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
Kako, S. i., Isobe, A., Kataoka, T., Yufu, K., Sugizono, S., Plybon, C., and Murphy, T. A. (2018). Sequential webcam monitoring and modeling of marine debris abundance, Mar. Pollut. Bull., 132, 33-43, https://doi.org/10.1016/j.marpolbul.2018.04.075
Kako, S. i., Morita, S., and Taneda, T.(2020). Estimation of plastic marine debris volumes on beaches using unmanned aerial vehicles and image processing based on deep learning, Mar. Pollut. Bull., 155, 111127, https://doi.org/10.1016/j.marpolbul.2020.111127.
Kaladharan, P., Vijayakumaran, K., Singh, V., Prema, D., Asha, P. S., Sulochanan, B., Hemasankari, P., Edward, L., Padua, S., Shettigar, V., Anasukoya, A., and Bhint, H. (2017). Prevalence of marine litter along the Indian beaches: A preliminary account on its status and composition, J. Mar. biol. Ass. India, 59, 19-24, https://doi.org/10.6024/jmbai.2017.59.1.1953-03
Kallio, K., T. Kutser, T. Hannonen, S. Koponen, J. Pulliainen, J. Vepsäläinen, T. Pyhälahti, (2001). Retrieval of water quality from airborne imaging spectrometry of various lake types in different seasons, The Science of the Total Environment, 268: 59-77.
Kalogirou, E., Makri, D., Kountouri, J., Stylianou, T., Themistokleous, K., Papoutsa, C., Melillos, G., and G. Hadjimitsis, D. (2023) Detect plastic litter in Cyprus region using Sentinel-2, in Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023), 3-5 April, Ayia Napa, Cyprus, 7, https://doi.org/10.1117/12.2681679
Kameda, T. and J. Ishizaka (2005). Size-fractionated primary production estimated by a two-phytoplankton community model applicable to ocean color remote sensing. J. Oceanogr. 61 663-672. [Abstract]
Kamykowski, D. and Zentara, S-J. (2003). Can phytoplankton community structure be inferred from satellite-derived sea surface temperature anomalies calculated relative to nitrate depletion temperatures? Rem. Sens. Env., 86: 444-457.
Kamykowski, D. and Zentara, S-J. (2005). Changes in world ocean nitrate availability through the 20th century. Deep-Sea Research I , 52(9): 1719-1744, 10.1016/j.dsr.2005.04.007.
Kamykowski, D., Zentara, S-J., Morrison, J. M. and Switzer, A. C. (2002). Dynamic global patterns of nitrate, phosphate, silicate, and iron availability and phytoplankton community composition from remote sensing data. Global Biogeochem. Cycles, 16(4): 1077. DOI:10.1029/2001GB001640
Kanhai, L. D. K., Asmath, H., and Gobin, J. F. (2022) The status of marine debris/litter and plastic pollution in the Caribbean Large Marine Ecosystem (CLME): 1980–2020. Environmental Pollution, v. 300, p. 118919, https://doi.org/10.1016/j.
Karabashev, G. S.; Evdoshenko, M. A.; Sheberstov, S. V.; (2001). Normalized radiance spectra from the SeaWiFS data as a natural tracer of water exchange between the coastal and off-shore areas of the eastern Mediterranean sea. Proceedings of the International Conference “Current Problems in Optics of Natural Waters”, I. Levin and G. Gilbert (eds.), St.Peterburg, 157-159.
Karakuş O (2023), On advances, challenges and potentials of remote sensing image analysis in marine debris and suspected plastics monitoring. Front. Remote Sens., 4, 1302384, https://doi.org/10.3389/frsen.2023.1302384
Kataoka, T. and Nihei, Y. (2020) Quantification of floating riverine macro-debris transport using an image processing approach. Sci. Rep., vol 10, pp 2198, https://doi.org/10.1038/s41598-020-59201-1
Kataoka, T., Hinata, H., and Kako, S. i. (2012). A new technique for detecting colored macro plastic debris on beaches using webcam images and CIELUV, Mar. Pollut. Bull., 64, 1829-1836, https://doi.org/10.1016/j.marpolbul.2012.06.006.
