski, D. 1999. “Semianalytic moderate‐resolution imaging spectrometer algorithms for chlorophyll a and absorption with bio‐optical domains based on nitrate‐depletion temperatures.” Journal of Geophysical Research: Oceans, Vol. 104(No. C3): pp. 5403–5421. doi:10.1029/1998JC900082.
  • Carpenter, S.R., Caraco, N.F., Correll, D.L., Howarth, R.W., Sharpley, A.N., and Smith, V.H. 1998. “Nonpoint pollution of surface waters with phosphorus and nitrogen.” Ecological Applications, Vol. 8(No. 3): pp. 559–568. doi:10.1890/1051-0761(1998)008[0559:NPOSWW].2.0.CO;2
  • Chegoonian, A., Mokhtarzade, M., and Valadan Zoej, M. 2017. “A comprehensive evaluation of classification algorithms for coral reef habitat mapping: Challenges related to quantity, quality, and impurity of training samples.” International Journal of Remote Sensing, Vol. 38(No. 14): pp. 4224–4243. doi:10.1080/01431161.2017.1317934.
  • Chegoonian, A.M., Zolfaghari, K., Baulch, H.M., and Duguay, C.R. 2021. “Support vector regression for chlorophyll-a estimation using Sentinel-2 images in small waterbodies.” In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, pp. 7449–7452. IEEE.
  • Chegoonian, A.M., Zolfaghari, K., Leavitt, P.R., Baulch, H.M., and Duguay, C.R. 2022. “Improvement of field fluorometry estimates of chlorophyll a concentration in a cyanobacteria‐rich eutrophic lake.” Limnology and Oceanography: Methods, Vol. 20(No. 4): pp. 193–209. doi:10.1002/lom3.10480.
  • Chen, T., and Guestrin, C. 2016. “Xgboost: A scalable tree boosting system.” In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 785–794.
  • Claverie, M., Ju, J., Masek, J.G., Dungan, J.L., Vermote, E.F., Roger, J.-C., Skakun, S.V., and Justice, C. 2018. “The harmonized Landsat and Sentinel-2 surface reflectance data set.” Remote Sensing of Environment, Vol. 219: pp. 145–161. doi:10.1016/j.rse.2018.09.002.
  • Clay, S., Peña, A., DeTracey, B., and Devred, E. 2019. “Evaluation of satellite-based algorithms to retrieve chlorophyll-a concentration in the Canadian Atlantic and Pacific Oceans.” Remote Sensing, Vol. 11(No. 22): pp. 2609. doi:10.3390/rs11222609.
  • Dall’Olmo, G., and Gitelson, A.A. 2005. “Effect of bio-optical parameter variability on the remote estimation of chlorophyll-a concentration in turbid productive waters: Experimental results.” Applied Optics, Vol. 44(No. 3): pp. 412–422. doi:10.1364/ao.44.000412.
  • De Keukelaere, L., Sterckx, S., Adriaensen, S., Knaeps, E., Reusen, I., Giardino, C., Bresciani, M., et al. 2018. “Atmospheric correction of Landsat-8/OLI and Sentinel-2/MSI data using iCOR algorithm: validation for coastal and inland waters.” European Journal of Remote Sensing, Vol. 51(No. 1): pp. 525–542. doi:10.1080/22797254.2018.1457937.
  • Defoin‐Platel, M., and Chami, M. 2007. “How ambiguous is the inverse problem of ocean color in coastal waters?” Journal of Geophysical Research, Vol. 112(No. C3): pp. 1–16. doi:10.1029/2006JC003847.
  • Delpla, I., Jung, A.V., Baures, E., Clement, M., and Thomas, O. 2009. “Impacts of climate change on surface water quality in relation to drinking water production.” Environment International, Vol. 35(No. 8): pp. 1225–1233. doi:10.1016/j.envint.2009.07.001.
