{cbc14b6b-8181-4e45-b1c3-5600a1cd0ba2} eng; USA utf8 dataset EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas pointOfContact 2025-07-23 ISO 19115 Geographic Information - Metadata ISO 19115:2003/Cor.1:2006(E) EnviroAtlas -- Cyanobacteria Index for the Continental United States 2017-01-01 publication U.S. EPA Office of Research & Development (ORD) - Center for Environmental Measurement and Modeling (CEMM) Research Triangle Park NC publisher National Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA), the United States Geological Survey (USGS), and the US Environmental Protection Agency (US EPA) originator This dataset shows the temporal frequency and spatial extent of cyanobacteria cells in large, freshwater lakes and reservoirs across the continental United States derived from 300x300 meter MEdium Resolution Imaging Spectrometer (MERIS) satellite imagery from 2002-2012 and functionally similar Ocean and Land Colour Instrument (OLCI) satellite imagery from 2017-2021. This dataset was produced through a partnership with the National Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA), the United States Geological Survey (USGS), and the United States Environmental Protection Agency (USEPA). This cyanobacteria dataset was derived using the European Space Agency's (ESA) Envisat MERIS sensor and their Sentinel-3 OLCI sensor. MERIS and OLCI are nadir-pointing imaging spectrometers which measure the solar radiation reflected by the Earth in 15 and 21 spectral bands, respectively (visible through near-infrared). MERIS and OLCI imagery was used to identify long-wavelength spectral bands (from red through near-infrared portion of the spectrum) to locate algal blooms within freshwaters and estuaries of the continental United States. EnviroAtlas allows users to spatially explore this cyanobacteria data in the online interactive map viewer. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the continental United States. The dataset is available as downloadable data (https://oceancolor.gsfc.nasa.gov/CYAN/) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets). The purpose is to provide a standard and uniform dataset to support identification of algal blooms that is useful and accessible to stakeholders of freshwater systems. The overall goal of EnviroAtlas is to employ and develop the best available science to map indicators of ecosystem services production, demand, and drivers for the nation. completed EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas pointOfContact NOTPLANNED Ecosystem Environment Estuary Natural Resources Surface Water Water theme EPA GIS Keyword Thesaurus Drinking Water Ecosystem Services EnviroAtlas Environment Environmental Atlas Estuary Habitat Hazards Health Monitoring Surface Water Toxics Water theme User Alabama Arizona Arkansas California Colorado Connecticut Delaware Florida Georgia Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas United States Utah Vermont Virginia Washington Washington DC West Virginia Wisconsin Wyoming place None https://edg.epa.gov/EPA_Data_License.html otherRestrictions Use Constraints: None. Please check sources, scale, accuracy, currency and other available information. Please confirm that you are using the most recent copy of both data and metadata. Users should acknowledge the Cyanobacteria Assessment Network that was supported by the NASA Ocean Biology and Biogeochemistry Program/Applied Sciences Program (proposals 14-SMDUNSOL14- 0001 and SMDSS20-000), and by U.S. EPA, NOAA, and USGS. otherRestrictions Access Constraints: None PUBLIC https://project-open-data.github.io/schema/#accessLevel Standard Technical Controls eng; USA environment inlandWaters -128.02839229 -65.20336449 22.7348894 51.6773602 2008-01-01 2021-01-01 This cyanobacteria image data is stored in 8-bit geotiff. The nominal size of each full-resolution pixel is 300 meters. File naming is with the following convention: sensoryyyydddyyyyddd.datalevel_temporalresolution_variable_version_resolution_region where: sensor = first initial of sensor, M indicates