Mapping the nation’s wind turbines 

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.

Assessment Experience

The USGS has extensive experience assessing energy resources, and it’s that expertise that makes the USGS qualified to assess nationwide impacts of wind energy development. One of the major reasons behind the success of USGS energy resource assessments is the scientifically robust methodology that underpins them.

USGS energy resource assessment methodologies are publicly available and are technically peer reviewed externally, and just as importantly, are used consistently in every assessment. That means that a USGS oil and gas assessment in Alaska provides comparable information to a USGS oil and gas assessment in Texas, or that a USGS geothermal assessment in California is comparable to a USGS geothermal assessment in Nevada.

A Different Kind of Assessment

USGS has recently undertaken a project to develop a methodology for assessing wind energy impacts on wildlife at a national scale. This research is different from previous USGS energy assessments. Instead of looking at technically recoverable resources of oil, gas, geothermal or coal, or even technically accessible storage areas for carbon sequestration, the USGS is developing a method for determining the impacts of a type of energy production. This work will merge the experience the USGS has creating assessment methodologies with its expertise in wildlife ecology and wind-wildlife research, as well as in land change science.

Wind energy can impact both wildlife and their habitats. Wildlife impacts include potential bird and bat mortality from collisions with turbine blades, and in some cases, species avoidance of habitat near turbines. Habitat impacts include the turbine pads in addition to service roads, transmission lines, substations, meteorological towers, and other structures associated with wind energy siting, generation, and transmission.

Turbine Locations

The first step in understanding the impact of wind energy development is to determine where the wind turbines are located. Prior to this study, there was no publicly available national-level data set of wind turbines. There were maps that showed turbines locations in a few states, and there were national-level maps that showed wind power facilities, but not individual turbines, or information about those turbines, such as height, blade length, or energy producing capacity.

To remedy the lack of information, the USGS created this publicly available national dataset and interactive mapping application of wind turbines. This dataset is built with publicly available data, as well as searching for and identifying individual wind turbines using satellite imagery. The locations of all wind turbines, including the publicly available datasets, were visually verified with high-resolution remote imagery to within plus or minus 10 meters.

Knowing the location of individual turbines, as well as information such as the make, model, height, area of the turbine blades, and capacity creates new opportunities for research, and important information for land and resource management. For example, turbine-level data will improve scientists’ ability to study wildlife collisions, the wakes causes by wind turbines, the interaction between wind turbines and ground based radar, and how wind energy facilities overlap with migratory flyways.

Next Steps

In addition to the value this powerful tool has to Federal and State land managers, non-governmental organizations, the energy industry, scientists, and the public, it will be a useful component in the methodology that the USGS is developing for assessing wind energy impacts. The USGS is bringing together scientists with expertise in landscape-level science, wildlife biology, and other associated disciplines to create the methodology. Once developed, the methodology will be externally peer-reviewed and tested with pilot-level data projects. Once peer reviewed, the revised methodology will be published for others to understand and use.