Type of dataset: ODATIS ocean color medium resolution (MR) Level 3 - Basic

Digital Object Identifiers (DOIs): 

• ODATIS Ocean_Color_MR_Basic: 10.24400/527896/a01-2024.013 - more metadata

Condition of access: ODATIS Ocean_Color_MR_Basic is distributed by AVISO under standard AVISO+ license agreement.

Use: Ocean Color Remote Sensing ; Marine Ecosystem Monitoring ; Coastal Water Monitoring

Description:  The ODATIS Ocean_Color_MR_Basic product provides optical reflectance measurements as well as related physical, subsurface and biogeochemical parameters at 300 m spatial resolution along the entire French metropolitan coastal zone, according to the criteria defined by the ODATIS Scientific Expert Consortium (CES) dedicated to ocean color : https://www.odatis-ocean.fr/activites/consortium-dexpertise-scientifique/ces-couleur-de-locean.

Product processing is performed from Level 1 to Level 3, and is reprojected on a regular square grid format. Data are temporally aggregated and provided as daily, 8 day and monthly products.

The "Basic" version of the ODATIS MR product includes data from the MODIS sensor processed with the "NIR/SWIR" atmospheric correction method (Wang and Shi, 2007), as well as data from the MERIS and OLCI-A/B sensors processed with the Polymer atmospheric correction (Hygeos, https://www.hygeos.com/polymer).

List of available parameters for each sensor:

• MODIS : NRRS555, CHL-OC5, SPM-G, CDOM, T-FNU, SST-NIGHT
• OLCI-A/B / MERIS : NRRS560, CHL-OC5, SPM-G, CDOM, T-FNU

Geographic coverage: 41.20°N-51.50°N, 7.80°W to 10.30°E

Citation:  "The ODATIS Ocean_Color_MR_Basic product, produced by ACRI-ST with the support from CNES and the ODATIS Ocean Cluster, is made freely available by AVISO". ACRI-ST, 2024. ODATIS Ocean Color Medium Resolution (MR) Level-3 Basic (v1.0) [Data set]. CNES. https://doi.org/10.24400/527896/A01-2024.013.

Resources: 

• ODATIS MR L3 User Handbbok
• Dogliotti, A. I., Ruddick, K. G., Nechad, B., Doxaran, D., & Knaeps, E. (2015). A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters. Remote sensing of environment, 156, 157-168.: doi.org/10.1016/j.rse.2014.09.020
• Menghua Wang and Wei Shi, "The NIR-SWIR combined atmospheric correction approach for MODIS ocean color data processing," Opt. Express 15, 15722-15733 (2007): doi.org/10.1364/OE.15.015722
• François Steinmetz, Pierre-Yves Deschamps, and Didier Ramon, "Atmospheric correction in presence of sun glint: application to MERIS," Opt. Express 19, 9783-9800 (2011): doi.org/10.1364/OE.19.009783
• Gohin, F., Druon, J. N., & Lampert, L. (2002). A five-channel chlorophyll concentration algorithm applied to SeaWiFS data processed by SeaDAS in coastal waters. International journal of remote sensing, 23(8), 1639-1661.: doi.org/10.1080/01431160110071879
• Hu, C., Lee, Z., & Franz, B. (2012). Chlorophyll algorithms for oligotrophic oceans: A novel approach based on three‐band reflectance difference. Journal of Geophysical Research: Oceans, 117(C1).: doi.org/10.1029/2011JC007395
• Han, B., Loisel, H., Vantrepotte, V., Mériaux, X., Bryère, P., Ouillon, S., ... & Zhu, J. (2016). Development of a semi-analytical algorithm for the retrieval of suspended particulate matter from remote sensing over clear to very turbid waters. Remote Sensing, 8(3), 211.: doi.org/10.3390/rs8030211
• Loisel, H., Vantrepotte, V., Dessailly, D., & Mériaux, X. (2014). Assessment of the colored dissolved organic matter in coastal waters from ocean color remote sensing. Optics Express, 22(11), 13109-13124.: doi.org/10.1364/OE.22.013109
• André Morel and Bernard Gentili, "Diffuse reflectance of oceanic waters. III. Implication of bidirectionality for the remote-sensing problem," Appl. Opt. 35, 4850-4862 (1996): doi.org/10.1364/AO.35.004850
• Brown, O. B., Minnett, P. J., Evans, R., Kearns, E., Kilpatrick, K., Kumar, A., ... & Závody, A. (1999). MODIS infrared sea surface temperature algorithm algorithm theoretical basis document version 2.0. University of Miami, 31, 098-33.: oceancolor.gsfc.nasa.gov/docs/technical/atbd_mod25.pdf