MERIS and L indicates OLCI yyyydddyyyyddd = start date and end date in a multiday; January 1 = 1; December 31 in a non-leap year = 365; datalevel = L3m is the high resolution MERIS/OLCI imagery; temporalresolution = 7D is seven day variable = CYAN is Cyanobacteria Assessment Network, CI is Cyanobacterial Index, cyano is cyanobacteria; version = CYAN_CONUS is Cyanobacteria Assessment Network Continental United States; resolution = 300 m imagery resolution for high resolution region = 7_1 is the CyAN regional grid identification number; Areas with no data, land, and cloudcover are flagged where: 0 indicates below detection, 1-253 are data, 254 is land, 255 are no data. Data are primarily provided as 7-day composites. However, data for MERIS are provided as 14-day composites from 2002-2007, when the instrument irregularly viewed the US and as 7-day composites from 2008-2012, when the instrument regularly collected data over the US. These data are validated Stage 2 of 4 on NASA's data maturity level ranking. This is defined as "data product accuracy is estimated using a significant set (although not full US/global) of independent measurements obtained from selected locations and time periods and ground-truth/field program efforts. There have been some peer-reviewed publications on the accuracy, but for limited spatial areas." Additional details on NASA's data maturity levels can be found at https://science.nasa.gov/earth-science/earth-science-data/data-maturity-levels. For details on data product validation efforts and applications, see Binding et al. [2011], Matthews et al. [2012], Moradi [2014], Lunetta et al. [2015], Matthews and Odermatt [2015], Palmer et al. [2015a], Palmer et al. [2015b], Tomlinson et al. [2016], Urquhart et al. [2017], Clark et al. [2017], Schaeffer et al. [2018], Coffer et al. [2020], Coffer et al. [2021], Seegers et al. [2021], and Mishra et al. [2021]. Processing version and reprocessing schedule: All data are processing version 3 (August 2020). Data are preliminary and to be used for evaluation purposes only. Known outstanding issues are listed below. The CyAN Project and OBPG will periodically reprocess and redistribute the MERIS and OLCI CI-cyano timeseries. Reprocessing will occur approximately every 6 to 12 months. Known issues: The following issues will be addressed or resolved in future releases of these data. (1) A snow/flag that identifies ice has been applied, but has not yet been verified. Ice can potentially register as high CI-cyano counts, so caution should be used where snow/ice might be visible. It is currently unknown if CyAN could detect cyanobacteria under thin ice in lakes and reservoirs. (2) The SRTM land mask may cover dry lakes, and may exclude other lakes. There is a need for an eroded landmask. (3) A flag has been added to identify mixed pixels that are potentially inclusive of land and water. The flag has not yet been verified, so caution should be used where mixed pixels may occur at the land/water interface. (4) Undetected thin clouds can potentially register as high CI-cyano counts (elevating CI-cyano beyond the minimum detect threshold value). (5) Retrievals are considered more robust for lakes ≥ 900 m window width as defined in Clark et al. [2017]. This 900 m window width provides a minimum of a 3 x 3-pixel array in a water body. Smaller water bodies and rivers are not masked and their data may be erroneous. (6) Satellite data processing does not account for changes in water levels due to cycles such as drought and flood. (7) Published US validation locations are Lake Erie, Florida, Ohio, Vermont, New Hampshire, Rhode Island, Connecticut, Massachusetts, Oregon, California, Indiana, New Jersey, New York, Utah, New Hampshire, Vermont, Maine, California, Oregon, and Idaho. References Binding, C. E., T. A. Greenberg, J. H. Jerome, R. P. Bukata, and G. Letourneau (2011), An assessment of MERIS algal products during an intense bloom in Lake of the Woods, Journal of Plankton Research, 33(5), 