National Renewable Energy Laboratory

GeoServer Web Map Service

workinglayers:RANKING_masked_rc workinglayers:RANKING_masked_rc data_res:90mwindspeed_hi
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Web Service, OGC Web Map Service 1.3.0
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WFS, WMS, GEOSERVER
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Anthony Lopez

National Renewable Energy Laboratory

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80401 Golden,, USA

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No INSPIRE Extended Capabilities (including service metadata) given. See INSPIRE Technical Guidance - View Services for more information.

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A compliant implementation of WMS plus most of the SLD extension (dynamic styling). Can also generate PDF, SVG, KML, GeoRSS

Available map layers (746)

NREL Hawaii 90m Offshore Wind Resource (data_res:90mwindspeed_hi)

Abstract: Annual average offshore wind speed for Hawaii at a 90 meter height. Supplemental Information: The annual offshore wind speed estimates were produced by AWS Truepower for an onshore wind mapping project using their MesoMap system and historical weather data. The wind speeds data have been interpolated to a 90-m height and extrapolated to 50 nautical miles by NREL. The raster dataset had a spatial 200 m resolution with a projection of UTM zone 4, datum WGS 84. The shapefile was generated from the raster dataset and then projected to Geographic Decimal Degrees, datum WGS 84. Source: AWS Truepower/NREL

Jordan Ranking Masked (workinglayers:RANKING_masked_rc)

Africa Transmission Lines Existing Polylines AICD (irena:africa_txline_existing08)

Africa Infrastructure Country Diagnostic (AICD) - http://www.infrastructureafrica.org/ The database is hosted by the African Development Bank. Data Sources Angola: IBRD map archive #23770, Apr 1992, & internet Benin: IBRD map archive #33246, #33245, Jun 2004. WAPP Member Utilities Performance report, 2005 Botswana: BPA 2006 Annual Report Burkina Faso: WB map archives IBRD #33253, Aug 2004. SONABEL website Burundi: "Reseau Electrique National", REGIDESO, undated hardcopy map Cameroon: "Reseau de Transport en Haute Tension Existant", AES SONEL c 2000 hardcopy map Cape Verde: IBRD map archive #30064, Mar 1999 Central African Republic: IBRD map archive #23036, Jun 1992 Chad: Data not available Comoros: Data not available Democratic Republic of Congo: IBRD map archive #35198, Apr 2007 Republic of Congo: IBRD map archive #28107, Jul 1996 Cote d'Ivoire: SOPIE website Djibouti: Data not available Equatorial Guinea: IBRD map archive #22885, Feb 1991. "OMVG Power System Development" WAPP undated hardcopy map Eritrea: Data not available Ethiopia: IBRD map archive #34623, April 2006 (hardcopy) Gabon: SEEG_Presentation_du_Situation_Energetique_du_Gabon.ppt Gambia, The: IBRD map archive #35062, Feb 2008; "OMVG Power System Development" WAPP undated hardcopy map Ghana: Solar and Wind Energy Resource Assessment (SWERA) Geospatial Toolkit (GsT) Guinea: IBRD map archive #34833, Jun 2006. WAPP Member Utilities Performance report, 2005 Guinea-Bissau: IBRD map archive #22885, Feb 1991 Kenya: IBRD map archive #33090, May 2004; SNC Lavalin Lesotho: "Lesotho Access to Electricity Study" UNDP/GEF Sep 2006 Liberia: IBRD map archive #35002, Feb 2008 Madagascar: IBRD map archive #34815, Jun 2006 Malawi: ESCOM Power System, undated hardcopy map Mali: IBRD map archive #36890, May 2009 Mauritania: OMVS undated hardcopy map Mauritius: Data not available Mayotte: Data not available Mozambique: IBRD map archive #32473, May 2003 Namibia: GISPrimaryConductorPath.shp downloaded from NamPower website, Sep 2009 Niger: IBRD map archive #35062; Feb 2008. Strategie d'Electrification Rurale, IED/CEH-SIDI Aug 2004 Nigeria: IBRD map archive #35062, Feb 2008 Reunion: Data not available Rwanda: IBRD map archive #33686, Nov 2004 Saint Helena: Data not available Sao Tome and Principe: Data not available Senegal: IBRD map archive #34462, Jan 2006 Seychelles: Data not available Sierra Leone: IBRD map archive #22273, Mar 1991. Bumbuna Hydroelectric Project Assessment EIA, 2005 Somalia: Data not available South Africa: Tx_Lines.shp provided by ESKOM, 2006 Sudan: IBRD map archive #32740, Jan 2004 Swaziland: IBRD map archive #19803, Jul 1986. "SEB Transmission System" with Motraco project, undated hardcopy map Tanzania: IBRD map archive #32473, May 2003 Togo: IBRD map archive #33246, #33245, Jun 2004. WAPP Member Utilities Performance report, 2005 Uganda: UGANDA-AERDP Final Report Annex 1, Feb 2004 Zambia: IBRD map archive #29233, Dec 1997 Zimbabwe: lines generated from map in ZESA Presentation on POWER GENERATION OPTIONS, SAPP website

