ESA Envisat MERIS 300mx300m raster ocean color data using cyanobacteria index (CI) algorithm. This dataset is associated with the following publication: Coffer, M., B. Schaeffer, J. Darling, E. Urquhart, and W. Salls. Quantifying national and regional cyanobacterial occurrence in US lakes using satellite remote sensing. ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 111: 105976, (2020).

This dataset shows the concentration of cyanobacteria cells/ml in fresh water bodies and estuaries of the Ohio and Florida derived from 300x300 meter MEdium Resolution Imaging Spectrometer (MERIS) satellite imagery. This dataset was produced through 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 satellite and MERIS instrument. MERIS is a 68.5 degree field-of-view nadir-pointing imaging spectrometer which measures the solar radiation reflected by the Earth in 15 spectral bands (visible and near-infrared). MERIS 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. This dataset is associated with the following publication: Urquhart, E., B. Schaeffer, R. Stumpf, K. Loftin, and J. Wedell. .A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing. Harmful Algae. Elsevier B.V., Amsterdam, NETHERLANDS, 67: 144-152, (2017).

This dataset shows the concentration of cyanobacteria cells/ml in fresh water bodies and estuaries of the Ohio and Florida derived from 300x300 meter MEdium Resolution Imaging Spectrometer (MERIS) satellite imagery. This dataset was produced through 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 satellite and MERIS instrument. MERIS is a 68.5 degree field-of-view nadir-pointing imaging spectrometer which measures the solar radiation reflected by the Earth in 15 spectral bands (visible and near-infrared). MERIS 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. This dataset is associated with the following publication: Urquhart, E., B. Schaeffer, R. Stumpf, K. Loftin, and J. Wedell. .A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing. Harmful Algae. Elsevier B.V., Amsterdam, NETHERLANDS, 67: 144-152, (2017).

MERIS and OLCI satellite data with CI_cyano algorithm quantify the spatial extent of cyanobacteria. This dataset is associated with the following publication: Schaeffer, B., E. Urquhart, M. Coffer, W. Salls, R. Stumpf, K. Loftin, and P.J. Werdell. Satellites quantify the spatial extent of cyanobacterial blooms across the United States at multiple scales. ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 140: 108990, (2022).

This dataset shows the concentration of cyanobacteria cells/ml in fresh water bodies and estuaries of the Ohio and Florida derived from 300x300 meter MEdium Resolution Imaging Spectrometer (MERIS) satellite imagery. This dataset was produced through 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 satellite and MERIS instrument. MERIS is a 68.5 degree field-of-view nadir-pointing imaging spectrometer which measures the solar radiation reflected by the Earth in 15 spectral bands (visible and near-infrared). MERIS 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. This dataset is associated with the following publication: Clark, J., B. Schaeffer, J. Darling, E. Urquhart, J. Johnston, A. Ignatius, M. Myer, K. Loftin, J. Werdell, and R. Stumpf. Methods for Monitoring Cyanobacterial Harmful Algal Bloom Frequency in Recreational Waters and Drinking Water Sources with Satellites. ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 80: 84-95, (2017).

Data represents satellite derived measures of cyanobacteria biomass across largest US lakes. This dataset is not publicly accessible because: Already publicly available at link below. It can be accessed through the following means: Original satellite files are publicly available at https://oceancolor.gsfc.nasa.gov/about/projects/cyan/. Format: GeoTIFF data, HE5 files. This dataset is associated with the following publication: Coffer, M., B. Schaeffer, W. Salls, J. Minucci, and O. Cronin-Golomb. Recommendations for temporal aggregation of water quality data from multi-platform satellite constellations. INTERNATIONAL JOURNAL OF REMOTE SENSING. Taylor & Francis, Inc., Philadelphia, PA, USA, 47(1): 177-199, (2026).