793-806, doi:10.1093/plankt/fbq133. Clark, J. M., B. A. Schaeffer, J. A. Darling, E. A. Urquhart, J. M. Johnston, A. R. Ignatius, M. H. Myer, K. A. Loftin, P. J. Werdell, and R. P. Stumpf (2017), Satellite monitoring of cyanobacterial harmful algal bloom frequency in recreational waters and drinking water sources, Ecological Indicators, 80(84-95), doi:10.1016/j.ecolind.2017.04.046. Coffer, M.M. B.A. Schaeffer, J.A. Darling, E.A. Urquhart, and W.B. Salls (2020), Quantifying national and regional cyanobacterial occurrence in US lakes using satellite remote sensing, Ecological Indicators, 111, doi: 10.1016/j.ecolind.2019.105976. Coffer, M. M., B.A. Schaeffer, K. Foreman, A. Porteous, K.A. Loftin, R.P. Stumpf, P.J. Werdell, E.A. Urquhart, R.J. Albert, and J.A. Darling (2021), Assessing cyanobacterial frequency and abundance at surface waters near drinking water intakes across the United States, Water Research, 201, doi: 10.1016/j.watres.2021.117377. Lunetta, R. S., B. A. Schaeffer, R. P. Stumpf, D. Keith, S. A. Jacobs, and M. S. Murphy (2015), Evaluation of cyanobacteria cell count detection derived from MERIS imagery across the eastern USA, Remote Sensing of Environment, 157, 24-34, doi:10.1016/j.rse.2014.06.008. Matthews, M. W., S. Bernard, and L. Robertson (2012), An algorithm for detecting trophic status (chlorophyll-a), cyanobacterial-dominance, surface scums and floating vegetation in inland and coastal waters, Remote Sensing of Environment, 124, 637-652, doi:10.1016/j.rse.2012.05.032. Matthews, M. W., and D. Odermatt (2015), Improved algorithm for routine monitoring of cyanobacteria and eutrophication in inland and near-coastal waters, Remote Sensing of Environment, 156, 374-382, doi:10.1016/j.rse.2014.10.010. Mishra, S., R.P. Stumpf, B.A. Schaeffer, P.J. Werdell, K.A. Loftin, and A. Meredith, (2021), Evaluation of a satellite-based cyanobacteria bloom detection algorithm using field-measured microcystin data, Science of the Total Environment, 774, doi: 10.1016/j.scitotenv.2021.145462. Moradi, M. (2014), Comparison of the efficacy of MODIS and MERIS data for detecting cyanobacterial blooms in the southern Caspian Sea, Marine Pollution Bulletin, 87(1-2), 311-322, doi:10.1016/j.marpolbul.2014.06.053. Palmer, S. C. J., et al. (2015a), Validation of Envisat MERIS algorithms for chlorophyll retrieval in a large, turbid and optically-complex shallow lake, Remote Sensing of Environment, 157, 158-169, doi:10.1016/j.rse.2014.07.024. Palmer, S. C. J., D. Odermatt, P. D. Hunter, C. Brockmann, M. Presing, H. Balzter, and V. R. Toth (2015b), Satellite remote sensing of phytoplankton phenology in Lake Balaton using 10 years of MERIS observations, Remote Sensing of Environment, 158, 441-452, doi:10.1016/j.rse.2014.11.021. Schaeffer, B. A., K. Loftin, R. P. Stumpf, and P. J. Werdell (2015), Agencies collaborate, develop a cyanobacteria assessment network, EOS Trans. AGU, 96(23), 16-20. Schaeffer, B.A., S.W. Bailey, R.N. Conmy, M. Galvin, A.R. Ignatius, J.M. Johnston, D.J. Keith, R.S. Lunetta, Parmar, R.P. Stumpf, E.A. Urquhart, P.J. Werdell, and K. Wolfe (2018), Mobile device application for monitoring cyanobacteria harmful algal blooms using Sentinel-3 satellite Ocean and Land Colour Instruments, Environmental Modelling & Software, 109(93-103), doi: 10.1016/j.envsoft.2018.08.015. Seegers, B.N., P.J. Werdell, R.A. Wandermeulen, W.B. Salls, R.P. Stumpf, B.A. Schaeffer, T.J. Owens, S.W. Bailey, J.P. Scott, and K.A. Loftin, (2021), Satellites for long-term monitoring of inland U.S. lakes: The MERIS time series and application for chlorophyll-a, Remote Sensing of Environment, 266, Doi: 10.1016/j.rse.2021.112685. Tomlinson, M. C., R. P. Stumpf, T. T. Wynne, D. Dupuy, R. Burks, J. Hendrickson, and R. S. Fulton (2016), Relating chlorophyll from cyanobacteria-dominated inland waters to a MERIS bloom index, Remote Sensing Letters, 7(2), 141-149, doi:10.1080/2150704x.2015.1117155. Urquhart, E. A., B. A. Schaeffer, R. P. Stumpf, K. A. Loftin, and P. J. Werdell (2017), A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing, Harmful Algae, 67, 