[null,null,[],[],[],null,["# Global Ocean Colour: Bio-Geo-Chemical, L4, from Satellite Observations, Reflectance, OLCI 300M\n\nDataset Availability\n: 2023-04-01T00:00:00Z--2025-06-01T00:00:00Z\n\nDataset Provider\n:\n\n\n [Copernicus](https://doi.org/10.48670/moi-00279)\n\nCadence\n: 1 Month\n\nTags\n:\n[copernicus](/earth-engine/datasets/tags/copernicus) [marine](/earth-engine/datasets/tags/marine) [oceans](/earth-engine/datasets/tags/oceans) \n\n#### Description\n\nThe Global Ocean Colour (Copernicus-GlobColour) dataset is a Bio-Geo-Chemical\n(BGC) product developed by ACRI-ST. Derived from multiple satellite sources\nlike SeaWiFS, MODIS, and OLCI. It provides a comprehensive range of\noceanographic variables, including: Chlorophyll (CHL),\nPhytoplankton Functional types and sizes (PFT), Primary Production (PP),\nSuspended Matter (SPM), Secchi Transparency Depth (ZSD),\nDiffuse Attenuation (KD490), Particulate Backscattering (BBP),\nAbsorption Coefficient (CDM), Reflectance (RRS) and more.\n\nThis dataset is a global product from the Copernicus Marine Service (CMEMS).\nIt provides Remote-Sensing Reflectance (Rrs), a fundamental optical property\nof the water that represents the light leaving the ocean surface.\nDerived from the Ocean and Land Colour Instrument (OLCI), this L4 dataset is\nprocessed into a ready-to-use format. With an exceptionally high spatial\nresolution of 300 meters, this dataset is particularly valuable for detailed\ncoastal and regional studies of water quality and marine constituents.\n\nDocumentation:\n\n- [User's Guide](https://documentation.marine.copernicus.eu/PUM/CMEMS-OC-PUM.pdf)\n\n- [Quality Information Document](https://documentation.marine.copernicus.eu/QUID/CMEMS-OC-QUID-009-101to104-111-113-116-118.pdf)\n\n- [Copernicus Marine Datastore](https://data.marine.copernicus.eu/products)\n\n### Bands\n\n\n**Pixel Size**\n\n300 meters\n\n**Bands**\n\n| Name | Units | Pixel Size | Description |\n|----------------------|--------|------------|----------------------------------------------------------------------------------------------------------------------------------|\n| `RRS400` | sr\\^-1 | meters | Remote Sensing Reflectance at 400 nm |\n| `RRS400_uncertainty` | % | meters | Remote Sensing Reflectance at 400 nm - The uncertainty as measured in hundredths of a percent (e.g., a value of 5000 means 50%). |\n| `RRS412` | sr\\^-1 | meters | Remote Sensing Reflectance at 412 nm |\n| `RRS412_uncertainty` | % | meters | Remote Sensing Reflectance at 412 nm - The uncertainty as measured in hundredths of a percent (e.g., a value of 5000 means 50%). |\n| `RRS443` | sr\\^-1 | meters | Remote Sensing Reflectance at 443 nm |\n| `RRS443_uncertainty` | % | meters | Remote Sensing Reflectance at 443 nm - The uncertainty as measured in hundredths of a percent (e.g., a value of 5000 means 50%). |\n| `RRS490` | sr\\^-1 | meters | Remote Sensing Reflectance at 490 nm |\n| `RRS490_uncertainty` | % | meters | Remote Sensing Reflectance at 490 nm - The uncertainty as measured in hundredths of a percent (e.g., a value of 5000 means 50%). |\n| `RRS510` | sr\\^-1 | meters | Remote Sensing Reflectance at 510 nm |\n| `RRS510_uncertainty` | % | meters | Remote Sensing Reflectance at 510 nm - The uncertainty as measured in hundredths of a percent (e.g., a value of 5000 means 50%). |\n| `RRS560` | sr\\^-1 | meters | Remote Sensing Reflectance at 560 nm |\n| `RRS560_uncertainty` | % | meters | Remote Sensing Reflectance at 560 nm - The uncertainty as measured in