10,000+ results returned
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Title: Photovoltaic Power (Tilted) Contour Lines, 100-Meter Intervals: United States, 1998-2005
Contributors:- Line data
- 2015
Summary: This line shapefile contains tilted photovoltaic solar power resource levels of watt hours per meter squared (Wh/m2) in the contiguous United States using 100-meter interval contour lines. Tilted photovoltaic panels are those that are angled in order to maximize exposure to direct sunlight. Tilt angles are often equal to the site's latitude but may vary throughout the year. This layer is a part of a collection of GIS data containing renewable and electric energy information for the U.S., including data on transmission lines, power plants and electricity substations. This layer can be used for estimates of solar resource potential. Hart Energy Publishing. (2015). Photovoltaic Power (Horizontal) Contour Lines, 100-Meter Intervals: United States, 1998-2005. Hart Energy Publishing. Available at: http://purl.stanford.edu/tt266jx1921 This data provides monthly average and annual average daily total solar resource averaged over surface cells of 0.1 degrees in both latitude and longitude, or about 10 km in size. This data was developed using the State University of New York/Albany satellite radiation model. This model was developed by Dr. Richard Perez and collaborators at the National Renewable Energy Laboratory and other universities for the U.S. Department of Energy. Specific information about this model can be found in Perez, et al. (2002). This model uses hourly radiance images from geostationary weather satellites, daily snow cover data, and monthly averages of atmospheric water vapor, trace gases, and the amount of aerosols in the atmosphere to calculate the hourly total insolation (sun and sky) falling on a horizontal surface. Atmospheric water vapor, trace gases, and aerosols are derived from a variety of sources. A modified Bird model is used to calculate clear sky direct normal (DNI). This is then adjusted as a function of the ratio of clear sky global horizontal (GHI) and the model predicted GHI. Where possible, existing ground measurement stations are used to validate the data. Nevertheless, there is uncertainty associated with the meterological input to the model, since some of the input parameters are not avalable at a 10km resolution. As a result, it is believed that the modeled values are accurate to approximately 15% of a true measured value within the grid cell. Due to terrain effects and other microclimate influences, the local cloud cover can vary significantly even within a single grid cell. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.
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Title: Alternative Fuel Filling Stations: United States, Fall 2014
Contributors:- Point data
- 2015
Summary: This point dataset shows the locations of alternative fuel filling stations in the United States. This layer is part of a collection of GIS data for renewable and electric energy in the U.S. This layer is from the 2014 Fall Quarter update (Update 1017). This shapefile can be used to locate alternative fuel filling stations in the United States. point dataset shows the locations of oil seed processing plants in the United States for 2013. This layer is a part of a collection of GIS data containing renewable and electric energy information for the U.S., including data on transmission lines, power plants and electricity substations. Hart Energy Publishing (2015). Alternative Fuel Filling Stations: United States, Fall 2014. Hart Energy Publishing. Available at: http://purl.stanford.edu/yh448wy2698. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.
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Title: Photovoltaic Power (Tilted) Contour Lines, 50-Meter Intervals: United States, 1998-2005
Contributors:- Line data
- 2015
Summary: This line shapefile contains tilted photovoltaic solar power resource levels of watt hours per meter squared (Wh/m2) in the contiguous United States using 50-meter interval contour lines. Tilted photovoltaic panels are those that are angled in order to maximize exposure to direct sunlight. Tilt angles are often equal to the site's latitude but may vary throughout the year. This layer is a part of a collection of GIS data containing renewable and electric energy information for the U.S., including data on transmission lines, power plants and electricity substations. This layer can be used for estimates of solar resource potential. Hart Energy Publishing. (2015). Photovoltaic Power (Horizontal) Contour Lines, 50-Meter Intervals: United States, 1998-2005. Hart Energy Publishing. Available at: http://purl.stanford.edu/gz526ym8943 This data provides monthly average and annual average daily total solar resource averaged over surface cells of 0.1 degrees in both latitude and longitude, or about 10 km in size. This data was developed using the State University of New York/Albany satellite radiation model. This model was developed by Dr. Richard Perez and collaborators at the National Renewable Energy Laboratory and other universities for the U.S. Department of Energy. Specific information about this model can be found in Perez, et al. (2002). This model uses hourly radiance images from geostationary weather satellites, daily snow cover data, and monthly averages of atmospheric water vapor, trace gases, and the amount of aerosols in the atmosphere to calculate the hourly total insolation (sun and sky) falling on a horizontal surface. Atmospheric water vapor, trace gases, and aerosols are derived from a variety of sources. A modified Bird model is used to calculate clear sky direct normal (DNI). This is then adjusted as a function of the ratio of clear sky global horizontal (GHI) and the model predicted GHI. Where possible, existing ground measurement stations are used to validate the data. Nevertheless, there is uncertainty associated with the meterological input to the model, since some of the input parameters are not avalable at a 10km resolution. As a result, it is believed that the modeled values are accurate to approximately 15% of a true measured value within the grid cell. Due to terrain effects and other microclimate influences, the local cloud cover can vary significantly even within a single grid cell. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.
