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.
RSMLD – remote sensing of marine litter and debris
ReportSeries – IOCCG Report Series
Bibliography
Abimbola, I.; McAfee, M.; Creedon, L.; Gharbia, S. (2024) In-situ detection of microplastics in the aquatic environment: A systematic literature review. Sci. Total Environ., vol. 934, pp 173111, https://doi.org/10.1016/j.scitotenv.2024.173111
Acuña-Ruz, T., Uribe, D., Amézquita, L., Guzmán, C., Taylor R., Merrill, J., Martínez P., Voisin, Mattar, C. (2018). Anthropogenic marine debris over beaches: Spectral characterization for remote sensing applications. Remote Sensing of Environment, 217: 309-322, https://doi.org/10.1016/j.rse.2018.08.008.
Acuña-Ruz, T., Park, Y.-J., Flöhr, T., and Garaba, S. P., (2027), Riverine litter patch detection, quantification and tracking at the Grabovica dam using Sentinel-2 imagery before and after October 2024 extreme flooding event: Water Res., v. 308 (Part B), p. 126705, https://doi.org/10.1016/j.watres.2026.126705.
Aguilar, M. A., Jiménez-Lao, R., Ladisa, C., Aguilar, F. J., and Tarantino, E. (2022). Comparison of spectral indices extracted from Sentinel-2 images to map plastic covered greenhouses through an object-based approach, GIsci. Remote Sens., 59, 822-842, https://doi.org/10.1080/15481603.2022.2071057.
Ahmed Dar, A., Chen, Z., Sardar, M. F. and An, C. (2024) Navigating the nexus: climate dynamics and microplastics pollution in coastal ecosystems. Environ. Res., 252, 118971, https://doi.org/10.1016/j.envres.2024.118971
Alboody, A., Vandenbroucke, N., Porebski, A., Sawan, R., Viudes, F., Doyen, P., and Amara, R. (2023) A new remote hyperspectral imaging system embedded on an unmanned aquatic drone for the detection and identification of floating plastic litter using machine learning. Remote Sens.(Basel), 15(14), 3455, https://doi.org/10.3390/rs15143455
Almeida, S., Radeta, M., Kataoka, T., Canning-Clode, J., Pessanha Pais, M., Freitas, R. and Monteiro, J.G. (2023) Designing unmanned aerial survey monitoring program to assess floating litter contamination. Remote Sens., vol. 15(1), pp 84, https://doi.org/10.3390/rs15010084
Anconitano, G., Bignami, C., Locritani, M., Merlino, S., Muccini, F., Nunziata, F., and Polcari, M., (2026), Towards plastic litter identification in aquatic environments using high-resolution SAR data: Remote Sens. Environ., v. 343, p. 115493, https://doi.org/10.1016/j.rse.2026.115493.
Andriolo, U., Topouzelis, K., van Emmerik, T. H. M., Papakonstantinou, A., Monteiro, J. G., Isobe, A., Hidaka, M., Kako, S. i., Kataoka, T., and Gonçalves, G. (2023) Drones for litter monitoring on coasts and rivers: suitable flight altitude and image resolution, Mar. Pollut. Bull., 195, 115521, https://doi.org/10.1016/j.marpolbul.2023.115521
Andriolo, U., Gonçalves, G., Hidaka, M., Gonçalves, D., Gonçalves, L. M., Bessa, F.,Kako, S. i. (2024) Marine litter weight estimation from UAV imagery: Three potential methodologies to advance macrolitter reports. Mar. Pollut. Bull. 202, 116405, https://doi.org/10.1016/j.marpolbul.2024.116405
Andriolo, U., Garcia-Garin, O., Vighi, M., Borrell, A., and Gonçalves, G. (2022) . Beached and floating litter surveys by unmanned aerial vehicles: operational analogies and differences, Remote Sens. (Basel), 14, 1336(1331-1312), https://doi.org/10.3390/rs14061336.
