The IOCCG bibliography is updated periodically when new references are submitted by readers. 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 publication to be included in the IOCCG 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 (if available). Please also check to see if 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
Stramski, D., Reynolds, R.A., Kahru, M. and Mitchell, B.G. (1999). Estimation of particulate organic carbon in the ocean from satellite remote sensing. Science, 285(5425): 239-242.
Strass, V.H. (1990). Meridional and seasonal variations in the satellite-sensed fraction of euphotic zone chlorophyll. J. Geophys. Res., 95: 18,289-18,301.
Strömberg,KHP, Smyth, TJ, Allen JI, Pitois, S., and O’Brien, TD (2009). Estimation of global zooplankton biomass from satellite ocean colour. Journal of Marine Systems 77(4): 367-528.
Stroming, S., Robertson, M., Mabee, B., Kuwayama, Y., and Schaeffer, B. (2020). Quantifying the human health benefits of using satellite information to detect cyanobacterial harmful algal blooms and manage recreational advisories in U.S. Llakes. GeoHealth, https://doi.org/10.1029/2020GH000254
Strub, P.T., James, C., Thomas, A.C. and Abbott, M.R. (1990). Seasonal and nonseasonal variability of satellite-derived surface pigment concentration in the California current. J. Geophys. Res., 95: 11501-11530.
Strub, T., Powell, T.M. and Abbott, M.R. (1984). Temperature and transport patterns in Lake Tahoe: satellite imagery, field data and a dynamical model. Verh. Internat. Verein. Limnol. 22: 112-118
Stuart V, Platt T, and Sathyendranath S (2011). The future of fisheries science in management: a remote-sensing perspective. ICES Journal of Marine Science; doi:10.1093/icesjms/fsq200. [PDF file]
Stuart, V., Sathyendranath, S., Head, E.J.H., Platt, T., Irwin, B. and Maass, H. (2000). Bio-optical characteristics of diatom and prymnesiophyte populations in the Labrador Sea. Mar. Ecol. Prog. Ser., 201: 91-106. [PDF file]
Stuart, V., Ulloa, O., Alarcón, G., Sathyendranath, S., Major, H., Head, E. J. H., and Platt, T. (2004). Bio-optical characteristics of phytoplankton populations in the upwelling system off the coast of Chile. Rev. Chilena Hist. Nat. 77: 87-105. [PDF file]
Stumpf, R.P., and Pennock, J.R. (1989). Calibration of a general optical equation for remote sensing of suspended sediments in a moderately turbid estuary. J. Geophys. Res., 94: 14,363-14,371.
Stumpf, R.P., and Pennock, J.R. (1991). Remote estimation of the diffuse attenuation coefficient in a moderately turbid estuary. Rem. Sens. Environ., 38: 183-191.
Sturm, B., and Zibordi, G. (2002). SeaWiFS atmospheric correction by an approximate model and vicarious calibration. Intl. J. Rem. Sens., 23(3): 489-501.
Subrahmanyam, B., Ueyoshi, K. and Morrison, J. M. (2008). Sensitivity of the Indian ocean circulation to phytoplankton forcing using an ocean model. Rem. Sen. Environ. 112: 1488–1496.
Subramaniam, A., and Carpenter, E.J. (1993). An empirically derived protocol for detection of blooms of the marine cyanobacterium Trichodesmium using CZCS imagery. Intl. J. Rem. Sens., 15: 1559-1569.
Subramaniam, A., and Carpenter, E.J. (1994). An empirically derived protocol for the detection of blooms of the marine cyanobacterium Trichodesmium using CZCS imagery. Intl. J. Rem. Sens., 15: 1559-1569.
Subramaniam, A., Carpenter, E.J., and Falkowski, P.G. (1999). Bio-optical properties of the marine diazotrophic cyanobacteria Trichodesmium spp. II. A reflectance model for remote sensing. Limnol. Oceanogr., 44: 618-627.
Subramaniam, A., Carpenter, E.J., Karentz, D. and Falkowski, P.G. (1999). Bio-optical properties of the marine diazotrophic cyanobacteria Trichodesmium spp. I. Absorption and photosynthetic action spectra. Limnol. Oceanogr., 44: 608-617.