Kataoka, T., Murray, C. C., and Isobe, A. (2018). Quantification of marine macro-debris abundance around Vancouver Island, Canada, based on archived aerial photographs processed by projective transformation, Mar. Pollut. Bull., 132, 44-51, https://doi.org/10.1016/j.marpolbul.2017.08.060
Katlane, R., Dupouy, C., Zargouni, F. (2012). Chlorophyll and turbidity concentrations deduced from MODIS as an index of water quality of the Gulf of Gabes in 2009. TŽlŽdŽtection, 11(1): 265-273.
Kaufman, Y.J.; et al, (2001) Baseline Maritime Aerosol: Methodology to Derive the Optical Thickness and Scattering Properties,Geophys. Res. Lett., 28(17): p. 3251.
Keeler, J. D. and Farmer, J. D. (1986). Robust space-time intermittency and 1/ f noise. Physica., 23D: 413-435.
Keiner, L. E., and Brown, C. W. (1999). Estimating oceanic chlorophyll concentrations with neural networks. Intl. J. Remote Sensing. 20: 189-194.
Keiner, L. E., and Yan, X.-H. (1998). A neural network model for estimating sea surface chlorophyll and sediments from thematic mapper imagery. Remote Sens. Environ. 66: 153-165.
Keith, D.J., Yoder, J.A. and Freeman, S.A. (2002). Spatial and temporal distribution of Coloured Dissolved Organic Matter (CDOM) in Narragansett Bay, Rhode Island: Implications for phytoplankton in coastal waters. Estuarine, Coastal and Shelf Science, 55: 705-717.
Keller, P. A. (2001). Comparison of two inversion techniques of a semi-analytical model for the determination of lake water constituents using imaging spectrometry data. The Sci. of the Tot. Env. (268) 189-196.
Kergoat, L., Fischer, A., Moulin, S. and Dedieu, G. (1995). Satellite measurements as a constraint on estimates of vegetation carbon budget. Tellus. 47B: 251-263.
Kharuk, V. I., Morgun, V. N., Rock, B. N. and Williams, D. L. (1994). Chlorophyll fluorescence and delayed fluorescence as potential tools in remote sensing: A reflection of some aspects of problems in comparative analysis. Remote Sens. Environ. 47: 98-105.
Kiefer, D. A. and SooHoo, J. B. (1982). Spectral absorption by marine particles of coastal waters of Baja California. Limnol. Oceanogr. 27: 492-499.
Kiefer, D. A. and Wilson, W. H. (1978). Reflectance spectroscopy of marine phytoplankton. Scripps Institute of Oceanography Ref. 78-6. Sponsored by U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Environment Satellite Service. Grant No. 04-6-158-44031 and 04-6-158-44033. February 1978 .
Kikaki, A., Karantzalos, K., Power, C. A., and Raitsos, D.A. (2020). Remotely Sensing the Source and Transport of Marine Plastic Debris in Bay Islands of Honduras (Caribbean Sea). Remote Sens., 12, 1727, https://doi.org/10.3390/rs12111727
Kikaki, K., Kakogeorgiou, I., Hoteit I., Karantzalos, K. (2024). Detecting Marine pollutants and Sea Surface features with Deep learning in Sentinel-2 imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 210, 39-54. https://doi.org/10.1016/j.isprsjprs.2024.02.017
Kikaki, K., Kakogeorgiou, I., Mikeli, P., Raitsos, DE., Karantzalos, K. (2022). MARIDA: A benchmark for Marine Debris detection from Sentinel-2 remote sensing data. PLoS ONE 17(1): e0262247. https://doi.org/10.1371/journal.pone.0262247
Kim, H-C., Yoo, S. and Oh, I. S. (2007). Relationship between phytoplankton bloom and wind stress in the sub-polar frontal area of the Japan/East Sea. Journal of Marine Systems, 67(3-4): 205-216. [Article]
Kim, J., and Kim, C. W. (2023) Improving the efficiency of marine debris collection policies using drone technology, J. Coastal Res., 116, 353-357, https://doi.org/10.2112/JCR-SI116-072.1
Kim, S.-W., Saitoh, S.-I., Ishizaka, J., Isoda, Y., and Kishino, M. (2000). Temporal and spatial variability of phytoplankton pigment concentrations in the Japan Sea derived from CZCS images. J. Oceanogr. 56: 527-538.