Andriolo, U., Gonçalves, G., Bessa, F., Sobral, P. (2020). Mapping marine litter on coastal dunes with unmanned aerial systems: A showcase on the Atlantic Coast. Science of the Total Environment, 736: https://doi.org/10.1016/j.scitotenv.2020.139632
Andriolo, U., Gonçalves, G., Rangel-Buitrago, N., Paterni, M., Bessa, F., Gonçalves, L., Sobral, P., Bini, M., Duarte, D., Fontan-Bouzas, A., Gonçalves, D., Kataoka, T., Luppichini, M., Pinto, L., Topouzelis, K., V ´ elez-Mendoza, A., Merlino, S., (2021). Drones for litter mapping: An inter-operator concordance test in marking beached items on aerial images. Marine Pollution Bulletin, 169, 112542. https://doi.org/10.1016/j.marpolbul.2021.112542
Andriolo, U., Gonçalves, G., Sobral, P., and Bessa, F.(2021) Spatial and size distribution of macro-litter on coastal dunes from drone images: A case study on the Atlantic coast, Mar. Pollut. Bull., 169, 112490, https://doi.org/10.1016/j.marpolbul.2021.112490.
Andriolo, U., Gonçalves, G., Sobral, P., Fontán-Bouzas, Á., Bessa, F. (2020). Beach-dune morphodynamics and marine macro-litter abundance: An integrated approach with Unmanned Aerial System. Science of the Total Environment, 749, 141474. https://doi.org/10.1016/j.scitotenv.2020.141474
Anggraini, N., Tawakkal, I., Rachman, I., and Matsumoto, T. (2024) Object detection of macroplastic waste using unmanned aerial vehicles in urban canal. Ecological Engineering & Environmental Technology, 25(8), pp. 271-284, https://doi.org/10.12912/27197050/189888
Antara, I. M. O. G., Nuarsa, I. W., Sudarma, I. M., Hendrawan, I. G., Cordova, M. R., (2024) Developing beach litter monitoring system based on reflectance characteristics and its abundance. Ecol. Eng. Technol. 25, (5), 61-78, https://doi.org/10.12912/27197050/184253
Aoyama, T. (2016). Extraction of marine debris in the Sea of Japan using satellite images, Proc. SPIE 9878, Remote Sensing of the Oceans and Inland Waters: Techniques, Applications, and Challenges, 987817 (7 May 2016); https://doi.org/10.1117/12.2220370
Arias, M., Sumerot, R., Delaney, J., Coulibaly, F., Cozar, A., Aliani, S., Suaria, G., Papadopoulou, T., and Corradi, P. (2021) Advances on remote sensing of windrows as proxies for marine litter based on Sentinel-2/MSI datasets, in 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium 2021, 1126-1129, https://doi.org/10.1109/IGARSS47720.2021.9555139
Arii, M., Koiwa, M., and Aoki, Y. (2014) Applicability of SAR to marine debris surveillance after the Great East Japan Earthquake. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 7(5), 1729-1744, https://doi.org/10.1109/JSTARS.2014.2308550
Asamoah, B.O., Uurasjärvi, E., Räty, J., Koistinen, A., Roussey, M., Peiponen, K.-E. (2021). Towards the development of portable and in situ optical devices for detection of micro-and nanoplastics in water: A review on the current status. Polymers, 13, 730. https://doi.org/10.3390/polym13050730
Astorayme, M. A., Vázquez-Rowe, I., and Kahhat, R. (2024) The use of artificial intelligence algorithms to detect macroplastics in aquatic environments: A critical review. Sci. Total Environ., vol 945, pp 173843, https://doi.org/10.1016/j.scitotenv.2024.173843.
Astorayme, M. A., Vázquez-Rowe, I., Muñoz-Sovero, E., and Kahhat, R., (2026), Advanced deep learning strategies for detection and quantification of macroplastics in rivers along the Peruvian coast: Mar. Pollut. Bull., v. 222, p. 118649, https://doi.org/10.1016/j.marpolbul.2025.118649.
Atuhaire, C., Semyalo, R., Kayondo, L. M., Nabende, J. N., and Gidudu, A., (2026), Towards spectral-based detection of plastic litter in freshwater environments: Geomatica, v. 78, no. 2, p. 100126, https://doi.org/10.1016/j.geomat.2026.100126.