Suchy, K.D., Le Baron, N., Hilborn, A., Perry, R.I. and Costa, M. (2019). Influence of environmental drivers on spatio-temporal dynamics of satellite-derived chlorophyll a in the Strait of Georgia. Prog. Oceanogr. 176, 102134 https://doi.org/10.1016/j.pocean.2019.102134
Sugihara, S. and Kishino, M. (1988). An algorithm for estimating the water quality parameters from irradiance just below the sea surface. J. Geophys. Res., 93: 10,857-10,862.
Suh, Y.-S., L.-H. Jang, N.-K. Lee, J. Ishizaka (2004). Feasibility of red tide detection around Korean waters using satellite remote sensing. J. Fish. Sci. Tech. 7: 148-162.
Sullivan, C.W., McClain, C.R., Comiso, J.C. and Smith Jr., W.O. (1988). Phytoplankton standing crops within an Antarctic ice edge assessed by satellite remote sensing. J. Geophys. Res., 93: 12,487-12,498.
Sun, J., M. Wang, L. Tan, and L. Jiang (2014). An efficient approach for VIIRS RDR to SDR data processing. IEEE Geosci. Remote Sens. Lett ., 11, 2037-2041. doi:10.1109/LGRS.2014.2317553
Sun, L., Guo, M., Zhu, J., Hu, X., Song, Q. (2013) FY-3A/MERSI, ocean color algorithm, products and demonstrative applications. Acta Oceanologica Sinica 32(5): 75-81. [Abstract].
Sun, S. Liu, Z., Chiu, L., Yang, R., Singh, R.P. and Kafatos, M. (2004). Anomalous cold water along the mid-Atlantic coast during sid-Summer. EOS Trans: 85 (15), 13
Sun, Y., Bakker, T., Ruf, C. and Pan, Y. (2023). Effects of microplastics and surfactants on surface roughness of water waves. Sci. Rep., 13, (1), 1978, https://doi.org/10.1038/s41598-023-29088-9
Suresh, T., Talaulikar, M., Desa, E., Matondkar, S.G.P., Mascarenhas, A. (2012). Comparison of measured and satellite derived spectral diffuse attenuation coefficients for the Arabian Sea. International Journal of Remote Sensing. 33:2, 570-585. doi:10.1080/01431161.2010.543435. [Full article]
Svejkovsky, J., and Shandley, J. (2001). Detection of offshore plankton blooms with AVHRR and SAR imagery. Intl. J. Rem. Sens.,22: 471-485.
Swanepoel, S., Scheckle, T. J., and Marlin, D. (2023) Implementing land-based litter surveys through visual inspection of imagery using unmanned aerial vehicles. Environ. Chall., 13, 100753, https://doi.org/10.1016/j.envc.2023.100753
Swathi, P.S. and Tong, T.W. (1988). A new algorithm for computing the scattering coefficients of highly absorbing cylinders. J. Quant. Spectrosc. Radiat. Transf., 40: 525-530.
Switzer, A. C., Kamykowski, D. and Zentara, S-J. (2003). Mapping nitrate in the global ocean using remotely sensed sea surface temperature. Journal of Geophysical Research , 108: 36-1,12. doi:10.1029/2000JC0000444.
Szekielda, K.-H., Gobler, C., Gross, B., Moshary, F. and Ahmed, S. (2003). Spectral reflectance measurements of estuarine waters. Ocean Dynamics, 53: 98-102. DOI 10.1007/s10236-003-0027-x
Szekielda, K.H. (2020). EUTROPHICATION: THE ANTHROPOGENIC OFFSHORE SIGNAL. International Journal of Geology, Earth & Environmental Sciences, 10(2): 128-137
Szekielda, K.H. , Bowles, J.H. Gillis, D.B. Snyder, W. Miller W.D. (2010) Patch recognition of algal blooms and macroalgae. In: Ocean Sensing and Monitoring II, Proc. of SPIE, edited by Hou W. and Arnone, R.A. 7678, 76780A-1; doi:10.1117/12.854772. [Abstract]
Szekielda, KH, Bowles, JH, Gillis, DB and Miller, WD (2009). Interpretation of absorption bands in airborne hyperspectral radiance data. Sensors, 9(4): 2907-2925; doi:10.3390/s90402907 [Link for PDF file]
Taddia, Y., Corbau, C., Buoninsegni, J., Simeoni, U. and Pellegrinelli, A. (2021). UAV approach for detecting plastic marine debris on the beach: A case study in the Po River Delta (Italy). Drones, 5, (4), 140, https://doi.org/10.3390/drones5040140
Taggio, N., Aiello, A., Ceriola, G., Kremezi, M., Kristollari, V., Kolokoussis, P., Karathanassi, V., and Barbone, E.(2022) A combination of machine learning algorithms for marine plastic litter detection exploiting hyperspectral PRISMA data, Remote Sens. (Basel), 14, 3606, https://doi.org/10.3390/rs14153606.