144-152, doi:10.1016/j.hal.2017.06.001. Wynne, T. T., R. P. Stumpf, M. C. Tomlinson, and J. Dyble (2010), Characterizing a cyanobacterial bloom in western Lake Erie using satellite imagery and meteorological data, Limnology and Oceanography, 55(5), 2025-2036, doi:10.4319/lo.2010.55.5.2025. Wynne, T. T., R. P. Stumpf, M. C. Tomlinson, R. A. Warner, P. A. Tester, J. Dyble, and G. L. Fahnenstiel (2008), Relating spectral shape to cyanobacterial blooms in the Laurentian Great Lakes, International Journal of Remote Sensing, 29(12), 3665-3672, doi:10.1080/01431160802007640. true Entity and Attribute Information Entity and Attribute Overview: This dataset shows the temporal frequency and spatial extent of cyanobacteria cells in large, freshwater lakes and reservoirs across the continental United States derived from 300x300 meter MEdium Resolution Imaging Spectrometer (MERIS) and Ocean and Land Colour Instrument (OLCI) satellite imagery. This dataset was produced through a partnership with the National Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA), the United States Geological Survey (USGS), and the United States Environmental Protection Agency (USEPA). This cyanobacteria dataset was derived using the European Space Agency (ESA) Envisat MERIS sensor and the Sentinel-3 OLCI sensor. MERIS and OLCI are nadir-pointing imaging spectrometers which measure the solar radiation reflected by the Earth in 15 and 21 spectral bands, respectively (visible through near-infrared). MERIS and OLCI imagery was used to identify long-wavelength spectral bands (from red through near-infrared portion of the spectrum) to locate algal blooms within freshwaters and estuaries of the continental United States. Citation: Clark, J.M., B.A. Schaeffer, J.A. Darling, E.A. Urquhart, J.M. Johnston, A.R. Ignatius, M.H. Myer, K.A. Loftin, P.J. Werdell, and R.P. Stumpf. 2017. Satellite monitoring of cyanobacterial harmful algal bloom frequency in recreational waters and drinking water sources. Ecological Indicators 80:84-95. Coffer, M.M., B.A. Schaeffer, W.B. Salls, E.A. Urquhart, K.A. Loftin, R.P. Stumpf, P.J. Werdell, and J.A. Darling. 2021. Satellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales. Ecological Indicators 128. doi:10.1016/j.ecolind.2021.107822. Entity and Attribute Detail Citation: https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas distributor https://enviroatlas.epa.gov/download/CyanLakes_poly_public_FGDB.zip download Download The URL providing direct access to the downloadable dataset. download https://enviroatlas.epa.gov/download/CyanLakes_poly_public_CSV.zip ESRI:ArcGIS API The endpoint of a web service to access the dataset (REST endpoint, WMS GetCapabilities URL, or a SOAP WSDL endpoint). webMapService https://oceancolor.gsfc.nasa.gov/CYAN/ information Documentation URL for accessing related documents such as data dictionary, technical information about a dataset, developer documentation, etc. information https://services.arcgis.com/cJ9YHowT8TU7DUyn/arcgis/rest/services/CyanLakes_poly_public/FeatureServer information Home Page Alternative landing page used to redirect user to a contextual, Agency-hosted "homepage" for the Dataset or API information dataset Horizontal Positional Accuracy Report Data were collected using methods that have unknown accuracy (EPA National Geospatial Data Policy [NGDP] Accuracy Tier 10). For more information, please see EPA's NGDP at https://epa.gov/geospatial/policies.html Features represented have not been tested for completeness Features represented have not been tested for completeness Tests for integrity have not been performed. This lineage was generated by the FGDC CSDGM to 19139 transformation Acquired full resolution (300 m) imagery from European Space Agency's MEdium Resolution Imaging Spectrometer (MERIS) and Ocean and Land Colour Instrument (OLCI). Standard MERIS and OLCI Level-1B data archived at the NASA Ocean Color website. Data processing guidance provided by Jeremy Werdell, NASA. 2017-02-17T00:00:00 Jeremy Werdell NASA Goddard Space Flight Center Geospatial