  • Doerffer, R., and Schiller, H. 2007. “The MERIS Case 2 water algorithm.” International Journal of Remote Sensing, Vol. 28(No. 3–4): pp. 517–535. doi:10.1080/01431160600821127.
  • Dörnhöfer, K., Göritz, A., Gege, P., Pflug, B., and Oppelt, N. 2016. “Water constituents and water depth retrieval from Sentinel-2A—A first evaluation in an oligotrophic lake.” Remote Sensing, Vol. 8(No. 11): pp. 941. doi:10.3390/rs8110941.
  • Dörnhöfer, K., Klinger, P., Heege, T., and Oppelt, N. 2018. “Multi-sensor satellite and in situ monitoring of phytoplankton development in a eutrophic-mesotrophic lake.” The Science of the Total Environment, Vol. 612: pp. 1200–1214. doi:10.1016/j.scitotenv.2017.08.219.
  • Downing, J.A., Prairie, Y.T., Cole, J.J., Duarte, C.M., Tranvik, L.J., Striegl, R.G., McDowell, W.H., et al. 2006. “The global abundance and size distribution of lakes, ponds, and impoundments.” Limnology and Oceanography, Vol. 51(No. 5): pp. 2388–2397. doi:10.4319/lo.2006.51.5.2388.
  • Dröscher, I., Finlay, K., Patoine, A., and Leavitt, P.R. 2008. “Daphnia control of the spring clear-water phase in six polymictic lakes of varying productivity and size.” Internationale Vereinigung Für Theoretische Und Angewandte Limnologie: Verhandlungen, Vol. 30(No. 2): pp. 186–190. doi:10.1080/03680770.2008.11902107.
  • Eaton, A.D., Clesceri, L.S., Rice E.W. Greenberg, A.E., eds. 2017. Standard Methods for the Examination of Water and Wastewater. 23th ed. American Public Health Association, Method 10200H p 10:22–24.
  • Filazzola, A., Mahdiyan, O., Shuvo, A., Ewins, C., Moslenko, L., Sadid, T., Blagrave, K., et al. 2020. “A database of chlorophyll and water chemistry in freshwater lakes.” Scientific Data, Vol. 7(No. 1): pp. 310. doi:10.1038/s41597-020-00648-2.
  • Finlay, K., Vogt, R.J., Bogard, M.J., Wissel, B., Tutolo, B.M., Simpson, G.L., and Leavitt, P.R. 2015. “Decrease in CO2 efflux from northern hardwater lakes with increasing atmospheric warming.” Nature, Vol. 519(No. 7542): pp. 215–218. doi:10.1038/nature14172.
  • Foody, G.M., and Mathur, A. 2006. “The use of small training sets containing mixed pixels for accurate hard image classification: Training on mixed spectral responses for classification by a SVM.” Remote Sensing of Environment, Vol. 103(No. 2): pp. 179–189. doi:10.1016/j.rse.2006.04.001.
  • Gitelson, A. 1992. “The peak near 700 nm on radiance spectra of algae and water: Relationships of its magnitude and position with chlorophyll concentration.” International Journal of Remote Sensing, Vol. 13(No. 17): pp. 3367–3373. doi:10.1080/01431169208904125.
  • Gitelson, A.A., Schalles, J.F., and Hladik, C.M. 2007. “Remote chlorophyll-a retrieval in turbid, productive estuaries: Chesapeake Bay case study.” Remote Sensing of Environment, Vol. 109(No. 4): pp. 464–472. doi:10.1016/j.rse.2007.01.016.
  • Gons, H.J. 1999. “Optical teledetection of chlorophyll a in turbid inland waters.” Environmental Science & Technology, Vol. 33(No. 7): pp. 1127–1132. doi:10.1021/es9809657.
  • Gons, H.J., Auer, M.T., and Effler, S.W. 2008. “MERIS satellite chlorophyll mapping of oligotrophic and eutrophic waters in the Laurentian Great Lakes.” Remote Sensing of Environment, Vol. 112(No. 11): pp. 4098–4106. doi:10.1016/j.rse.2007.06.029.