Taheri H. Shahraiyni; M. Schaale; F. Fell; J. Fischer; R. Preusker; M. Vatandoust; Bagheri S. Shouraki; M. Tajrishy; H. Khodaparast; A. Tavakoli (2007). Application of the Active Learning Method for the estimation of geophysical variables in the Caspian Sea from satellite ocean colour observations. International Journal of Remote Sensing, 28(20): 4677 – 4683.
Taheri Shahraiyni, H., S. Bagheri Shouraki; F. Fell; M. Schaale; J. Fischer; A. Tavakoli; R. Preusker; M. Tajrishy; M. Vatandoust; H. Khodaparast (2009). Application of the active learning method to the retrieval of pigment from spectral remote sensing reflectance data. International Journal of Remote Sensing, 30(4): 1045 – 1065
Talaulikar, M., Suresh, T., Desa, E., Inamdar, A. (2014). An empirical algorithm to estimate spectral average cosine of underwater light field from remote sensing data in coastal oceanic waters. Limnol. Oceanogr. Methods, 12: 74-85. DOI: 10.4319/lom.2014.12.74 [ Full Article]
Talaulikar, M., Suresh,T., Desa, E., Matondkar, S.G.P., Kumar, S.T., Lotlikar, A., and Inamdar, A. (2012). Empirical algorithm to estimate the average cosine of underwater light field at 490 nm. Remote Sensing Letters, 3(7): 585-593. doi:10.1080/01431161.2011.643506. [Full article]
Tan, C.K., Ishizaka, J., Matsumura, S., Yusoff, F.M. and Mohamed, M.I. (2006). Seasonal variability of SeaWiFS chlorophyll a in the Malacca Straits in relation to Asian Monsoon. Continental Shelf Research, 26: 168-178.
Tang, D. (1999). Remote Sensing of Pigment Concentration and Sea Surface Temperature on the Continental Shelf of China. Diss. Abst. Intl. Pt. B – Sci. & Eng., 59: 6220.
Tang, D., B. Satyanarayana, R.P. Singh, and H. Zhao, (2006). Satellite Remote Sensing of Chlorophyll-a Distribution in the Northeast Arabian Sea, Advances in Geosciences, Volume 5: Oceans and Atmospheres (OA). Speer, M.S. (ed.), World Scientific Co., Pte. Ltd., Singapore, p.15.
Tang, D., Satyanarayana,B., Zhao, H., Zheng,G., Singh, R.P. and L.V. JianHai (2008). Variation of Chlorophyll-a in the Northeastern Indian Ocean after the 2004 South Asian Tsunami, International J. Remote Sensing, In press,
Tang, D.L.; Kawamura, H; Doan-Nhu, H.; Takahashi, W. (2004). Remote sensing oceanography of a harmful algal bloom off the coast of southeastern Vietnam. J. Geophys. Res., Vol. 109, No. C3, C03014 10.1029/2003JC002045 05 March 2004
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.
Tang, S., P. Larouche, A. Niemi and C. Michel 2013. Regional algorithms for remote-sensing estimates of total suspended matter in the Beaufort Sea. International J. of Remote Sensing, 34 (19): 6562-6576
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Tao, B., Mao, Z., Pan, D., Shen,Y. (2013). Optical detection of Prorocentrum donghaiense blooms based on multispectral reflectances. Acta Oceanologica Sinica . 32(10):48-56.
Tao, B., Mao, Z., Pan, D., Shen,Y., Zhu, Q., Chen, J. (2013). Influence of bio-optical parameter variability on the reflectance peak position in the red band of algal bloom waters, Ecological Informatics, 16:17-24,2013.