Visual Impact Assessment of the Existing Land-based Wind Turbine Fleet of the Contiguous United States
This data submission contains GIS raster datasets mapping the visual impacts of the land-based wind turbine fleet in the Contiguous United States (CONUS). Two datasets are included, each presenting a different quantification of visual impacts:
1. Cumulative visual magnitude, measured as the percentage of a hypothetical observer's field of view that is occupied by all nearby wind turbines.
2. Visual impact rating, a human-interpretable estimate of the visual impacts ranging from "No Impact" to "Very High Impact", based on calibration to field-based ratings from trained observers.
Each dataset is 30m in resolution, covers the full extent of the CONUS, and is provided in the ESRI:102003 coordinate reference system.
For additional details and citation, please refer to the Gleason et al. (2025) paper below, which includes information on the methodology used to derive these datasets, how to interpret their values, and other relevant details and limitations.
Gleason, M., Lopez, A., Rivers, M., 2025. Mapping and characterizing the visual impacts of the existing US wind turbine fleet. Applied Energy 378, 124801. https://doi.org/10.1016/j.apenergy.2024.124801
Citation Formats
National Renewable Energy Lab. (2024). Visual Impact Assessment of the Existing Land-based Wind Turbine Fleet of the Contiguous United States [data set]. Retrieved from https://data.openei.org/submissions/8370.
Gleason, Michael, Lopez, Anthony, and Rivers, Marie. Visual Impact Assessment of the Existing Land-based Wind Turbine Fleet of the Contiguous United States. United States: N.p., 19 Mar, 2024. Web. https://data.openei.org/submissions/8370.
Gleason, Michael, Lopez, Anthony, & Rivers, Marie. Visual Impact Assessment of the Existing Land-based Wind Turbine Fleet of the Contiguous United States. United States. https://data.openei.org/submissions/8370
Gleason, Michael, Lopez, Anthony, and Rivers, Marie. 2024. "Visual Impact Assessment of the Existing Land-based Wind Turbine Fleet of the Contiguous United States". United States. https://data.openei.org/submissions/8370.
@div{oedi_8370, title = {Visual Impact Assessment of the Existing Land-based Wind Turbine Fleet of the Contiguous United States}, author = {Gleason, Michael, Lopez, Anthony, and Rivers, Marie.}, abstractNote = {This data submission contains GIS raster datasets mapping the visual impacts of the land-based wind turbine fleet in the Contiguous United States (CONUS). Two datasets are included, each presenting a different quantification of visual impacts:
1. Cumulative visual magnitude, measured as the percentage of a hypothetical observer's field of view that is occupied by all nearby wind turbines.
2. Visual impact rating, a human-interpretable estimate of the visual impacts ranging from "No Impact" to "Very High Impact", based on calibration to field-based ratings from trained observers.
Each dataset is 30m in resolution, covers the full extent of the CONUS, and is provided in the ESRI:102003 coordinate reference system.
For additional details and citation, please refer to the Gleason et al. (2025) paper below, which includes information on the methodology used to derive these datasets, how to interpret their values, and other relevant details and limitations.
Gleason, M., Lopez, A., Rivers, M., 2025. Mapping and characterizing the visual impacts of the existing US wind turbine fleet. Applied Energy 378, 124801. https://doi.org/10.1016/j.apenergy.2024.124801
}, doi = {}, url = {https://data.openei.org/submissions/8370}, journal = {}, number = , volume = , place = {United States}, year = {2024}, month = {03}}
Details
Data from Mar 19, 2024
Last updated Mar 11, 2025
Submitted Mar 11, 2025
Organization
National Renewable Energy Lab
Contact
Michael Gleason
Authors
Research Areas
Keywords
SitingLab, wind energy, onshore wind, wind turbines, visual impact assessment, viewsheds, GIS, 3D simulation, United StatesDOE Project Details
Project Name Spatial Analysis for Wind Technology Development
Project Number 34877