The dataset provided here contains the added pixel quality assurance (QA) flags that help ensure validity of satellite-derived water quality estimates in freshwater lakes and reservoirs. This work builds upon a study by Urquhart et al. [1] where inland lake and waterbody satellite data was processed and flagged for California, Ohio, and Florida. Added pixel QA flags include land-adjacent pixels, unresolvable waterbody pixels, and snow/ice pixels. Any water pixel adjacent to land is flagged to caution potential for mixed land-water pixels and land adjacency effects. A weekly QA flag mask is provided for snow/ice presence over lakes. The unresolvable QA flag mask contains inland waterbodies smaller than 27 hectares and/or with less than three 300m resolvable satellite pixels. An updated version of the Shuttle Radar Topography Mission (SRTM) Waterbody Data (SWBD) is provided to fix a land-waterbody mask error identified in Rhode Island and Massachusetts. The Research Environments MEaSUREs SRTM, used in the NASA data pre-processing, includes the Water Body Data Shapefiles (~30m) product. Version 3.0 of the SRTM contains the vectorized coastline masks used by National Geospatial-Intelligence Agency (NGA) in the editing, called the SRTM Waterbody Data, in shapefile and rasterized formats [4]. Version 4.0 of the SRTM presented here fixes the land-waterbody mask error identified in Rhode Island and Massachusetts. Version 4.0 of the SRTM has been adopted into the NASA pre-processing of the MERIS and OLCI satellite datafiles described above. This dataset is associated with the following publication: Urquhart, E., and B. Schaeffer. Envisat MERIS and Sentinel-3 OLCI satellite lake biophysical water quality flag dataset for the contiguous United States. Data in Brief. Elsevier B.V., Amsterdam, NETHERLANDS, 28: 104826, (2020).

The dataset provided here contains the added pixel quality assurance (QA) flags that help ensure validity of satellite-derived water quality estimates in freshwater lakes and reservoirs. This work builds upon a study by Urquhart et al. [1] where inland lake and waterbody satellite data was processed and flagged for California, Ohio, and Florida. Added pixel QA flags include land-adjacent pixels, unresolvable waterbody pixels, and snow/ice pixels. Any water pixel adjacent to land is flagged to caution potential for mixed land-water pixels and land adjacency effects. A weekly QA flag mask is provided for snow/ice presence over lakes. The unresolvable QA flag mask contains inland waterbodies smaller than 27 hectares and/or with less than three 300m resolvable satellite pixels. An updated version of the Shuttle Radar Topography Mission (SRTM) Waterbody Data (SWBD) is provided to fix a land-waterbody mask error identified in Rhode Island and Massachusetts. The Research Environments MEaSUREs SRTM, used in the NASA data pre-processing, includes the Water Body Data Shapefiles (~30m) product. Version 3.0 of the SRTM contains the vectorized coastline masks used by National Geospatial-Intelligence Agency (NGA) in the editing, called the SRTM Waterbody Data, in shapefile and rasterized formats [4]. Version 4.0 of the SRTM presented here fixes the land-waterbody mask error identified in Rhode Island and Massachusetts. Version 4.0 of the SRTM has been adopted into the NASA pre-processing of the MERIS and OLCI satellite datafiles described above. This dataset is associated with the following publication: Urquhart, E., and B. Schaeffer. Envisat MERIS and Sentinel-3 OLCI satellite lake biophysical water quality flag dataset for the contiguous United States. Data in Brief. Elsevier B.V., Amsterdam, NETHERLANDS, 28: 104826, (2020).

OLCI satellite data with CI_cyano algorithm quantify cyanobacteria. Air temperature, precipitation data from PRISM Climate group. This dataset is associated with the following publication: Schaeffer, B., N. Reynolds, H. Ferriby, W. Salls, D. Smith, J. Johnston, and M. Myer. Forecasting freshwater cyanobacterial harmful algal blooms for Sentinel-3 satellite resolved U.S. lakes and reservoirs. JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 349: 119518, (2024).

OLCI satellite data with CI_cyano algorithm quantify cyanobacteria. Air temperature, precipitation data from PRISM Climate group. This dataset is associated with the following publication: Schaeffer, B., N. Reynolds, H. Ferriby, W. Salls, D. Smith, J. Johnston, and M. Myer. Forecasting freshwater cyanobacterial harmful algal blooms for Sentinel-3 satellite resolved U.S. lakes and reservoirs. JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 349: 119518, (2024).