The IOCCG bibliography is updated periodically when new references are submitted by readers, especially references that are published open access. Another useful ocean colour bibliography is the searchable Historic Ocean Colour Archive assembled by Marcel Wernand, with articles and books written between the 17th and early 20th century.
If you would like to submit a peer-reviewed open access publication to be included in the Ocean Colour Bibliography, please send the reference to Raisha Lovindeer using the following format: Lastname1, Initials1., Lastname2, Initials2., etc. (DATE). Full title of publication, Journal Abbreviation, Volume, Page numbers, DOI as a link. Please also check that the reference is not already in the database (search by first author). It is not necessary to send the PDF file as an attachment. Note that only peer-reviewed articles will be accepted.
If you would like to view recently-published papers, enter the current year in “Search by Keyword”. You can also search the database using keywords or the author’s last name. For papers dealing with Remote Sensing of Marine Litter and Debris, use the keyword “RSMLD”. You can also view the Datasets Bibliography for remote sensing and marine litter and debris.
Bibliography
Sathyendranath, S., Platt, T., Stuart, V., Irwin, B.D., Veldhuis, M.J.W., Kraay, G.W. and Harrison, W.G. (1996). Some bio-optical characteristics of phytoplankton in the N.W. Indian Ocean. Mar. Ecol. Prog. Ser., 132: 299-311.
Sathyendranath, S., Platt, T., Stuart, V., Maass, H. and Cota, G. (1999). Remote sensing of phytoplankton biomass and primary production (in Japanese). Aquabiology, 21: 17-22.
Sathyendranath, S., Prieur, L., and Morel, A. (1989). A three-component model of ocean colour and its application to remote sensing of phytoplankton pigments in coastal waters. Intl. J. Rem. Sens., 10: 1373-1394.
Sathyendranath, S., Stuart, V., Irwin, B.D., Maass, H., Savidge, G., Gilpin, L., and Platt, T. (1999). Seasonal variations in bio-optical properties of phytoplankton in the Arabian Sea. Deep-Sea Res., 46: 633-654.
Sathyendranath, S., Subba Rao, D.V., Chen, Z., Stuart, V., Platt, T., Bugden, G. L., Jones, W. and Vass, P. (1997). Aircraft remote sensing of toxic phytoplankton blooms: a case study from Cardigan River, Prince Edward Island. Can. J. Rem. Sens., 23: 15-23.
Sathyendranath, S., Watts, L., Devred, E., Platt, T., Caverhill, C., and Maass, H. (2004). Discrimination of diatoms from other phytoplankton using ocean-colour data. Mar. Ecol. Prog. Ser. 272: 59-68. [PDF file]
Sathyendrath, S., Cota, G., Stuart, V., Maass H., Platt T (2000). Remote sensing of phytoplankton pigments: a comparison of empirical and theoretical approaches. Intl. J. Rem. Sens., 22(2&3): 249-273.
Sauzède, R., H. Claustre, J. Uitz, C. Jamet, G. Dall’Olmo, F. D’Ortenzio, B. Gentili, A. Poteau, and C. Schmechtig (2016), A neural network-based method for merging ocean color and Argo data to extend surface bio-optical properties to depth: Retrieval of the particulate backscattering coefficient, J. Geophys. Res. Oceans, 121, doi:10.1002/2015JC011408. [Full article].
Savastano, S., Cester, I., Perpinyà, M., and Romero, L. (2021) . A first approach to the automatic detection of marine litter in SAR images using artificial intelligence, in 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium, 2021, 8704-8707, https://doi.org/10.1109/IGARSS47720.2021.9737038
Savidge, G. and Gilpin, L. (1999). Seasonal influences on size-fractionated chlorophyll a concentrations and primary production in the north-west Indian Ocean. Deep-Sea Res., 46: 701-724.
Scardi, M., and Harding, L.W.J. (1999). Developing an empirical model of phytoplankton primary production: a neural network case study. Ecol. Model, 120: 213-223.
Schaeffer, B. A., P. Whitman, R. Vandermeulen, C. Hu, A. Mannino, J. Salisbury, B. Efremova, R. Conmy, M. Coffer, W. Salls, H. Ferriby, and N. Reynolds (2023). Assessing potential of the Geostationary Littoral Imaging and Monitoring Radiometer (GLIMR) for water quality monitoring across the coastal United States. Marine Pollution Bulletin. 196, 115558, https://doi.org/10.
Schiller, H. and Doerffer, R. (1999). Neural network for emulation of an inverse model operational derivation of Case II water properties from MERIS data. Intl. J. Rem. Sens., 20(9): 1735-1746.
