Cyanobacteria Assessment Network (CyAN) is a multi-agency project among EPA, the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the United States Geological Survey (USGS) to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying cyanobacteria algal blooms. This effort has resulted in the production of satellite remote sensing products using the cyanobacteria index (CI) algorithm to estimate cyanobacteria concentrations (CI_cyano) in lakes across the contiguous United States (CONUS) and Alaska. The Merged S3 product combines Sentinel-3A and Sentinel-3B OLCI data.

Cyanobacteria Assessment Network (CyAN) is a multi-agency project among EPA, the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the United States Geological Survey (USGS) to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying cyanobacteria algal blooms. This effort has resulted in the production of satellite remote sensing products using the cyanobacteria index (CI) algorithm to estimate cyanobacteria concentrations (CI_cyano) in lakes across the contiguous United States (CONUS) and Alaska. The Merged S3 product combines Sentinel-3A and Sentinel-3B OLCI data.

The Inland Waters dataset (ILW) provides data for lakes and other water bodies across the contiguous United States (CONUS) and Alaska. ILW significantly reduces the processing effort required by end users and is a standardized community resource for lake and reservoir algorithm development and performance assessment. The data is provided for 15,450 CONUS waterbodies with a size of at least one 300 m pixel and over 2,300 resolvable lakes with sizes greater than three 300 m pixels. Alaska has 5,874 lakes resolvable lakes. ILW was developed in collaboration with the Cyanobacteria Assessment Network (CyAN). Additional inland water details and resources, including maps of resolvable lakes and additional inland water products, such as true color imagery, are available at the CyAN site.

The Inland Waters dataset (ILW) provides data for lakes and other water bodies across the contiguous United States (CONUS) and Alaska. ILW significantly reduces the processing effort required by end users and is a standardized community resource for lake and reservoir algorithm development and performance assessment. The data is provided for 15,450 CONUS waterbodies with a size of at least one 300 m pixel and over 2,300 resolvable lakes with sizes greater than three 300 m pixels. Alaska has 5,874 lakes resolvable lakes. ILW was developed in collaboration with the Cyanobacteria Assessment Network (CyAN). Additional inland water details and resources, including maps of resolvable lakes and additional inland water products, such as true color imagery, are available at the CyAN site.

The Ocean and Land Colour Instrument (OLCI) is the successor to ENVISAT's Medium Resolution Imaging Spectrometer (MERIS) having additional spectral channels, different camera arrangements and simplified on-board processing. The OLCI is a push-broom instrument with five camera modules sharing the field of view. The field of view of the five cameras is arranged in a fan-shaped configuration in the vertical plane, perpendicular to the platform velocity. Each camera has an individual field of view of 14.2° and a 0.6° overlap with its neighbors. The whole field of view is shifted across track by 12.6° away from the sun to minimize the impact of sun glint. OLCI is equipped with on-board calibration hardware based on sun diffusers. There are three sun diffusers--two 'white' diffusers dedicated to radiometric calibration and one dedicated to spectral calibration, with spectral reflectance features. The native resolution is approximately 300m, refered to as Full Resolution (FR). A Reduced Resolution (RR) processing mode provides Level-1B data at sampling rates decreased by a factor of four in both spatial dimensions resulting to resolution of approximately 1.2 km.

Weekly averaged data from USF virtual buoys text files

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).