NREL Alaska 50m Wind Resource (data_res:alaska_50mwind)

Abstract: Annual average wind resource potential for the main section of the state of Alaska. Supplemental Information: Provide information on the wind resource development potential within the state of Alaska. Source:

all_wells_five_million (gt_prospector:all_wells_five_million)

all_wells_million (gt_prospector:all_wells_million)

Test Data - More than a Million (gt_prospector:all_wells_temp)

all_wells_ten_million (gt_prospector:all_wells_ten_million)

NREL Arkansas 50m Wind Resource (data_res:ar_50mwind)

Abstract: Annual average wind resource potential for the state of Arkansas at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 15N, datum WGS 84 projection system. Source: AWS TrueWind/NREL

NREL Arizona 50m Wind Resource (data_res:arizona_50mwind)

Abstract: Annual average wind resource potential for the state of Arizona at a 50 meter height. This dataset will be replaced when the southwest region has been completed, and the data may change when this region has been completed. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. Source: AWS TrueWind/NREL

NREL Atlantic Coast 90m Offshore Wind Resource (data_res:atlantic_coast_90mwindspeed_off)

Abstract: 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. Source: AWS Truepower/NREL

authorized2010geoparcels (gt_prospector:authorized2010geoparcels)

This data set is designed to display the location of all authorized geothermal parcels, including those in the March 2010 lease sale, in the state of Nevada. Polygons have been labeled by Lease Number.

bedgeol_2010 (gt_prospector:bedgeol_2010)

WSGS updated Geologic Unit geometry and edited attributes for spelling and/or description errors February 2010. The geologic map was digitized from original scribe sheets used to prepare the published Geologic Map of Wyoming (Love and Christiansen, 1985), consequently at a 1:500,000 scale. Stable base contact prints of the scribe sheets were scannned on a Tektronix 4991 digital scanner. The scanner automatically converts the scanned image to an ASCII vector format. These vectors were transferred to a VAX minicomputer, where they were loaded into Arc/Info. The dataset includes both linear and polygon features, with attributes derived from the original 1985 map. ArialSG font used for labeling Special Characters using G_Sym field.

RE_Atlas Biomass Residue (re_atlas:biomass)

Biopower potential estimated based on available residue data produced in the report Geographic Perspective on the Current Biomass Resource Availability in the United States (NREL, 2004), assuming conversion efficiencies between 30 and 35% depending on the residue type.

BTU - County: Annual Energy Crops (biomass:btu_county_annual_energy_crops)

Units: Dry Tons, Metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - County: Barley Straw (biomass:btu_county_barley_straw)

Units: Dry Tons, Metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - County: Composite Operations No Federal Lands (biomass:btu_county_composite_no_feds)

Units: Dry Tons, Metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - County: Composite Operations With Federal Lands (biomass:btu_county_composite_with_feds)

Units: Dry Tons, Metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - County: Conventional Woods (biomass:btu_county_conventional_wood)

Units: Dry Tons, Metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - County: Coppice & Non-Coppice Woody Crops (biomass:btu_county_coppice_and_non-coppice_woody)

Units: Dry Tons, Metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - County: Corn Stover (biomass:btu_county_corn_stover)

Units: Dry Tons, Metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - County: Forestland Thinnings No Federal Lands (biomass:btu_county_forestland_thinnings_no_fed)

Units: Dry Tons, Metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - County: Forestland Thinnings With Federal Lands (biomass:btu_county_forestland_thinnings_with_fed)

Units: Dry Tons, Metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - County: Mill Residue Unused Primary (biomass:btu_county_mill_residue_unused_primary)

Units: Dry Tons, Metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - County: Oat Straw (biomass:btu_county_oat_straw)

Units: Dry Tons, Metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - County: Other Residue (biomass:btu_county_other_residue)

Units: Dry Tons, Metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - County: Perennial Grasses (biomass:btu_county_perennial_grasses)

Units: Dry Tons, Metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - County: Sorghum Stubble (biomass:btu_county_sorghum_stubble)

Units: Dry Tons, Metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - County: Urban CD Wood (biomass:btu_county_urban_c_and_d_wood)