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Title: Photovoltaic Power (Tilted) Contour Lines, 500-Meter Intervals: United States, 1998-2005
Contributors:- Line data
- 2015
Summary: This line shapefile contains tilted photovoltaic solar power resource levels of watt hours per meter squared (Wh/m2) in the contiguous United States using 500-meter interval contour lines. Tilted photovoltaic panels are those that are angled in order to maximize exposure to direct sunlight. Tilt angles are often equal to the site's latitude but may vary throughout the year. This layer is a part of a collection of GIS data containing renewable and electric energy information for the U.S., including data on transmission lines, power plants and electricity substations. This layer can be used for estimates of solar resource potential. Hart Energy Publishing. (2015). Photovoltaic Power (Tilted) Contour Lines, 500-Meter Intervals: United States, 1998-2005. Hart Energy Publishing. Available at: http://purl.stanford.edu/vx760hv6666 This data provides monthly average and annual average daily total solar resource averaged over surface cells of 0.1 degrees in both latitude and longitude, or about 10 km in size. This data was developed using the State University of New York/Albany satellite radiation model. This model was developed by Dr. Richard Perez and collaborators at the National Renewable Energy Laboratory and other universities for the U.S. Department of Energy. Specific information about this model can be found in Perez, et al. (2002). This model uses hourly radiance images from geostationary weather satellites, daily snow cover data, and monthly averages of atmospheric water vapor, trace gases, and the amount of aerosols in the atmosphere to calculate the hourly total insolation (sun and sky) falling on a horizontal surface. Atmospheric water vapor, trace gases, and aerosols are derived from a variety of sources. A modified Bird model is used to calculate clear sky direct normal (DNI). This is then adjusted as a function of the ratio of clear sky global horizontal (GHI) and the model predicted GHI. Where possible, existing ground measurement stations are used to validate the data. Nevertheless, there is uncertainty associated with the meterological input to the model, since some of the input parameters are not avalable at a 10km resolution. As a result, it is believed that the modeled values are accurate to approximately 15% of a true measured value within the grid cell. Due to terrain effects and other microclimate influences, the local cloud cover can vary significantly even within a single grid cell. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.