  • Hayes, N.M., Haig, H.A., Simpson, G.L., and Leavitt, P.R. 2020. “Local and regional effects of lake warming on risk of toxic algal exposure.” Limnology and Oceanography Letters, Vol. 5(No. 6): pp. 393–402. doi:10.1002/lol2.10164.
  • Helder, D., Markham, B., Morfitt, R., Storey, J., Barsi, J., Gascon, F., Clerc, S., et al. 2018. “Observations and recommendations for the calibration of Landsat 8 OLI and Sentinel 2 MSI for improved data interoperability.” Remote Sensing, Vol. 10(No. 9): pp. 1340. doi:10.3390/rs10091340.
  • Ho, J.C., Michalak, A.M., and Pahlevan, N. 2019. “Widespread global increase in intense lake phytoplankton blooms since the 1980s.” Nature, Vol. 574(No. 7780): pp. 667–670. doi:10.1038/s41586-019-1648-7.
  • Hosseini, N., Akomeah, E., Davies, J.-M., Baulch, H., and Lindenschmidt, K.-E. 2018. “Water quality modeling of a prairie river-lake system.” Environmental Science and Pollution Research International, Vol. 25(No. 31): pp. 31190–31204. doi:10.1007/s11356-018-3055-2.
  • Hu, C., Feng, L., and Guan, Q. 2021. “A machine learning approach to estimate surface chlorophyll a concentrations in global oceans from satellite measurements.” IEEE Transactions on Geoscience and Remote Sensing, Vol. 59(No. 6): pp. 4590–4607. doi:10.1109/TGRS.2020.3016473.
  • Ilori, C.O., Pahlevan, N., and Knudby, A. 2019. “Analyzing performances of different atmospheric correction techniques for Landsat 8: Application for coastal remote sensing.” Remote Sensing, Vol. 11(No. 4): pp. 469. doi:10.3390/rs11040469.
  • IOCCG. 2006. Remote Sensing of Inherent Optical Properties: Fundamentals, Tests of Algorithms, and Applications. In Z.-P. Lee (Ed.), Reports of the international ocean-color coordinating group, No. 5. Dartmouth, Canada: IOCCG. doi:10.25607/OBP-96.
  • Jeffrey, S.W., and Humphrey, G.F. 1975. “New spectrophotometric equations for determining chlorophylls a, b, c1 and c2 in higher plants, algae and natural phytoplankton.” Biochemie Und Physiologie Der Pflanzen, Vol. 167(No. 2): pp. 191–194. doi:10.1016/S0015-3796(17)30778-3.
  • Kehoe, M., Ingalls, B., Venkiteswaran, J., and Baulch, H. 2019. “Successful forecasting of harmful cyanobacteria blooms with high frequency lake data.” bioRxiv, pp. 674325.
  • Kehoe, M.J., Chun, K.P., and Baulch, H.M. 2015. “Who smells? Forecasting taste and odor in a drinking water reservoir.” Environmental Science & Technology, Vol. 49(No. 18): pp. 10984–10992. doi:10.1021/acs.est.5b00979.
  • Kutser, T. 2009. “Passive optical remote sensing of cyanobacteria and other intense phytoplankton blooms in coastal and inland waters.” International Journal of Remote Sensing, Vol. 30(No. 17): pp. 4401–4425. doi:10.1080/01431160802562305.
  • Kutser, T., Paavel, B., Verpoorter, C., Ligi, M., Soomets, T., Toming, K., and Casal, G. 2016. “Remote sensing of black lakes and using 810 nm reflectance peak for retrieving water quality parameters of optically complex waters.” Remote Sensing, Vol. 8(No. 6): pp. 497. doi:10.3390/rs8060497.
  • Kwiatkowska, E.J., and Fargion, G.S. 2003. “Application of machine-learning techniques toward the creation of a consistent and calibrated global chlorophyll concentration baseline dataset using remotely sensed ocean color data.” IEEE Transactions on Geoscience and Remote Sensing, Vol. 41(No. 12): pp. 2844–2860. doi:10.1109/TGRS.2003.818016.
