10,000+ results returned
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Title: BOEM Wind Planning Areas, Atlantic Region, 2013
Contributors:- Polygon data
- 2013
Summary: This polygon shapefile represents the most recent changes for the Bureau of Ocean Energy Management (BOEM) Wind Development Planning Areas in the Atlantic. Wind Planning Areas in this layer represent up to six different types of announcements within the US Federal Register that can be used to show the current status of an area that is being considered for Wind Power Development. The Smart from the Start Wind Energy Areas (WEAs) are represented in a separate layer. Not all areas will start out as WEAs. Since the WEAs were the first announcement for some of these areas, we have decided to repost the WEA layer to show its original areas prior to any reshaping by BOEM after the original announcement since the reshaped areas are really not the WEAs but one of the other six types of areas represented here. For those areas that started out as WEAs, the user may see the changes that have taken place over time. For the areas represented here, once an area has changed from one type of area to another, it will be replaced entirely by the new area. The types of areas and their descriptions can be found in the attributes section of the metadata record. To let those that are interested in Wind Energy Planning and Development know of the most recent updates to areas of interest for Wind Energy Development off the United States Coast within Federal Waters. U.S. Bureau of Ocean Energy Management. Office of Renewable Energy Programs. (2013). BOEM Wind Planning Areas, Atlantic Region, 2013. BOEM. Available at: http://purl.stanford.edu/yj142kb3734. Not for navigational use. Not to be used for leasing purposes. For visual purposes only. 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 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: 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: Oil and Gas Wells in the United States, February 2020
Contributors:- Mixed
- 2020
Summary: This geodatabase contains a point feature class layer of oil and gas wells in the United States. This layer is from February 2020. The purpose of this file is to combine multiple oil and gas well data sources into one national file. This dataset is intended to assist users in locating and analyzing United States oil and gas field data 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. Hart Energy Publishing. (2020). Oil and Gas Wells in the United States, February 2020. Hart Energy Publishing. Available at: http://purl.stanford.edu/pq479rm6462.
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Title: Oil and Gas Wells in the United States, January 2020
Contributors:- Mixed
- 2020
Summary: This geodatabase contains a point feature class layer of oil and gas wells in the United States. This layer is from January 2020. The purpose of this file is to combine multiple oil and gas well data sources into one national file. This dataset is intended to assist users in locating and analyzing United States oil and gas field data 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. Hart Energy Publishing. (2020). Oil and Gas Wells in the United States, January 2020. Hart Energy Publishing. Available at: http://purl.stanford.edu/zn948fy2680.
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Title: Oil and Gas Wells in the United States, March 2019
Contributors:- Mixed
- 2019
Summary: This geodatabase contains a point feature class layer of oil and gas wells in the United States. This layer is from March 2019. The purpose of this file is to combine multiple oil and gas well data sources into one national file. This dataset is intended to assist users in locating and analyzing United States oil and gas field data 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. Hart Energy Publishing. (2019). Oil and Gas Wells in the United States, March 2019. Hart Energy Publishing. Available at: http://purl.stanford.edu/tt689ns3047.
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Title: Electricity Dataset, United States, May 2019
Contributors:- Mixed
- 2019
Summary: This geodatabase contains data on electricity and power in the United States. This geodatabase contains 4 feature classes: Electric Service Territories (polygon), Electric Substations (point), Electric Transmission Lines (Line), and Power Plants (point). This database is current as of May 2019. The purpose of this file is to combine multiple oil and gas well data sources into one national file. This dataset is intended to assist users in locating and analyzing United States oil and gas field data 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. Hart Energy Publishing. (2019). Electricity Dataset, United States, May 2019. Hart Energy Publishing. Available at: http://purl.stanford.edu/kn722tx1063.
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Title: Oil and Gas Wells in the United States, November 2019
Contributors:- Mixed
- 2019
Summary: This geodatabase contains a point feature class layer of oil and gas wells in the United States. This layer is from November 2019. The purpose of this file is to combine multiple oil and gas well data sources into one national file. This dataset is intended to assist users in locating and analyzing United States oil and gas field data 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. Hart Energy Publishing. (2019). Oil and Gas Wells in the United States, November 2019. Hart Energy Publishing. Available at: http://purl.stanford.edu/rv035nj5561.
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Title: Oil and Gas Wells in the United States, May 2019
Contributors:- Mixed
- 2019
Summary: This geodatabase contains a point feature class layer of oil and gas wells in the United States. This layer is from May 2019. The purpose of this file is to combine multiple oil and gas well data sources into one national file. This dataset is intended to assist users in locating and analyzing United States oil and gas field data 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. Hart Energy Publishing. (2019). Oil and Gas Wells in the United States, May 2019. Hart Energy Publishing. Available at: http://purl.stanford.edu/jr112wt8361.
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Title: Electricity Dataset, United States, November 2019
Contributors:- Mixed
- 2019
Summary: This geodatabase contains data on electricity and power in the United States. This geodatabase contains 4 feature classes: Electric Service Territories (polygon), Electric Substations (point), Electric Transmission Lines (Line), and Power Plants (point) layer of oil and gas wells in the United States. This database is current as of November 2019. The purpose of this file is to combine multiple oil and gas well data sources into one national file. This dataset is intended to assist users in locating and analyzing United States oil and gas field data 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. Hart Energy Publishing. (2020). Electricity Dataset, United States, November 2019. Hart Energy Publishing. Available at: http://purl.stanford.edu/xv258hm5571.