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Title: Photovoltaic Power (Horizontal) Contour Lines, 100-Meter Intervals: United States, 1998-2005
Contributors:- Line data
- 2015
Summary: This line shapefile contains horizontal photovoltaic solar power resource levels of watt hours per meter squared (Wh/m2) in the contiguous United States using 100-meter interval contour lines. Horizontal photovoltaic panels are those that are positioned on a flat surface. This layer is a part of a collection of GIS data containing renewable and electric energy information for the U.S., including data on transmission lines, power plants and electricity substations. This layer can be used for estimates of solar resource potential. Hart Energy Publishing. (2015). Photovoltaic Power (Horizontal) Contour Lines, 100-Meter Intervals: United States, 1998-2005. Hart Energy Publishing. Available at: http://purl.stanford.edu/gj625pt1990 This data provides monthly average and annual average daily total solar resource averaged over surface cells of 0.1 degrees in both latitude and longitude, or about 10 km in size. This data was developed using the State University of New York/Albany satellite radiation model. This model was developed by Dr. Richard Perez and collaborators at the National Renewable Energy Laboratory and other universities for the U.S. Department of Energy. Specific information about this model can be found in Perez, et al. (2002). This model uses hourly radiance images from geostationary weather satellites, daily snow cover data, and monthly averages of atmospheric water vapor, trace gases, and the amount of aerosols in the atmosphere to calculate the hourly total insolation (sun and sky) falling on a horizontal surface. Atmospheric water vapor, trace gases, and aerosols are derived from a variety of sources. A modified Bird model is used to calculate clear sky direct normal (DNI). This is then adjusted as a function of the ratio of clear sky global horizontal (GHI) and the model predicted GHI. Where possible, existing ground measurement stations are used to validate the data. Nevertheless, there is uncertainty associated with the meterological input to the model, since some of the input parameters are not avalable at a 10km resolution. As a result, it is believed that the modeled values are accurate to approximately 15% of a true measured value within the grid cell. Due to terrain effects and other microclimate influences, the local cloud cover can vary significantly even within a single grid cell. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.
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Title: Alternative Fuel Filling Stations: United States, Summer 2014
Contributors:- Point data
- 2014
Summary: This point dataset shows the locations of alternative fuel filling stations in the United States. This layer is part of a collection of GIS data for renewable and electric energy in the U.S. This layer is from the 2014 Summer Quarter update (Update 1016). This shapefile can be used to locate alternative fuel filling stations in the United States. point dataset shows the locations of oil seed processing plants in the United States for 2013. This layer is a part of a collection of GIS data containing renewable and electric energy information for the U.S., including data on transmission lines, power plants and electricity substations. Hart Energy Publishing (2016). Alternative Fuel Filling Stations: United States, Summer 2014. Hart Energy Publishing. Available at: http://purl.stanford.edu/js268xr6074. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.
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Title: Alternative Fuel Filling Stations: United States, Spring 2013
Contributors:- Point data
- 2013
Summary: This point dataset shows the locations of alternative fuel filling stations in the United States. This layer is part of a collection of GIS data for renewable and electric energy in the U.S. This layer is from the 2013 Spring Quarter update (Update 1011). This shapefile can be used to locate alternative fuel filling stations in the United States. point dataset shows the locations of oil seed processing plants in the United States for 2013. This layer is a part of a collection of GIS data containing renewable and electric energy information for the U.S., including data on transmission lines, power plants and electricity substations. Hart Energy Publishing (2013). Alternative Fuel Filling Stations: United States, Spring 2013. Hart Energy Publishing. Available at: http://purl.stanford.edu/km958vb4793. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.
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Title: United States Alternative Fuels Stations, 2013
Contributors:- Point data
- 2013
Summary: United States Alternative Fuels Stations, 2013 is a point theme representing alternative fuels stations. Through a nationwide network of local coalitions, Clean Citiesprovides project assistance to help stakeholders in the public and private sectors deploy alternative and renewable fuels, idle-reduction measures, fuel economy improvements, and emerging transportation technologies.Department of Energy collects this data as part of the Projects undertaken by Clean Cities coalitions and stakeholders to ensure customers access to clean alternative energy. This data can be found at the Department of Energy Alternative Fuels Data Center Web Feature Service: http://www.afdc.energy.gov/locator/stations/Clean Cities is the deployment arm of the U.S. Department of Energy's (DOE) Vehicle Technologies Office.
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Title: Offfshore Wind Speed 90-Meters, Atlantic Coast, United States, 2011
Contributors:- Raster data
- 2011
Summary: This raster data layer contains the annual average offshore wind speed for the Atlantic Coast (Connecticut, Delaware, Georgia, Massachusetts, Maine, Maryland, New Hampshire, New Jersey, New York, North Carolina, Rhode Island, South Carolina, and Virginia) at a 90 meter height.These data provide information on the wind resource development potential for the Atlantic Coast.
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Title: United States Alternative Fueling Facilities, 2008
Contributors:- Point data
- 2008
Summary: United States Alternative Fueling Facilities is a point theme representing fueling facilities that offer fuels other than gasoline in the United States.
