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1.
Sci Data ; 10(1): 760, 2023 11 08.
Artigo em Inglês | MEDLINE | ID: mdl-37938593

RESUMO

Over 4,400 large-scale solar photovoltaic (LSPV) facilities operate in the United States as of December 2021, representing more than 60 gigawatts of electric energy capacity. Of these, over 3,900 are ground-mounted LSPV facilities with capacities of 1 megawatt direct current (MWdc) or more. Ground-mounted LSPV installations continue increasing, with more than 400 projects appearing online in 2021 alone; however, a comprehensive, publicly available georectified dataset including spatial footprints of these facilities is lacking. The United States Large-Scale Solar Photovoltaic Database (USPVDB) was developed to fill this gap. Using US Energy Information Administration (EIA) data, locations of 3,699 LSPV facilities were verified using high-resolution aerial imagery, polygons were digitized around panel arrays, and attributes were appended. Quality assurance and control were achieved via team peer review and comparison to other US PV datasets. Data are publicly available via an interactive web application and multiple downloadable formats, including: comma-separated value (CSV), application programming interface (API), and GIS shapefile and GeoJSON.

2.
Sci Data ; 7(1): 15, 2020 01 13.
Artigo em Inglês | MEDLINE | ID: mdl-31932591

RESUMO

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 quarterly-updated data are available in a variety of formats, including an interactive web application, comma-separated 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.

3.
PeerJ ; 7: e7129, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31341727

RESUMO

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.

4.
Sci Data ; 2: 150060, 2015 Nov 24.
Artigo em Inglês | MEDLINE | ID: mdl-26601687

RESUMO

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.

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