Atuhaire, C., Semyalo, R., Kayondo, L. M., Nakatumba Nabende, J., Nakimbugwe, L., Katongole, U., and Gidudu, A., (2026), Diagnostic spectral features for plastic litter detection in freshwater environments: ISPRS Open J. Photogramm. Remote Sens., v. 20, p. 100126, https://doi.org/10.1016/j.ophoto.2026.100126.
Atuhaire, C., Semyalo, R., Manga, M., Kayondo, L. M., Nabende, J., and Gidudu, A., (2025), Prospects of remote sensing for monitoring plastic litter in freshwater environments: A systematic review: Sci. Afr., v. 29, p. e02833, https://doi.org/10.1016/j.sciaf.2025.e02833.
Atwood, E.C., Falcieri, F.M., Piehl, S., Bochow, M. Matthies, M., Franke, J., Carniel, S., Sclavo, M., Laforsch, C., Siegert, F. (2019). Coastal accumulation of microplastic particles emitted from the Po River, Northern Italy: Comparing remote sensing and hydrodynamic modelling with in situ sample collections. Marine Pollution Bulletin, 138, 561-574. https://doi.org/10.1016/j.marpolbul.2018.11.045
Bak, S., Kim, H.-M., Kim, Y., Lee, I., Park, M., Kim, T.-Y. and Jang Seon, W. (2024) High-resolution mapping techniques for coastal debris using YOLOv8 and unmanned aerial vehicle. KJRS, vol 40 (2), pp 151-166, https://doi.org/10.7780/kjrs.2024.40.2.3
Balsi, M., Moroni, M., Chiarabini, V., and Tanda, G.(2021). High-resolution aerial detection of marine plastic litter by hyperspectral sensing, Remote Sens. (Basel), 13, 1557, https://doi.org/10.3390/rs13081557
Bancud, G. E., Labanon, A. J., Abreo, N. A. and Kobayashi, V. (2023). Combining image enhancement techniques and deep learning for shallow water benthic marine litter detection. International Workshops of ECML PKDD 2022, 137-149, https://doi.org/10.1007/978-3-031-23618-1_9
Bansal, K. and Tripathi, A. K. (2024) WasteNet: A novel multi-scale attention-based U-Net architecture for waste detection in UAV images. Remote Sens. Appl. Soc. Environ., vol. 35, p. 101220, https://doi.org/10.1016/j.rsase.2024.101220
Bansal, K., and Tripathi, A. K. (2025) Automated floating debris monitoring using optical satellite imagery and artificial intelligence: Recent trends, challenges and opportunities, Remote Sens. Appl. Soc. Environ., v. 37, p. 101475, https://doi.org/10.1016/j.rsase.2025.101475
Bansal, K., and Tripathi, A. K., 2026, FlotSegNet: A lightweight attention-based 3D encoder architecture for efficient segmentation of floating river debris in multi-spectral satellite imagery: Expert Syst. Appl., v. 296, p. 128903, https://doi.org/10.1016/j.eswa.2025.128903.
Bansal, K., Tripathi, A. K., and Pandey, A. C., (2025), Efficient floating debris classification using a modified Vision Transformer and Sentinel-2 imagery: Remote Sens. Appl. Soc. Environ., v. 38, p. 101610, https://doi.org/10.1016/j.rsase.2025.101610.
Bao, Z., Sha, J., Li, X., Hanchiso, T., and Shifaw, E. (2018). Monitoring of beach litter by automatic interpretation of unmanned aerial vehicle images using the segmentation threshold method, Mar. Pollut. Bull., 137, 388-398. https://doi.org/10.1016/j.marpolbul.2018.08.009
Bartolo, M., Hili, G., Seychell, D., Montebello, M., Debono, C. J., Formosa, S., and Makantasis, K., (2026), Litter detection from aerial imagery: a review of UAV-based approaches and deep learning techniques: Multimed.Tools Appl., v. 85, no. 3, p. 232, https://doi.org/10.1007/s11042-026-21440-1.