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Title: USA (Alternative Fuels, 2008)
Contributors:- Point data
- 2008
Summary: The Alternative Fuels database is a geographic point database of fueling facilities that offer fuels other than gasoline in the United States.
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Title: USA (Alternative Fuel Stations, 2006)
Contributors:- Point data
- 2006
Summary: Biodiesel, CNG, electric, 85% ethanol, hydrogen, LNG, LPG/Propane stations in the United States.
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Title: Coal Mines, Surface and Underground, United States, 2012
Contributors:- Point data
- 2015
Summary: This point shapefile represents operating surface and underground coal mines in the United States as of 2012 These data originate from the U.S. Energy Information Administration, Form EIA-7A "Coal Production and Preparation Report" and the U.S. Department of Labor, Mine Safety and Health Administration Form 7000-2, "Quarterly Mine Employment and Coal Production Report." This layer is part of a collection of GIS data produced by the U.S. National Energy Information Administration. This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data. National Energy Information Center (U.S.). (2015). Coal Mines, Surface and Underground, United States, 2012. National Energy Information Center. Available at: http://purl.stanford.edu/mn565xr9255. For additional mine data see "Historical Detailed Coal Production Data": http://www.eia.gov/coal/data.cfm#production The U.S. Energy Information Administration shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time. The U.S. Energy Information Administration gives no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.
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Title: Liquefied Natural Gas Import/Export Terminals, United States, 2012
Contributors:- Point data
- 2015
Summary: This point shapefile represents liquefied natural gas import/export terminals in the United States. The data exclude the import facility in Puerto Rico. These data were gahtered from the U.S. Energy Information Administration and the Federal Energy Regulatory Commission and were last updated in September 2012. Terminals capable of liquefaction of natural gas for transport (Kenai, AK), or receipt and regasification of LNG for use as natural gas (GA - Elba Island; LA - Cameron, Lake Charles, Gulf Gateway Deepwater Port, and Sabine Pass; MA - Everett, Neptune, and Northeast Gateway Energy Bridge; MD - Cove Point; PR - Peñuelas; TX - Freeport and Golden Pass). This layer is part of a collection of GIS data produced by the U.S. National Energy Information Administration. This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data. National Energy Information Center (U.S.). (2015). Liquefied Natural Gas Import/Export Terminals, United States, 2012. National Energy Information Center. Available at: http://purl.stanford.edu/rm745tc7680. The U.S. Energy Information Administration shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time. The U.S. Energy Information Administration gives no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.
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Title: Petroleum Refineries, United States, 2014
Contributors:- Point data
- 2015
Summary: This point shapefile represents all operating petroleum refineries located in the United States, Puerto Rico, Guam, the U.S. Virgin Islands, and other U.S. Territories as of January 1, 2014. These data originate from the U.S. Energy Information Administration, Refinery Capacity Report, (EIA-820) Table 3, Capacity of Operable Petroleum Refineries by State. In addition to the sources listed, accuracy for the locations of facilities shown on the map was improved through the use of publicly available sites such as company websites and satellite images from public websites. This layer is part of a collection of GIS data produced by the U.S. National Energy Information Administration. This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data. National Energy Information Center (U.S.). (2015). Petroleum Refineries, United States, 2014. National Energy Information Center. Available at: http://purl.stanford.edu/sn471sh5118. EIA-820 report: http://www.eia.gov/petroleum/refinerycapacity/table3.pdf. The U.S. Energy Information Administration shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time. The U.S. Energy Information Administration gives no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.
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Title: Petroleum Product Terminals, United States, 2014
Contributors:- Point data
- 2015
Summary: This point shapefile represents all operable bulk petroleum product terminals located in the 50 States and the District of Columbia with a total bulk shell storage capacity of 50,000 barrels or more, and/or ability to receive volumes from tanker, barge, or pipeline. Survey locations were adjusted using public data. These data were gathered from "EIA-815, Monthly Bulk Terminal and Blender Report." These data are current as of November 2014. This layer is part of a collection of GIS data produced by the U.S. National Energy Information Administration. This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data. National Energy Information Center (U.S.). (2015). Petroleum Product Terminals, United States, 2014. National Energy Information Center. Available at: http://purl.stanford.edu/kx379sb6876. The U.S. Energy Information Administration shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time. The U.S. Energy Information Administration gives no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.
