Wednesday, May 20, 2015
Revised May 4, 2015
USGS Publication: Data Series 817
The wind turbine dataset was updated as follows: It now includes new turbines listed in the Federal Aviation Administration (FAA) Obstacle Repository System (ORS) Digital Obstacle File (DOF) through March 2, 2014. This is 171 new turbines and over 1000 updated ORS numbers...
Thursday, May 14, 2015
USGS Technical Release
USGS has released a preliminary methodology to assess the population level impacts of onshore wind energy development on birds and bats.
Tuesday, February 11, 2014
Press Release & Publication
In response to the Department of Interior’s Powering Our Future initiative, the U.S. Geological Survey (USGS) has begun investigating how to assess the impacts of wind energy development on wildlife at a national scale.
Thursday, August 08, 2013
Publication: Data Series
This dataset represents an update to USGS Data Series 596. Locations and attributes of wind turbines in New Mexico, 2009 (available at http://pubs.usgs.gov/ds/596/). This updated New Mexico wind turbine Data Series provides geospatial data for all 562 wind turbines established within the State of New Mexico as of June 2011, an increase of 155 wind turbines from 2009.
Thursday, August 08, 2013
USGS Publication: Data Series 782
This dataset represents an update to USGS Data Series 597. Locations and attributes of wind turbines in Colorado, 2009 (available at http://pubs.usgs.gov/ds/597/). This updated Colorado wind turbine Data Series provides geospatial data for all 1,204 wind turbines established within the State of Colorado as of September 2011, an increase of 297 wind turbines from 2009.
Tuesday, June 19, 2012
Coal and Wind
Technical Announcement & Publication
Land and resource managers now have a comprehensive new map of coal and wind energy resources information for southwestern Wyoming. This map has been released by the U.S. Geological Survey and the Wyoming State Geological Survey, as Part A of a two part energy map and data series.
Wind energy is one of the fastest-growing sectors of renewable energy in the United States. About 3% of the total electricity in the United States was generated by wind turbines in 2012 (according to the U.S. Energy Information Administration), which is equivalent to the annual electricity use for about 12 million households. The amount of electricity generated by wind has increased from about 6 billion kilowatt hours (kw) in 2000 to 140 billion kw in 2012. In response to the Department of Interior’s Powering Our Future Initiative, the U.S. Geological Survey (USGS), Energy Resources Program has begun investigating how to assess the impacts of onshore wind energy development on wildlife at a national scale.
In order to investigate how to assess the impacts of wind energy development on wildlife, the Energy Resources Program has undertaken a project to develop a new methodology. This methodology is very different from previous USGS energy assessments. Instead of looking at technically recoverable resources of oil, gas, geothermal or coal, or technically accessible storage areas for carbon sequestration, the USGS is developing a methodology for determining the impacts of a type of energy development. This work merges the experience that the USGS has in creating assessment methodologies with its expertise in wildlife ecology and wind-wildlife research.
To aid in developing the methodology, the Wind Energy Impacts Assessment Methodology project will conduct several lines of research. The research topics include: a geospatial dataset of onshore, commercial scale, wind turbine locations in the United States; forecasting wind energy impacts on Indiana (Myotis sodalis) and little brown bats (M. lucifugus) using migratory connectivity models; assessing the population level effects of wind energy on birds using the North American Breeding Bird Survey; a framework to prioritize birds and bats killed at wind facilities based on the risk of wind energy development impacting the overall population; new analyses of bird and bat mortality data from United States wind farms; an evaluation of new data types and tools for determining the intensity of low-elevation flights of birds and bats; and geospatial analyses of how wind energy development affects land transformation.
Margo D. Corum
James E. Diffendorer
Matthew D. Merrill
Initiative to Map Wind Turbines in the United States
Until now, an accurate, complete, and publicly available geodataset of wind turbine infrastructure did not exist for the United States. Turbine-level data were required for the development of the impacts methodology because they improve our ability to model wind energy impacts on wildlife populations, assess the overlap between wind energy and wildlife, and study turbine-specific mortality.
The objective of the initiative is to develop a geospatial dataset that includes every commercial-scale, onshore, turbine location in the United States and compile associated attribute information describing the turbine and the facility.
The USGS developed the wind turbine dataset by synthesizing publicly available data from multiple sources. A key dataset was the Federal Aviation Administration’s (FAA) Digital Obstacles File (DOF). The DOF describes many known obstacles to aviators and includes wind turbines. In addition, facility information was derived from U.S. Energy Information Administration (EIA) databases and the no longer maintained Wind Energy Data and Information (WENDI) dataset from Oak Ridge National Laboratory.