  • Leavitt, P., and Hodgson, D. 2001. Sedimentary Pigments. Tracking Environmental Change Using Lake Sediments. Volume 3: Terrestrial, Algal, and Siliceous Indicators. Dordrecht: Kluwer Academic Publishers.
  • Lee, Z., Carder, K.L., and Arnone, R.A. 2002. “Deriving inherent optical properties from water color: A multiband quasi-analytical algorithm for optically deep waters.” Applied Optics, Vol. 41(No. 27): pp. 5755–5772. doi:10.1364/ao.41.005755.
  • Li, A.H., and Bradic, J. 2018. “Boosting in the presence of outliers: Adaptive classification with nonconvex loss functions.” Journal of the American Statistical Association, Vol. 113(No. 522): pp. 660–674. doi:10.1080/01621459.2016.1273116.
  • Li, J., and Roy, D.P. 2017. “A global analysis of Sentinel-2A, Sentinel-2B and Landsat-8 data revisit intervals and implications for terrestrial monitoring.” Remote Sensing, Vol. 9(No. 9): pp. 902. doi:10.3390/rs9090902.
  • Li, S., Ganguly, S., Dungan, J.L., Wang, W., and Nemani, R.R. 2017. “Sentinel-2 MSI radiometric characterization and cross-calibration with Landsat-8 OLI.” Advances in Remote Sensing, Vol. 6(No. 2): pp. 147–159. doi:10.4236/ars.2017.62011.
  • Lunetta, R.S., Schaeffer, B.A., Stumpf, R.P., Keith, D., Jacobs, S.A., and Murphy, M.S. 2015. “Evaluation of cyanobacteria cell count detection derived from MERIS imagery across the eastern USA.” Remote Sensing of Environment, Vol. 157: pp. 24–34. doi:10.1016/j.rse.2014.06.008.
  • Martinez, E., Gorgues, T., Lengaigne, M., Fontana, C., Sauzède, R., Menkes, C., Uitz, J., Di Lorenzo, E., and Fablet, R. 2020. “Reconstructing global chlorophyll-a variations using a non-linear statistical approach.” Frontiers in Marine Science, Vol. 7: pp. 464. doi:10.3389/fmars.2020.00464.
  • Matthews, M.W., Bernard, S., and Robertson, L. 2012. “An algorithm for detecting trophic status (chlorophyll-a), cyanobacterial-dominance, surface scums and floating vegetation in inland and coastal waters.” Remote Sensing of Environment, Vol. 124: pp. 637–652. doi:10.1016/j.rse.2012.05.032.
  • Matthews, M.W., and Odermatt, D. 2015. “Improved algorithm for routine monitoring of cyanobacteria and eutrophication in inland and near-coastal waters.” Remote Sensing of Environment, Vol. 156: pp. 374–382. doi:10.1016/j.rse.2014.10.010.
  • Mishra, S., and Mishra, D.R. 2012. “Normalized difference chlorophyll index: A novel model for remote estimation of chlorophyll-a concentration in turbid productive waters.” Remote Sensing of Environment, Vol. 117: pp. 394–406. doi:10.1016/j.rse.2011.10.016.
  • Mobley, C.D. 1994. Light and Water: Radiative Transfer in Natural Waters. New York: Academic Press.
  • Morel, A. 1980. “In-water and remote measurements of ocean color.” Boundary-Layer Meteorology, Vol. 18(No. 2): pp. 177–201. doi:10.1007/BF00121323.
  • Morley, S.K., Brito, T.V., and Welling, D.T. 2018. “Measures of model performance based on the log accuracy ratio.” Space Weather, Vol. 16(No. 1): pp. 69–88. doi:10.1002/2017SW001669.