Schmid, T., Wellhausen, J., Kumm, M., Binkele, T., Tholen, C. and Wurl, O. (2024) Requirement study on a specialized hyperspectral aerial imaging system for marine plastic litter classification, in OCEANS 2024 Halifax, Canada, 2024, 1-7, https://doi.org/10.1109/OCEANS55160.2024.10754274
Schmidt, T., Kuester, T., Smith, T. and Bochow, M. (2023). Potential of optical spaceborne sensors for the differentiation of plastics in the environment. Remote Sens., 15, (8), 2020, https://doi.org/10.3390/rs15082020
Schofield, O., Bidigare, R.R. and Prézelin, B.B. (1990). Spectral photosynthesis, quantum yield and blue-green light enhancement of productivity rates in the diatom Chaetoceros gracile and the prymnesiophyte Emiliana huxleyi. Mar. Ecol. Prog. Ser., 64: 175-186.
Schofield, O., Prézelin, B.B., Smith, R.C., Stegmann, P.M., Nelson, N.B., Lewis, M.R. and Baker, K.S. (1991). Variability in spectral and nonspectral measurements of photosynthetic light utilization efficiencies. Mar. Ecol. Prog. Ser., 78: 253-271.
Schollaert Uz, S. (2016). Building intuition for in-water optics and ocean color remote sensing: Spectrophotometer activity with littleBits™. Oceanography 29(1):98–103, http://dx.doi.org/10.5670/oceanog.2016.01
Schollaert Uz, S., A.J. Busalacchi, T.M. Smith, M.N. Evans, C.W. Brown and E.C. Hackert (2017) Interannual and decadal variability in tropical Pacific chlorophyll from a statistical reconstruction: 1958-2008, J. Climate, 30, 18, doi: 10.1175/JCLI-D-16-0202.1.
Schollaert, S.E., Rossby, T. and Yoder, J. (2004) Gulf stream cross-frontal exchange: Possible mechanisms to explain interannual variations in phytoplankton chlorophyll in the Slope Sea during SeaWiFS years. Deep Sea Research. II. Topical Studies in Oceanography, 51: 173-188
Schollaert, S.E., Yoder, J.A., Westphal, D.L and O’Reilly, J.E. (2003). Influence of dust and sulfate aerosols on ocean color spectra and chlorophyll-a concentrations derived from SeaWiFS off the U.S. East Coast. J. Geophys. Res., 108 (C6): 3191, doi:10.1029/2000JC000555, 2003
Schreyers L, van Emmerik T, Nguyen TL, Phung N-A, Kieu-Le T-C, Castrop E, Bui T-KL, Strady E, Kosten S, Biermann L, van den Berg SJ and van der Ploeg M (2021). A Field Guide for Monitoring Riverine Macroplastic Entrapment in Water Hyacinths. Front. Environ. Sci. 9:716516. https://doi.org/10.3389/fenvs.2021.716516
Schreyers, L. J., van Emmerik, T. H. M., Bui, T.-K. L., Biermann, L., Uijlenhoet, R., Nguyen, H. Q., Wallerstein, N. and van der Ploeg, M. (2024) Water hyacinths retain river plastics. Environ. Pollut., vol 356, pp 124118, https://doi.org/10.1016/j.envpol.2024.124118
Schreyers, L., van Emmerik, T., Biermann, L. and van der Ploeg, M. (2022) Direct and indirect river plastic detection from space, in Proceedings IGARSS 2022 – 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 17-22 July, p. 5539-5542, https://doi.org/10.1109/IGARSS46834.2022.9883379
Schreyers, L., van Emmerik, T., Nguyen, T. L., Castrop, E., Phung, N.-A., Kieu-Le, T.-C., Strady, E., Biermann, L., van der Ploeg, M. (2021). Plastic Plants: The Role of Water Hyacinths in Plastic Transport in Tropical Rivers. Front. . Environ. Sci. 9, 177. https://www.frontiersin.org/article/10.3389/fenvs.2021.686334
Schroeder, T., Schaale, M., Lovell, J., Blondeau-Patissier, D. (2022). An ensemble neural network atmospheric correction for Sentinel-3 OLCI over coastal waters providing inherent model uncertainty estimation and sensor noise propagation. Remote Sensing of Environment, 270, 112848, https://doi.org/10.1016/j.rse.2021.112848.
Schwarz J.N., Kowalczuk, P., Kaczmarek, S., Cota, G.F., Mitchell, B.G., Kahru, M., Chavez, F.P., Cunningham, A., McKee, D., Gege, P., Kishino, M., Phinney, D.A., and Raine, R. (2002). Two models for absorption by coloured dissolved organic matter (CDOM), Oceanologia, 44(2): 209-241.
Schwarz, J.N. (2005). Derivation of dissolved organic carbon concentrations from SeaWiFS data. International Journal of Remote Sensing, 26(2): 283 – 293.
Schwarz, J.N. and Schodlok, M.P. (2009). Impact of drifting icebergs on surface phytoplankton biomass in the Southern Ocean: Ocean colour remote sensing and in situ iceberg tracking. Deep Sea Research Part I: Oceanographic Research Papers, 56(10): 1727-1741
Sciandra, A., Lazzara, L., Claustre, H. and Babin, M. (2000). Responses of the growth rate, pigment composition and optical properties of Cryptomonas sp. to light and nitrogen stresses. Mar. Ecol. Prog. Ser., 201: 107-120.
