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2018_extent_CI_data

Metadata Updated: September 24, 2022

Full resolution (300m), weekly MERIS data were obtained over the contiguous United States for 2008 through 2011. Seven day composite images were created by retaining the maximum value detected for each pixel within the time period and then the monthly mean of the maximums was calculated. A spatial mosaic composed of 54 individual scenes was generated for each week resulting in a total of 208 CONUS images from 2008 to 2011. Weekly OLCI data were also retrieved from January 2017 through December 2017. MERIS and OLCI data were processed by the NASA OBPG, using the SeaWiFS Data Analysis System, SRTM static land mask, and a transformation to Albers Equal Area with an area-weighted interpolation to match the projections of the National Hydrography Dataset High Resolution. The SRTM land mask and SeaDAS processing is static in relation to waterbody size and did not account for periods of drought nor flood during the study period. Any water pixel adjacent to the SRTM static land mask was automatically flagged and excluded from analysis to reduce potential for mixed land-water pixels and land adjacency effects. To avoid pixel misclassification due to artifacts such as bridges, catchment facilities, and islands, “valid” water pixels were determined by examining the ESRI World Imagery Basemap. This manual operator pixel selection process lowered the potential that land pixels were not misclassified as water or vice versa. Each 300m satellite pixel in a weekly CONUS map represents a provisional maximum Cyanobacteria Index (CI) value retrieved in the specific time period. The provisional CI was calculated using a spectral shape (SS) algorithm detailed and validated elsewhere.

Conventional methods to distinguish between ice and water often fail due to high ice reflectance as well as the possibility of cyanobacterial biomass formation under the ice. Therefore, weekly MERIS data were masked for the presence of ice and snow using Interative Multisensor Snow and Ice Mapping System (IMS) Northern Hemisphere Snow and Ice Analysis data (Version 1, 4km). Daily snow and ice data were obtained from the National Snow and Ice Data Center then cropped to the extent of CONUS. Snow and ice data were temporally binned into maximum weekly time composites to match the MERIS data and then converted from raster to shapefile format. If MERIS or OLCI CI values were within the spatial area of the snow and ice mask, they were removed from further analysis. 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). NOTE: This dataset has been removed from public access due to revocation. Please refer inquiries regarding this dataset to the listed contact person.

Access & Use Information

Public: This dataset is intended for public access and use. License: See this page for license information.

Downloads & Resources

No file downloads have been provided. The publisher may provide downloads in the future or they may be available from their other links.

Dates

Metadata Created Date November 12, 2020
Metadata Updated Date September 24, 2022

Metadata Source

Harvested from EPA ScienceHub

Additional Metadata

Resource Type Dataset
Metadata Created Date November 12, 2020
Metadata Updated Date September 24, 2022
Publisher U.S. EPA Office of Research and Development (ORD)
Maintainer
Identifier https://doi.org/10.23719/1423890
Data Last Modified 2018-03-01
Public Access Level public
Bureau Code 020:00
Schema Version https://project-open-data.cio.gov/v1.1/schema
Harvest Object Id 8f3f9b85-8327-4214-a7cc-65007350ac34
Harvest Source Id 04b59eaf-ae53-4066-93db-80f2ed0df446
Harvest Source Title EPA ScienceHub
License https://pasteur.epa.gov/license/sciencehub-license.html
Program Code 020:096
Publisher Hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
Source Datajson Identifier True
Source Hash 623297766d8b745a118ab468ff0e426fc00f5dde
Source Schema Version 1.1

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