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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).
Complete Metadata
| bureauCode |
[ "020:00" ] |
|---|---|
| describedBy | https://pasteur.epa.gov/uploads/10.23719/1503160/documents/SchaefferBlake_A-hdrr_metadata_20170306.docx |
| describedByType | application/vnd.openxmlformats-officedocument.wordprocessingml.document |
| identifier | https://doi.org/10.23719/1503160 |
| programCode |
[ "020:096" ] |
| references |
[ "https://doi.org/10.1016/j.dib.2019.104826" ] |
| rights | null |