Basu, B, Sannigrahi, S, Sarkar Basu, A., and Pilla, F. (2021) Development of Novel Classification Algorithms for Detection of Floating Plastic Debris in Coastal Waterbodies Using Multispectral Sentinel-2 Remote Sensing Imagery. Remote Sens.(Basel), 13(8), 1598, https://doi.org/10.3390/
Beck, A. J., Kaandorp, M., Hamm, T., Bogner, B., Kossel, E., Lenz, M., Haeckel, M., and Achterberg, E. P. (2023) Rapid shipboard measurement of net-collected marine microplastic polymer types using near-infrared hyperspectral imaging, Anal. Bioanal. Chem., 415, 2989-2998, https://doi.org/10.1007/s00216-023-04634-6
Bekova, R., and Prodanov, B. (2023) Assessment of beach macrolitter using unmanned aerial systems: A study along the Bulgarian Black Sea Coast, Mar. Pollut. Bull., 196, 115625, https://doi.org/10.1016/j.marpolbul.2023.115625
Biermann, L., Clewley, D., Martinez-Vicente, V., and Topouzelis, K. (2020). Finding plastic patches in coastal waters using optical satellite data, Sci. Rep., 10, 5364, https://doi.org/10.1038/s41598-020-62298-z
Blondeau-Patissier, D., Schroeder, T., Suresh, G., Li, Z., Diakogiannis, F. I., Irving, P., Witte, C., & Steven, A. D. (2023). Detection of marine oil-like features in Sentinel-1 SAR images by supplementary use of deep learning and empirical methods: Performance assessment for the Great Barrier Reef marine park. Marine Pollution Bulletin, 188, 114598. https://doi.org/10.1016/j.marpolbul.2023.114598
Bojesomo, A., Liatsis, P., and Almarzouqi, H.(2023) Marine debris segmentation using a parameter efficient octonion-based architecture, IEEE Geosci. Remote Sens. Lett., 20, 1-5, https://doi.org/10.1109/LGRS.2023.3321177
Booth, H., Ma, W., and Karakuş, O. (2023) High-precision density mapping of marine debris and floating plastics via satellite imagery. Sci. Rep., 13(1), 6822, https://doi.org/10.1038/s41598-023-33612-2
Bouchelaghem, S., Tibermacine, I. E., Balsi, M., Moroni, M. and Napoli, C. (2024) In Cross-domain machine learning approaches using hyperspectral imaging for plastics litter detection, 2024 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS), Oran, Algeria, 15-17 April, pp 36-40. https://doi.org/10.1109/M2GARSS57310.2024.10537535
Cadondon, J., Vallar, E., Shiina, T. and Galvez, M. C. (2024) Experimental detection of marine plastic litter in surface waters by 405 nm LD-based fluorescence lidar. Mar. Pollut. Bull., v. 207, pp. 116842. https://doi.org/10.1016/j.marpolbul.2024.116842
Campillo, A., Almeda, R., Vianello, A., Gómez, M., Martínez, I., Navarro, A., and Herrera, A. (2023) Searching for hotspots of neustonic microplastics in the Canary Islands, Mar. Pollut. Bull., 192, 115057, https://doi.org/10.1016/j.marpolbul.2023.115057
Cerra, D., Auer, S., Baissero, A. and Bachofer, F. (2024) Estimation of floating plastic debris surface in inland waters using spectral unmixing with multispectral data. in IGARSS 2024 – 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, pp 4393-4396, https://doi.org/10.1109/IGARSS53475.2024.10641060
Cerra, D., Auer, S., Baissero, A., and Bachofer, F. (2025) Detection and monitoring of floating plastic debris on inland waters from Sentinel-2 time series, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., v. 18, p. 1122-1138, https://doi.org/10.1109/JSTARS.2024.3502796
The 6th International Ocean Colour Science (IOCS) meeting was held in Darmstadt, Germany from 1 – 4 December 2025, hosted by EUMETSAT and ESA. All meeting material is available is on the archive webpage.