Data Owner (301) 286-1440 (000) 000-0000 Mail Code 616.2 000 Greenbelt MD 20771 jeremy.werdell@nasa.gov https://oceandata.sci.gsfc.nasa.gov/api/cyan_file_search/ processor Data were processed using NOAA satellite automated processing system, which incorporates the NASA standard ocean color satellite processing software distributed within the NASA Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Data Analysis System (SeaDAS, version 7.1 and above) package and the Shuttle Radar Topography Mission (SRTM) GC 60-meter land mask. Data processing guidance provided by Jeremy Werdell, NASA. 2017-02-17T00:00:00 Jeremy Werdell NASA Goddard Space Flight Center Geospatial Data Owner (301) 286-1440 (000) 000-0000 Mail Code 616.2 000 Greenbelt MD 20771 jeremy.werdell@nasa.gov https://oceancolor.gsfc.nasa.gov/ processor Estimates of spectral surface albedo (Rhos) were generated by removing Rayleigh radiances from the top-of-atmosphere signal measured by the satellite. Algorithm guidance provided by Rick Stumpf, NOAA. 2017-02-17T00:00:00 Richard P Stumpf National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science Geospatial Data Owner (240) 533-0338 (000) 000-0000 1305 East West Highway Rm 8110 Silver Spring MD 20910 richard.stumpf@noaa.gov processor Clouds were masked using a spectral albedo threshold algorithm that accounts for turbid water to eliminate misidentification of intense blooms' bright reflectances as clouds. Algorithm guidance provided by Rick Stumpf, NOAA. 2017-02-17T00:00:00 Richard P Stumpf National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science Geospatial Data Owner (240) 533-0338 (000) 000-0000 1305 East West Highway Rm 8110 Silver Spring MD 20910 richard.stumpf@noaa.gov processor Mixed land-water pixels were identified when Rhos(885) was > both Rhos(709) and Rhos(754). The Rhos estimates were used to calculate the Cyanobacteria Index (CI-cyano) from two spectral shape algorithms: one centered at 681 nanometers(nm) and the other centered at 665 nm. Algorithm guidance provided by Rick Stumpf, NOAA. 2017-02-17T00:00:00 Richard P Stumpf National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science Geospatial Data Owner (240) 533-0338 (000) 000-0000 1305 East West Highway Rm 8110 Silver Spring MD 20910 richard.stumpf@noaa.gov processor CyanoHAB (Cyanobacterial harmful algal blooms) abundance was then calculated as cells per milliliter (cell mL-1) where cyanoHAB abundance = 1.0 X 10^8*CI-cyano. Water quality interpretation guidance provided by Blake Schaeffer, EPA. 2017-02-17T00:00:00 Blake Schaeffer U.S. Environmental Protection Agency, Office of Research and Development Geospatial Data Owner (919) 541-5571 (919) 541-4329 109 T.W. Alexander Drive E266 Research Triangle Park NC 27709 schaeffer.blake@epa.gov https://www.epa.gov/water-research/cyanobacteria-assessment-network-cyan-project processor Weekly 7-day composite images were created by retaining the maximum value detected for each pixel within the time period. Data processing guidance provided by Jeremy Werdell, NASA. 2017-02-17T00:00:00 Jeremy Werdell NASA Goddard Space Flight Center Geospatial Data Owner (301) 286-1440 (000) 000-0000 Mail Code 616.2 000 Greenbelt MD 20771 jeremy.werdell@nasa.gov https://oceancolor.gsfc.nasa.gov/ processor The weekly composites were transformed to Albers Equal Area projection with an area-weighted interpolation to match the projections of the National Hydrography Dataset (NHD). Data processing guidance provided by Jeremy Werdell, NASA. 2017-02-17T00:00:00 Jeremy Werdell NASA Goddard Space Flight Center Geospatial Data Owner (301) 286-1440 (000) 000-0000 Mail Code 616.2 000 Greenbelt MD 20771 jeremy.werdell@nasa.gov https://oceancolor.gsfc.nasa.gov/ processor unknown 2029-07-23 This metadata was automatically generated from the FGDC Content Standard for Digital Geospatial Metadata standard (version FGDC-STD-001-1998) using the 2024-02-09T11:11:00 version of the FGDC CSDGM to ISO 19139 transform. EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas pointOfContact