  • Moses, W.J., Gitelson, A.A., Berdnikov, S., and Povazhnyy, V. 2009. “Satellite estimation of chlorophyll-a concentration using the red and NIR bands of MERIS—The Azov sea case study.” IEEE Geoscience and Remote Sensing Letters, Vol. 6(No. 4): pp. 845–849. doi:10.1109/LGRS.2009.2026657.
  • Moses, W.J., Gitelson, A.A., Berdnikov, S., Saprygin, V., and Povazhnyi, V. 2012. “Operational MERIS-based NIR-red algorithms for estimating chlorophyll-a concentrations in coastal waters—The Azov Sea case study.” Remote Sensing of Environment, Vol. 121: pp. 118–124. doi:10.1016/j.rse.2012.01.024.
  • Mountrakis, G., Im, J., and Ogole, C. 2011. “Support vector machines in remote sensing: A review.” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 66(No. 3): pp. 247–259. doi:10.1016/j.isprsjprs.2010.11.001.
  • Nikparvar, B., and Thill, J.-C. 2021. “Machine learning of spatial data.” ISPRS International Journal of Geo-Information, Vol. 10(No. 9): pp. 600–632. doi:10.3390/ijgi10090600.
  • O'Reilly, J.E., Maritorena, S., Mitchell, B.G., Siegel, D.A., Carder, K.L., Garver, S.A., Kahru, M., and McClain, C. 1998. “Ocean color chlorophyll algorithms for SeaWiFS.” Journal of Geophysical Research: Oceans, Vol. 103(No. C11): pp. 24937–24953. doi:10.1029/98JC02160.
  • O'Reilly, J.E., and Werdell, P.J. 2019. “Chlorophyll algorithms for ocean color sensors-OC4, OC5 & OC6.” Remote Sensing of Environment, Vol. 229: pp. 32–47. doi:10.1016/j.rse.2019.04.021.
  • O'Sullivan, F. 1986. “A statistical perspective on ill-posed inverse problems.” Statistical Science, Vol. 1(No. 4): pp. 502–518. doi:10.1214/ss/1177013525.
  • Odermatt, D., Gitelson, A., Brando, V.E., and Schaepman, M. 2012. “Review of constituent retrieval in optically deep and complex waters from satellite imagery.” Remote Sensing of Environment, Vol. 118: pp. 116–126. doi:10.1016/j.rse.2011.11.013.
  • Pahlevan, N., Chittimalli, S.K., Balasubramanian, S.V., and Vellucci, V. 2019. “Sentinel-2/Landsat-8 product consistency and implications for monitoring aquatic systems.” Remote Sensing of Environment, Vol. 220: pp. 19–29. doi:10.1016/j.rse.2018.10.027.
  • Pahlevan, N., Lee, Z., Wei, J., Schaaf, C.B., Schott, J.R., and Berk, A. 2014. “On-orbit radiometric characterization of OLI (Landsat-8) for applications in aquatic remote sensing.” Remote Sensing of Environment, Vol. 154: pp. 272–284. doi:10.1016/j.rse.2014.08.001.
  • Pahlevan, N., Mangin, A., Balasubramanian, S.V., Smith, B., Alikas, K., Arai, K., Barbosa, C., et al. 2021. “ACIX-Aqua: A global assessment of atmospheric correction methods for Landsat-8 and Sentinel-2 over lakes, rivers, and coastal waters.” Remote Sensing of Environment, Vol. 258: pp. 112366. doi:10.1016/j.rse.2021.112366.
  • Pahlevan, N., Smith, B., Schalles, J., Binding, C., Cao, Z., Ma, R., Alikas, K., et al. 2020. “Seamless retrievals of chlorophyll-a from Sentinel-2 (MSI) and Sentinel-3 (OLCI) in inland and coastal waters: A machine-learning approach.” Remote Sensing of Environment, Vol. 240: pp. 111604. doi:10.1016/j.rse.2019.111604.
  • Philipson, P., Eriksso, K., and Stelzer, K. 2014. MERIS data for monitoring of small and medium sized humic Swedish lakes. In 2014 IEEE/OES Baltic International Symposium (BALTIC), 1–4. IEEE. doi:10.1109/BALTIC.2014.6887835.