hundredths of a percent (e.g., a value of 5000 means 50%). |\n| `RRS620` | sr\\^-1 | meters | Remote Sensing Reflectance at 620 nm |\n| `RRS620_uncertainty` | % | meters | Remote Sensing Reflectance at 620 nm - The uncertainty as measured in hundredths of a percent (e.g., a value of 5000 means 50%). |\n| `RRS665` | sr\\^-1 | meters | Remote Sensing Reflectance at 665 nm |\n| `RRS665_uncertainty` | % | meters | Remote Sensing Reflectance at 665 nm - The uncertainty as measured in hundredths of a percent (e.g., a value of 5000 means 50%). |\n| `RRS674` | sr\\^-1 | meters | Remote Sensing Reflectance at 674 nm |\n| `RRS674_uncertainty` | % | meters | Remote Sensing Reflectance at 674 nm - The uncertainty as measured in hundredths of a percent (e.g., a value of 5000 means 50%). |\n| `RRS681` | sr\\^-1 | meters | Remote Sensing Reflectance at 681 nm |\n| `RRS681_uncertainty` | % | meters | Remote Sensing Reflectance at 681 nm - The uncertainty as measured in hundredths of a percent (e.g., a value of 5000 means 50%). |\n| `RRS709` | sr\\^-1 | meters | Remote Sensing Reflectance at 709 nm |\n| `RRS709_uncertainty` | % | meters | Remote Sensing Reflectance at 709 nm - The uncertainty as measured in hundredths of a percent (e.g., a value of 5000 means 50%). |\n| `flags` | | meters | Land water mask bit. - 0: Water - 1: Land |\n\n### Terms of Use\n\n**Terms of Use**\n\nThis dataset is released for use under Service Level Agreement (SLA),\nusing the acronym \"CMEMS\" or the shortened name \"Copernicus Marine Service\"\nboth denote the E.U. Copernicus Marine Environment Monitoring Service.\nHighlights and key features of the licence are provided in this document\n[License](https://marine.copernicus.eu/user-corner/service-commitments-and-licence)\n\n### Citations\n\nCitations:\n\n- Copernicus Global Ocean Colour: Global Ocean Satellite Observations,\n ACRI-ST company (Sophia Antipolis, France) is providing Bio-Geo-Chemical\n (BGC) products based on the Copernicus-GlobColour processor.\n [doi:10.48670/moi-00279](https://doi.org/10.48670/moi-00279)\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar dataset =\n ee.ImageCollection('COPERNICUS/MARINE/OC_GLO_BGC/REFLECTANCE_OLCI_300M')\n .filter(ee.Filter.date('2025-03-01', '2025-06-01'));\n\nvar RRS412 = dataset.select('RRS412').mean();\nvar vis = {\n min: 0.000069,\n max: 0.017,\n palette:\n ['D7F9D0', '91CA85', '5AB05D', '129450', '0F7347', '195437', '122414'],\n};\nMap.setCenter(71, 52, 2);\nMap.addLayer(RRS412, vis, 'RRS412');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/COPERNICUS/COPERNICUS_MARINE_OC_GLO_BGC_REFLECTANCE_OLCI_300M) \n[Global Ocean Colour: Bio-Geo-Chemical, L4, from Satellite Observations, Reflectance, OLCI 300M](/earth-engine/datasets/catalog/COPERNICUS_MARINE_OC_GLO_BGC_REFLECTANCE_OLCI_300M) \nThe Global Ocean Colour (Copernicus-GlobColour) dataset is a Bio-Geo-Chemical (BGC) product developed by ACRI-ST. Derived from multiple satellite sources like SeaWiFS, MODIS, and OLCI. It provides a comprehensive range of oceanographic variables, including: Chlorophyll (CHL), Phytoplankton Functional types and sizes (PFT), Primary Production (PP), Suspended Matter (SPM), Secchi Transparency Depth ... \nCOPERNICUS/MARINE/OC_GLO_BGC/REFLECTANCE_OLCI_300M, copernicus,marine,oceans \n2023-04-01T00:00:00Z/2025-06-01T00:00:00Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/https://doi.org/10.48670/moi-00279)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_MARINE_OC_GLO_BGC_REFLECTANCE_OLCI_300M)"]]