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Title: Natural Gas Processing Plants, United States, 2012-2013
Contributors:- Point data
- 2015
Summary: This point shapefile represents natural gas processing plants in the United States in 2012 with select updates through 2013. Zip code centroids are used for map location. These data were gathered from the EIA-757, Natural Gas Processing Plant Survey. This layer is part of a collection of GIS data produced by the U.S. National Energy Information Administration. This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data. National Energy Information Center (U.S.). (2015). Natural Gas Processing Plants, United States, 2012-2013. National Energy Information Center. Available at: http://purl.stanford.edu/md188gh4020. The U.S. Energy Information Administration shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time. The U.S. Energy Information Administration gives no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.
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Title: Natural Gas Interstate and Intrastate Pipelines, United States, 2014
Contributors:- Line data
- 2014
Summary: This line shapefile represents the major natural gas transmission pipelines in the U.S. including interstate, intrastate, and gathering pipelines as of November 2014. These data were obtained by the U.S. Energy Information Administration from various sources including FERC Form 567—Annual Report Of System Flow Diagrams and Capacity, and other external sources such as company web pages and industry press. This layer is part of a collection of GIS data produced by the U.S. National Energy Information Administration. This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data. National Energy Information Center (U.S.). (2014). Natural Gas Interstate and Intrastate Pipelines, United States, 2014. National Energy Information Center. Available at: http://purl.stanford.edu/nb980gq7004. The U.S. Energy Information Administration shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time. The U.S. Energy Information Administration gives no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.
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Title: Hydrocarbon Gas Liquid Pipelines, United States, 2014
Contributors:- Line data
- 2014
Summary: This line shapefile represents major hydrocarbon gas liquid (HGL) pipelines in the United States as of November 2014. HGL refers to both the natural gas liquids (paraffins or alkanes) and olefins (alkenes) produced by natural gas processing plants, fractionators, crude oil refineries, and condensate splitters but excludes liquefied natural gas (LNG) and aromatics. HGL is both fuel and feedstock in various markets (petrochemicals, residential heating/cooking, agriculture, and motor fuel blending). Seasonal and regional fluctuations in these end-use sectors, including export markets, affect investment and production decisions throughout the upstream, midstream, and downstream sectors of the oil and gas industry. Billions of dollars have been invested recently in the field gathering systems, lease separators, crude/condensate stabilizers, natural gas processing plants, fractionation facilities, refineries, condensate splitters, pipelines, storage caverns, rail terminals, port facilities, ethylene crackers, and other petrochemical plants that constitute HGL infrastructure. This layer includes interstate trunk lines and selected intrastate lines and are based on publicly available data from a variety of sources with varying scales and levels of accuracy. This layer is part of a collection of GIS data produced by the U.S. National Energy Information Administration. This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data. National Energy Information Center (U.S.). (2014). Hydrocarbon Gas Liquid Pipelines, United States, 2014. National Energy Information Center. Available at: http://purl.stanford.edu/tr705zj4339. The U.S. Energy Information Administration shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time. The U.S. Energy Information Administration gives no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.
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Title: Natural Gas Underground Storage Facilities, United States, 2014
Contributors:- Point data
- 2014
Summary: This point shapefile represents underground natural gas storage fields in the United States as of July 2014. County centroids are used for map location. These data were gathered from EIA-191, Monthly Underground Gas Storage Report. This layer is part of a collection of GIS data produced by the U.S. National Energy Information Administration. This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data. National Energy Information Center (U.S.). (2014). Natural Gas Underground Storage Facilities, United States, 2014. National Energy Information Center. Available at: http://purl.stanford.edu/tb598wt7743. CREDIT The U.S. Energy Information Administration shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time. The U.S. Energy Information Administration gives no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.