  • Qiu, G., Xing, X., Boss, E., Yan, X.-H., Ren, R., Xiao, W., and Wang, H. 2021. “Relationships between optical backscattering, particulate organic carbon, and phytoplankton carbon in the oligotrophic South China Sea basin.” Optics Express, Vol. 29(No. 10): pp. 15159–15176. doi:10.1364/OE.422671.
  • Roesler, C., Uitz, J., Claustre, H., Boss, E., Xing, X., Organelli, E., Briggs, N., et al. 2017. “Recommendations for obtaining unbiased chlorophyll estimates from in situ chlorophyll fluorometers: A global analysis of WET Labs ECO sensors.” Limnology and Oceanography: Methods, Vol. 15(No. 6): pp. 572–585. doi:10.1002/lom3.10185.
  • Santini, F., Alberotanza, L., Cavalli, R.M., and Pignatti, S. 2010. “A two-step optimization procedure for assessing water constituent concentrations by hyperspectral remote sensing techniques: An application to the highly turbid Venice lagoon waters.” Remote Sensing of Environment, Vol. 114(No. 4): pp. 887–898. doi:10.1016/j.rse.2009.12.001.
  • Schaeffer, B.A., Bailey, S.W., Conmy, R.N., Galvin, M., Ignatius, A.R., Johnston, J.M., Keith, D.J., et al. 2018. “Mobile device application for monitoring cyanobacteria harmful algal blooms using Sentinel-3 satellite ocean and land colour instruments.” Environmental Modelling & Software : With Environment Data News, Vol. 109: pp. 93–103. doi:10.1016/j.envsoft.2018.08.015.
  • Schroeder, T., Schaale, M., and Fischer, J. 2007. “Retrieval of atmospheric and oceanic properties from MERIS measurements: A new case‐2 water processor for BEAM.” International Journal of Remote Sensing, Vol. 28(No. 24): pp. 5627–5632. doi:10.1080/01431160701601774.
  • Seegers, B.N., Stumpf, R.P., Schaeffer, B.A., Loftin, K.A., and Werdell, P.J. 2018. “Performance metrics for the assessment of satellite data products: An ocean color case study.” Optics Express, Vol. 26(No. 6): pp. 7404–7422. doi:10.1364/OE.26.007404.
  • Smith, B., Pahlevan, N., Schalles, J., Ruberg, S., Errera, R., Ma, R., Giardino, C., et al. 2021. “A chlorophyll-a algorithm for Landsat-8 based on mixture density networks.” Frontiers in Remote Sensing, Vol. 1: pp. 623678. doi:10.3389/frsen.2020.623678.
  • Smola, A.J., and Schölkopf, B. 2004. “A tutorial on support vector regression.” Statistics and Computing, Vol. 14(No. 3): pp. 199–222. doi:10.1023/B:STCO.0000035301.49549.88.
  • Soranno, P.A., Bacon, L.C., Beauchene, M., Bednar, K.E., Bissell, E.G., Boudreau, C.K., Boyer, M.G., et al. 2017. “LAGOS-NE: A multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes.” GigaScience, Vol. 6(No. 12): pp. 1–22. doi:10.1093/gigascience/gix101.
  • Spyrakos, E., O'Donnell, R., Hunter, P.D., Miller, C., Scott, M., Simis, S.G.H., Neil, C., et al. 2018. “Optical types of inland and coastal waters.” Limnology and Oceanography, Vol. 63(No. 2): pp. 846–870. doi:10.1002/lno.10674.
  • Sterckx, S., Knaeps, S., Kratzer, S., and Ruddick, K. 2015. “SIMilarity Environment Correction (SIMEC) applied to MERIS data over inland and coastal waters.” Remote Sensing of Environment, Vol. 157: pp. 96–110. doi:10.1016/j.rse.2014.06.017.
