Over 60,000 utility-scale wind turbines are installed in the United States as of October, 2019, representing over 97 gigawatts of electric power capacity; US wind turbine installations continue to grow at a rapid pace. Yet, until April 2018, no publicly-available, regularly updated data source existed to describe those turbines and their locations. Under a cooperative research and development agreement, analysts from three organizations collaborated to develop and release the United States Wind Turbine Database (USWTDB)-a publicly available, continuously updated, spatially rectified data source of locations and attributes of utility-scale wind turbines in the United States. Technical specifications and wind facility data, incorporated from five sources, undergo rigorous quality control. The location of each turbine is visually verified using high-resolution aerial imagery. The quarterlyupdated data are available in a variety of formats, including an interactive web application, commaseparated values (CSV), shapefile, and application programming interface (API). The data are used widely by academic researchers, engineers and developers from wind energy companies, government agencies, planners, educators, and the general public.
For more information on the USGS-the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment-visit http://www.usgs.gov or call 1-888-ASK-USGS (1-888-275-8747).For an overview of USGS information products, including maps, imagery, and publications, visit
Wind energy generation affects landscapes as new roads, pads, and transmission lines are constructed. Limiting the landscape change from these facilities likely minimizes impacts to biodiversity and sensitive wildlife species. We examined the effects of wind energy facilities’ geographic context on changes in landscape patterns using three metrics: portion of undeveloped land, core area index, and connectance index. We digitized 39 wind facilities and the surrounding land cover and measured landscape pattern before and after facility construction using the amount, core area, and connectivity of undeveloped land within one km around newly constructed turbines and roads. New facilities decreased the amount of undeveloped land by 1.8% while changes in metrics of landscape pattern ranged from 50 to 140%. Statistical models indicated pre-construction development was a key factor explaining the impact of new wind facilities on landscape metrics, with pre-construction road networks, turbine spacing, and topography having smaller influences. As the proportion of developed land around facilities increased, a higher proportion of the facility utilized pre-construction developed land and a lower density of new roads were built, resulting in smaller impacts to undeveloped landscapes. Building of new road networks was also a predictor of landscape fragmentation. Utilizing existing development and carefully placing turbines may provide opportunities to minimize the impacts of new wind energy facilities.
Wind energy is a rapidly growing form of renewable energy in the United States. While summary information on the total amounts of installed capacity are available by state, a free, centralized, national, turbine-level, geospatial dataset useful for scientific research, land and resource management, and other uses did not exist. Available in multiple formats and in a web application, these public domain data provide industrial-scale onshore wind turbine locations in the United States up to March 2014, corresponding facility information, and turbine technical specifications. Wind turbine records have been collected and compiled from various public sources, digitized or position verified from aerial imagery, and quality assured and quality controlled. Technical specifications for turbines were assigned based on the wind turbine make and model as described in public literature. In some cases, turbines were not seen in imagery or turbine information did not exist or was difficult to obtain. Uncertainty associated with these is recorded in a confidence rating.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.