High-resolution orthoimagery was used to verify the location of turbines listed in the DOF or to find and digitize turbines not in the DOF. Turbines not in the DOF were found by searching for facilities listed in the facility databases, or wind energy literature discovered from web searches. Sets of turbines were assigned to a facility based on matches between turbine counts, aerial photography, industry reports, press articles, and descriptions or maps found in environmental reports and planning documents. Turbine specifications were based on a variety of sources including model-specific lists of turbine dimensions and capacities found at company websites. These sources were used in conjunction with site descriptions, planning documents, or information found at the facility owner’s website. Quality control and error reduction was based on peer review of the data; cartographers checked each other’s work. All attributes in the database, including the digitized locations of each turbine, and the attribute information, were initially entered by one analyst then error checked and corrected by an independent analyst. Detailed information on our methods and attribute information can be found in the metadata file associated with the data series.
Science in Support of Wind Energy Impacts Assessment Methodology
See details on current projects below
Forecasting wind energy impacts on the Indiana and little brown bats
The Indiana bat is listed as Endangered under the Endangered Species Act, whereas the little brown bat is currently under consideration for listing. A theoretical framework has been developed that provides insight into the effects of wind energy on migratory patterns and spatial dynamics of bats.
USGS scientists in the Upper Midwest Environmental Science Center have developed a quantitative framework for understanding the impacts of wind energy development on migratory bats. Scientists are working on a migratory connectivity model for the Indiana (Myotis sodalis) and little brown bats (M. lucifugus) in collaboration with the U. S. Fish and Wildlife Service (FWS). Research focuses on parameterizing and applying the model to bat populations using data from (FWS). In addition to effects from wind energy, the model will consider the synergistic effects of White-nose Syndrome on bats, with plans to expand the model and evaluate the effects of climate change and other stressors on migratory bat species. The model being developed for bats will also be generalizable to other species, and the project's long term plans include researching what model features and attributes are necessary to assess the impact of multiple stressors on bats as well as potential wind energy impacts on a suite of wildlife species.
Contact: Wayne Thogmartin; email@example.com
Assessment of population-level impacts of wind energy development on avian species
Studies of the impacts of wind energy on wildlife often begin by monitoring and measuring direct mortality due to species colliding with turbines while flying. These incidental mortality events may or may not scale-up to increasing the risk of significant decline or extinction at the population level. The degree to which wind energy facilities are impacting species at the population-level may depend on several other factors or conditions. These factors may include the species behavioral response to the habitat loss or disturbance caused by the facility itself, the number of mortality events relative to the total population size, the time of year or season the mortality takes place, and the age or life-stage of individuals most likely to be impacted. This type of analysis is extremely data intensive and the necessary detail is currently not available for most species, even for heavily studied taxon, such as birds.
The purpose of this research task is to utilize one of the best available sources of long-term avian data, the North American Breeding Bird Survey (BBS), in conjunction with detailed spatio-temporal data on wind turbine locations to assess whether wind energy development alters the population trajectories of avian species. By making paired comparisons within and outside of wind development regions, as well as before and after wind development, this project will attempt to estimate the relative impact of wind on these species’ population dynamics through linear multivariate autoregressive state-space (MARSS) models. This approach will also allow the estimation of parameters that describe the basic population dynamics. These population dynamic parameters can then be used to predict the long-term viability of individual avian populations in different regions.
Contact: Wayne Thogmartin; firstname.lastname@example.org
Prioritizing birds and bats killed at wind facilities based on the risk of population consequences from turbine mortality
An array of bats and birds of various species have been killed by wind turbines across the United States. For some species, the levels of mortality caused by wind turbines may add little or no additional risk to the species' persistence, while for others, mortality from wind turbines may be of management concern.
USGS scientists are developing a transparent and reasonably rapid approach for prioritizing species by their relative risk to wind turbines. This method combines information from two main categories: the existing conservation status of a species and the potential impacts of collisions on population dynamics. The potential impacts assume a relationship between how much turbine mortality a species can endure before beginning to decline and a number of species traits, such as age at first reproduction, total reproductive output, and survival.
Contact: Jay Diffendorfer; email@example.com
An evaluation of the potential for new data types and tools to determine the intensity of low-elevation flights of birds and bats
In order to assess the effect of wind energy development on wildlife, it is necessary to know where birds and bats fly, especially during migration.
USGS scientists at the Northern Prairie Wildlife Research Center are evaluating a variety of data types for assessing the use of airspace by birds and bats. Among these are markers,such as leg bands on birds; radio telemetry, most recently involving satellite receivers; fixed-site radar facilities, such as NEXRAD Doppler radar weather monitors; mobile radar units; acoustic monitors; stable isotope analysis; photo-sensitive geolocators; genetic markers; and thermal cameras; and Internet tools such as eBird (ebird.org) and oldbird (oldbird.org).
The goal of this work is to refine range maps for species and demarcate migratory pathways to better quantify the proportion of the population exposed to wind turbines. These data are used to refine the species prioritization methods described above.