  • Swarbrick, V.J., Simpson, G.L., Glibert, P.M., and Leavitt, P.R. 2019. “Differential stimulation and suppression of phytoplankton growth by ammonium enrichment in eutrophic hardwater lakes over 16 years.” Limnology and Oceanography, Vol. 64(No. S1): pp. S130–S149. doi:10.1002/lno.11093.
  • Sydor, M., Gould, R.W., Arnone, R.A., Haltrin, V.I., and Goode, W. 2004. “Uniqueness in remote sensing of the inherent optical properties of ocean water.” Applied Optics, Vol. 43(No. 10): pp. 2156–2162. doi:10.1364/ao.43.002156.
  • Tang, D., Kawamura, H., Lee, M.-A., and Van Dien, T. 2003. “Seasonal and spatial distribution of chlorophyll-a concentrations and water conditions in the Gulf of Tonkin, South China Sea.” Remote Sensing of Environment, Vol. 85(No. 4): pp. 475–483. doi:10.1016/S0034-4257(03)00049-X.
  • Tebbs, E.J., Remedios, J.J., and Harper, D.M. 2013. “Remote sensing of chlorophyll-a as a measure of cyanobacterial biomass in Lake Bogoria, a hypertrophic, saline–alkaline, flamingo lake, using Landsat ETM+.” Remote Sensing of Environment, Vol. 135: pp. 92–106. doi:10.1016/j.rse.2013.03.024.
  • Tian, S., Guo, H., Xu, W., Zhu, X., Wang, B., Zeng, Q., Mai, Y., and Huang, J.J. 2022. “Remote sensing retrieval of inland water quality parameters using Sentinel-2 and multiple machine learning algorithms.” Environmental Science and Pollution Research, Vol. 30(No. 7): pp. 18617–18630. doi:10.1007/s11356-022-23431-9.
  • Toming, K., Kotta, J., Uuemaa, E., Sobek, S., Kutser, T., and Tranvik, L.J. 2020. “Predicting lake dissolved organic carbon at a global scale.” Scientific Reports, Vol. 10(No. 1): pp. 8471. doi:10.1038/s41598-020-65010-3.
  • Toming, K., Kutser, T., Laas, A., Sepp, M., Paavel, B., and Nõges, T. 2016. “First experiences in mapping lake water quality parameters with Sentinel-2 MSI imagery.” Remote Sensing, Vol. 8(No. 8): pp. 640. doi:10.3390/rs8080640.
  • Van Der Woerd, H.J., and Pasterkamp, R. 2008. “HYDROPT: A fast and flexible method to retrieve chlorophyll-a from multispectral satellite observations of optically complex coastal waters.” Remote Sensing of Environment, Vol. 112(No. 4): pp. 1795–1807. doi:10.1016/j.rse.2007.09.001.
  • Vanhellemont, Q. 2019. “Adaptation of the dark spectrum fitting atmospheric correction for aquatic applications of the Landsat and Sentinel-2 archives.” Remote Sensing of Environment, Vol. 225: pp. 175–192. doi:10.1016/j.rse.2019.03.010.
  • Vanhellemont, Q., and Ruddick, K. 2014. “Turbid wakes associated with offshore wind turbines observed with Landsat 8.” Remote Sensing of Environment, Vol. 145: pp. 105–115. doi:10.1016/j.rse.2014.01.009.
  • Vapnik, V. 2013. The Nature of Statistical Learning Theory. Berlin, Heidelberg, Germany: Springer Science & Business Media.
  • Vogt, R.J., Sharma, S., and Leavitt, P.R. 2018. “Direct and interactive effects of climate, meteorology, river hydrology, and lake characteristics on water quality in productive lakes of the Canadian Prairies.” Canadian Journal of Fisheries and Aquatic Sciences, Vol. 75(No. 1): pp. 47–59. doi:10.1139/cjfas-2016-0520.
  • Walker, H.W. 2019. Harmful Algae Blooms in Drinking Water: Removal of Cyanobacterial Cells and Toxins. Boca Raton, Florida, USA: CRC Press.