Segura, V., Lutz, V.A., Dogliotti, A. I., Silva, R., Negri, R., Akselman, R. and Benavides, H. (2013). Phytoplankton Functional Types and primary production in the Argentine Sea. Marine Ecology Progress Series, 491: 15–31. doi: 10.3354/meps10461.
Serafino, F. and Bianco, A. (2024) X-Band radar detection of small garbage islands in different sea state conditions. Remote Sens. vol 16(12), pp 2101, https://doi.org/10.3390/rs16122101
Serafino, F., and Bianco, A.(2021). Use of X-Band radars to monitor small garbage islands, Remote Sens. (Basel), 13, 3558, https://doi.org/10.3390/rs13183558.
Serranti, S., Palmieri, R., Bonifazi, G., and Cózar, A.(2018). Characterization of microplastic litter from oceans by an innovative approach based on hyperspectral imaging, Waste Management
76, 117-125, https://doi.org/10.1016/j.wasman.2018.03.003
Seshamani, R., Alex, T.K. and Jain, Y.K. (1994). An airborne sensor for primary productivity and related parameters of coastal waters and large water bodies. Intl. J. Rem. Sens., 15: 1101-1108.
Shaffer, G.P. and Onuf, C.P. (1985). Reducing the error in estimating annual production of benthic microflora: hourly to monthly rates, patchiness in space and time. Mar. Ecol. Prog. Ser., 26: 221-231.
Shang P., Shen F. (2016). Atmospheric Correction of Satellite GF-1/WFV Imagery and Quantitative Estimation of Suspended Particulate Matter in the Yangtze Estuary. Sensors, 16, 1997. doi:10.3390/s16121997
Shanmugam, P. (2010). An evaluation of inversion models to retrieve IOPs in Korean waters. Journal of Oceanography, 66: 815-830.
Shanmugam, P. (2011). New models for retrieving and partitioning coloured dissolved organic matter in the global oceans. Implications for remote sensing. Remote Sensing of Environment, 115: 1501–1521. [Article]
Shanmugam, P. (2011). A new bio-optical algorithm for the remote sensing. Journal of Geophysical Research, 116: C04016, doi:10.1029/2010JC006796.
Shanmugam, P. (2011). A new inversion model to retrieve the particulate backscattering in coastal oceans. IEEE Transaction on Geoscience and Remote Sensing, 49: 2463-2475.
Shanmugam, P., Ahn, Y.H., and Ram, P.S. (2008). SeaWiFS sensing of hazardous algal blooms and their underlying mechanisms in shelf-slope waters of the Northwest Pacific during summer. Remote Sensing of Environment 112: 3248-3270.
Shanmugam, V., P. Shanmugam, and X. He (2019). New algorithm for computation of the Rayleigh-scattering radiance for remote sensing of water color from space. Optics Express, 27 (21), 30116-30139, https://doi.org/10.1364/OE.27.030116.
Shanmugam,P. and Ahn, Y.H. (2007). New atmospheric correction technique to retrieve the ocean colour from SeaWiFS imagery in complex coastal waters. Journal of Optics A: Pure and Applied Optics, 9: 511-530.
Shanmugam,P. and Ahn, Y.H. (2007). Reference solar irradiance spectra and consequences of their disparities in remote sensing of the ocean color. Annales Geophysicae, 25: 1235-1252.
Shannon, L.V., Mostert, S.A., and Schlittenhardt, P. (1984). The Nimbus 7 CZCS experiment in the Benguela current region off southern Africa, February 1980. II — Interpretation of imagery and oceanographic implications. J. Geophys. Res., 89: 4,968-4,976.
Shannon, L.V., Mostert, S.A., Walters, N.M., and Anderson, F.P. (1983). Chlorophyll concentrations in the southern Benguela current region as determined by satellite ( Nimbus-7 coastal zone colour scanner). J. Plankton Res., 5: 565-583.
Shen, F., Zhou, Y., Peng, X., Chen, Y. (2014) Satellite multisensor mapping of suspended particulate matter in turbid estuarine and coastal ocean, China. International Journal of Remote Sensing, 35(11-12): 4173 – 4192. DOI: 10.1080/01431161.2014.916053 [Full article]
Shenglei Wang, Junsheng Li, Bing Zhang, Evangelos Spyrakos, Andrew Tyler, Qian Shen, et al. (2018). Trophic state assessment of global inland waters using a MODIS-derived Forel-Ule index. Remote Sensing of Environment, 217, 444-460. https://doi.org/10.1016/j.rse.2018.08.026
Shi W. and M. Wang (2019). A blended inherent optical property algorithm for global satellite ocean color observations. Limnol. Oceanogr.: Methods 17: 377–394. http://dx.doi.org/10.1002/lom3.10320
The sixth International Ocean Colour Science (IOCS) meeting will take place in Darmstadt, Germany from 1 – 4 December 2025, hosted by EUMETSAT and ESA with support from other agencies.