Contact: Doug Johnson; firstname.lastname@example.org
Systematic analysis of collision mortality data to investigate impacts of wind energy development on U.S. wildlife
Wildlife mortality from collisions with wind turbines is the most direct, visible, and well-documented impact of wind energy development. However, until recently, conclusions about collision rates have been tentative, based primarily on extrapolation of results from individual wind farms and non-systematic comparison of collision rates among sites. The collision mortality literature consists primarily of unpublished industry reports that are not widely available to researchers and the public. In a recent comprehensive meta-analysis based on data extracted from 67 published and unpublished data sets, it was estimated that between 140,000 and 328,000 birds are killed annually in the U.S. by colliding with new generation monopole wind turbines and that fatality rates increase with increasing turbine height (link to study: http://www.sciencedirect.com/science/article/pii/S0006320713003522).
Despite this advance in the analysis of collision mortality data, there remains great uncertainty regarding the full range of direct and indirect impacts posed to birds and bats by wind energy development. For example, bats experience high collision rates with turbines in some regions but few systematic analyses have been conducted to: 1) estimate national bat collision mortality at monopole wind turbines, 2) generate species-specific mortality estimates, and 3) incorporate species estimates into models of population dynamics. In addition, despite studies that have assessed how mortality estimates for individual wind farms are affected by biases such as imperfect detection by surveyors and scavenging of carcasses, no research has investigated how varying approaches to account for these biases influence national mortality estimates. The new turbine geodataset will enhance these mortality studies. First, new turbine attributes can be included in statistical models of mortality, such as rotor swept area. Second, mortality at wind farms is not uniform across turbines, and understanding why some turbines kill more or fewer animals than others can help with fine-scaling siting issues.
As part of the Wind Energy Impacts Assessment Methodology project, a Cooperative Ecosystem Studies Units (CESU) partnership with scientists at the Department of Natural Resource Ecology and Management, Oklahoma State University (OSU) was formed to collaborate on the research described above.
Contact: Scott Loss; email@example.com
Wind Energy Impacts on the Landscape
Studying how wind energy development affects land transformation
The goal of this work is to understand how the development of wind energy results in land transformation -- altered patterns of land cover, and to use this information to consider impacts to terrestrial species. Land transformation includes changes caused by surface disturbance and road development. These changes can affect species, especially those sensitive to habitat fragmentation.
USGS scientists are performing two types of analyses using data from 39 wind facilities. First, the total amount of land transformation was estimated by digitizing all forms of surface disturbance caused by the development of the facilities. Second, by digitizing the pre- and post-construction road networks, USGS scientists can study how wind facilities alter road networks (e.g. widening of existing roads, construction of new ones, and removal of others), and how this alteration changes the levels and spatial patterns of the remaining habitat.
Contact: Jay Diffendorfer; firstname.lastname@example.org
Downloadable Wind Energy Data
USGS Data Series DS-817, provides the greatest flexibility for analysis using a geographic information system (GIS) and is the recommended download for GIS users. Additional file formats and associated metadata files can be downloaded below:
- Google Earth KMZ (883 KB)
- Metadata html | xml (116 KB)
- Tabular Data csv (10 MB)
Web Service Endpoints
Service endpoints for wind turbine data are available here:
WindFarm – Wind Turbine Interactive Web Map
WindFarm, a product from the USGS Energy Resources Program, lets users visualize, inspect, interact, and download our most current wind turbine dataset through a simple web browser. The dataset represents industrial-scale onshore wind turbine locations in the United States through July 2013.
WindFarm lets users explore over 47,000 industrial-scale onshore wind turbine locations throughout the conterminous United States, Alaska, and Hawaii.
The database contains over 46,000 wind turbine records that have been collected, digitized, locationally verified, and internally quality controlled. Turbine sites were obtained from the Federal Aviation Administration Digital Obstacle File, through product release date July 22, 2013.
A high-resolution view of wind turbines in southern Idaho. Clicking on any turbine site allows users to see detailed information and technical specifications of the site.
Visual interpretation using high-resolution aerial imagery in a GIS was used to verify wind turbine positions. Turbines without Federal Aviation Administration Obstacle Repository System numbers were visually identified and point locations were added to the collection. Locational error is estimated at plus or minus 10 meters.
Through dynamic querying, windFarm lets users filter turbine data by attributes like capacity, total height, and blade length.
Technical specifications for turbines were assigned based on the wind turbine make and model as described in literature, specifications listed in the Federal Aviation Administration Digital Obstacle File, and information on the turbine manufacturer’s website. Some facility and turbine information on make and model did not exist or was difficult to obtain. Thus, uncertainty may exist for certain turbine specifications. Uncertainty was rated and a confidence was recorded for both location and attribution data quality. For additional details see USGS DS-817.
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Page Last Modified: Monday, May 18, 2015
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