  • Warren, M.A., Simis, S.G., Martinez-Vicente, V., Poser, K., Bresciani, M., Alikas, K., Spyrakos, E., Giardino, C., and Ansper, A. 2019. “Assessment of atmospheric correction algorithms for the Sentinel-2A MultiSpectral Imager over coastal and inland waters.” Remote Sensing of Environment, Vol. 225: pp. 267–289. doi:10.1016/j.rse.2019.03.018.
  • Werdell, P.J., and Bailey, S.W. 2005. “An improved in-situ bio-optical data set for ocean color algorithm development and satellite data product validation.” Remote Sensing of Environment, Vol. 98(No. 1): pp. 122–140. doi:10.1016/j.rse.2005.07.001.
  • Werdell, P.J., Bailey, S.W., Franz, B.A., Harding, L.W., Feldman, G.C., and McClain, C.R. 2009. “Regional and seasonal variability of chlorophyll-a in Chesapeake Bay as observed by SeaWiFS and MODIS-Aqua.” Remote Sensing of Environment, Vol. 113(No. 6): pp. 1319–1330. doi:10.1016/j.rse.2009.02.012.
  • Werdell, P.J., McKinna, L.I.W., Boss, E., Ackleson, S.G., Craig, S.E., Gregg, W.W., Lee, Z., et al. 2018. “An overview of approaches and challenges for retrieving marine inherent optical properties from ocean color remote sensing.” Progress in Oceanography, Vol. 160: pp. 186–212. doi:10.1016/j.pocean.2018.01.001.
  • Werther, M., Odermatt, D., Simis, S.G.H., Gurlin, D., Lehmann, M.K., Kutser, T., Gupana, R., et al. 2022. “A Bayesian approach for remote sensing of chlorophyll-a and associated retrieval uncertainty in oligotrophic and mesotrophic lakes.” Remote Sensing of Environment, Vol. 283: pp. 113295. doi:10.1016/j.rse.2022.113295.
  • Wintermans, J., and De Mots, A.S. 1965. “Spectrophotometric characteristics of chlorophylls a and b and their phenophytins in ethanol.” Biochimica et Biophysica Acta, Vol. 109(No. 2): pp. 448–453. doi:10.1016/0926-6585(65)90170-6.
  • Wulder, M.A., Hilker, T., White, J.C., Coops, N.C., Masek, J.G., Pflugmacher, D., and Crevier, Y. 2015. “Virtual constellations for global terrestrial monitoring.” Remote Sensing of Environment, Vol. 170: pp. 62–76. doi:10.1016/j.rse.2015.09.001.
  • Wynne, T.T., Stumpf, R.P., Tomlinson, M.C., and Dyble, J. 2010. “Characterizing a cyanobacterial bloom in western Lake Erie using satellite imagery and meteorological data.” Limnology and Oceanography, Vol. 55(No. 5): pp. 2025–2036. doi:10.4319/lo.2010.55.5.2025.
  • Xu, Y., Feng, L., Zhao, D., and Lu, J. 2020. “Assessment of Landsat atmospheric correction methods for water color applications using global AERONET-OC data.” International Journal of Applied Earth Observation and Geoinformation, Vol. 93: pp. 102192. doi:10.1016/j.jag.2020.102192.
  • Yacobi, Y.Z., Gitelson, A., and Mayo, M. 1995. “Remote sensing of chlorophyll in Lake Kinneret using highspectral-resolution radiometer and Landsat TM: Spectral features of reflectance and algorithm development.” Journal of Plankton Research, Vol. 17(No. 11): pp. 2155–2173. doi:10.1093/plankt/17.11.2155.
  • Zhan, H., Shi, P., and Chen, C. 2003. “Retrieval of oceanic chlorophyll concentration using support vector machines.” IEEE Transactions on Geoscience and Remote Sensing, Vol. 41: pp. 2947–2951.

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