Kirk, J. T. O. (1979). Spectral distribution of photosynthetically active radiation in some south-eastern Australian waters. Aust. J. Mar. Freshw. Res. 30: 81-91.
Kirk, J. T. O. (1980). Spectral absorption properties of natural waters: contribution of the soluble and particulate fractions to light absorption in some inland waters of south-eastern Australia. Aust. J. Mar. Freshw. Res. 31: 287-296.
Kirk, J. T. O. (1997). Point-source integrating-cavity absorption meter: theoretical principles and numerical modeling. Appl. Optics.36: 6123-6128.
Kirk, J. T. O. and Tyler, P. A. (1986). The spectral absorption and scattering properties of dissolved and particulate components in relation to the underwater light field of some tropical Australian freshwaters. Freshw. Biol. 16: 573-583.
Kiselev, V., B. Bulgarelli, and T. Heege (2015). Sensor independent adjacency correction algorithm for coastal and inland water systems, Remote Sensing of Environment, vol. 157, pp. 85–95, 2015.
Kishino, M. A. Tanaka, and J. Ishizaka (2005). Retrieval of chlorophyll a, suspended solids, and colored dissolved organic matter in Tokyo Bay using ASTER data. Remote Sens. Env., 99: 66-74. [Article]
Kishino, M. and Okami, N. (1984). Instrument for measuring downward and upward spectral irradiances in the sea. La mer. 22: 37-40.
Kishino, M., Ishimaru, T., Furuya, K., Oishi, T. and Kawasaki, K. (1995). Development of under water algorithm (in Japanese), The Institute of Physical and Chemical Research, Japan, 89 p.
Kishino, M., Takahashi, M., Okami, N. and Ichimura, S. (1985). Estimation of the spectral absorption coefficients of phytoplankton in the sea. Bull. Mar. Sci. 37: 634-642.
Kiyomoto, Y., Iseki, K., and Okamura, K. (2001). Ocean color satellite imagery and shipboard measurements of chlorophyll a and suspended paticulate matter distribution in the East China Sea. J. Oceanogr. 57: 37-45.
Klemas, V (2011). Remote sensing techniques for studying coastal ecosystems: An overview. J. Coastal Research, 27(1): 2–17
Klemas, V (2012). Fisheries applications of remote sensing: An overview. Fisheries Research, doi.org/10.1016/j.fishres.2012.02.027
Klemas, V (2012). Remote sensing of algal blooms: An overview with case studies. Journal of Coastal Research, 28(1A): 34–43
Klemas, V (2012). Remote sensing of coastal plumes and ocean fronts: overview and case study. Journal of Coastal Research,28(1A): 1–7
Knaeps, E., Dogliotti, A. I., Raymaekers D., Ruddick, K., and, Sterckx, S. (2012). In-situ evidence of non-zero reflectance in the OLCI 1020 nm band for a turbid estuary. Rem. Sens. of Environment, 120, 133-144. DOI:10.1016/j.rse.2011.07.025.
Knaeps, E., K.G. Ruddick, D. Doxaran, A.I. Dogliotti, B. Nechad, D. Raymaekers, S. Sterckx (2015). A SWIR based algorithm to retrieve total suspended matter in extremely turbid waters Remote Sens. Environ. 168: 66-79 [Full article].
Knaeps, E., Sterckx, S., Strackx, G., Mijnendonckx, J., Moshtaghi, M., Garaba, S. P., and Meire, D. (2021). Hyperspectral reflectance dataset of dry, wet and submerged marine litter, Earth Syst. Sci. Data, 13, 713–730, https://doi.org/10.5194/essd-13-713-2021
Knobelpiesse, K.D., Pietras, C., Fargion, G.S., Wang, M., Frouin, R., Miller, M.A., Subramaniam, A. and Balch, W.M. (2004). Maritime aerosol optical thickness measured by handheld sun photometers.Rem. Sens. Environ. , 93 : 87-106.
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.