{units:'Dry Tons', metadata:'BT2 Energy Crops 2022 $60/dry tonThese data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website:http://www1.eere.energy.gov/biomass/billion_ton_update.html'}

BTU - County: Urban MSW Wood (biomass:btu_county_urban_msw_wood)

Units: Dry Tons, Metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - County: Wheat Straw (biomass:btu_county_wheat_straw)

Units: Dry Tons, Metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

Crop Residues: Bagasse (biomass:btu_cropresidues_bagasse_by_county)

Units: Tonnes/yr, Metadata: Available crop residues are estimated using total crop production, crop to residue ratio, moisture content, and the amount of residue left on the field for soil protection, grazing and other agricultural activities. Source: USDA, National Agricultural Statistics Service; 5 year average: 2004-2008 data. For more information on data development, please refer to (http://www.nrel.gov/docs/fy06osti/39181.pdf). Although the document contains the methodology for the development of an older assessment, the information is applicable to this assessment as well. The difference is only in the data’s time period.

Crop Residues: Barley Straw (biomass:btu_cropresidues_barley_straw_by_county)

Units: Tonnes/yr, Metadata: Available crop residues are estimated using total crop production, crop to residue ratio, moisture content, and the amount of residue left on the field for soil protection, grazing and other agricultural activities. Source: USDA, National Agricultural Statistics Service; 5 year average: 2004-2008 data. For more information on data development, please refer to (http://www.nrel.gov/docs/fy06osti/39181.pdf). Although the document contains the methodology for the development of an older assessment, the information is applicable to this assessment as well. The difference is only in the data’s time period.

Crop Residues: Corn Cobs (biomass:btu_cropresidues_corn_cobs_by_county)

Units: Tonnes/yr, Metadata: Available crop residues are estimated using total crop production, crop to residue ratio, moisture content, and the amount of residue left on the field for soil protection, grazing and other agricultural activities. Source: USDA, National Agricultural Statistics Service; 5 year average: 2004-2008 data. For more information on data development, please refer to (http://www.nrel.gov/docs/fy06osti/39181.pdf). Although the document contains the methodology for the development of an older assessment, the information is applicable to this assessment as well. The difference is only in the data’s time period.

Crop Residues: Corn Stover (biomass:btu_cropresidues_corn_stover_by_county)

Units: Tonnes/yr, Metadata: Available crop residues are estimated using total crop production, crop to residue ratio, moisture content, and the amount of residue left on the field for soil protection, grazing and other agricultural activities. Source: USDA, National Agricultural Statistics Service; 5 year average: 2004-2008 data. For more information on data development, please refer to (http://www.nrel.gov/docs/fy06osti/39181.pdf). Although the document contains the methodology for the development of an older assessment, the information is applicable to this assessment as well. The difference is only in the data’s time period.

Crop Residues: Rice Straw (biomass:btu_cropresidues_rice_straw_by_county)

Units: Tonnes/yr, Metadata: Available crop residues are estimated using total crop production, crop to residue ratio, moisture content, and the amount of residue left on the field for soil protection, grazing and other agricultural activities. Source: USDA, National Agricultural Statistics Service; 5 year average: 2004-2008 data. For more information on data development, please refer to (http://www.nrel.gov/docs/fy06osti/39181.pdf). Although the document contains the methodology for the development of an older assessment, the information is applicable to this assessment as well. The difference is only in the data’s time period.

Crop Residues: Wheat Straw (biomass:btu_cropresidues_wheat_straw_by_county)

Units: Tonnes/yr, Metadata: Available crop residues are estimated using total crop production, crop to residue ratio, moisture content, and the amount of residue left on the field for soil protection, grazing and other agricultural activities. Source: USDA, National Agricultural Statistics Service; 5 year average: 2004-2008 data. For more information on data development, please refer to (http://www.nrel.gov/docs/fy06osti/39181.pdf). Although the document contains the methodology for the development of an older assessment, the information is applicable to this assessment as well. The difference is only in the data’s time period.

Crops: Sugarbeets (biomass:btu_crops_sugarbeets_by_county)

Units: tonnes/yr, Source: USDA, National Agricultural Statistics Service; 5 year average: 2004-2008 data. For more information, visit: USDA National Agricultural Statistics Service (http://www.nass.usda.gov)

Crops: Sugarcane (biomass:btu_crops_sugarcane_by_county)

Units: tonnes/yr, Source: USDA, National Agricultural Statistics Service; 5 year average: 2004-2008 data. For more information, visit: USDA National Agricultural Statistics Service (http://www.nass.usda.gov)

Methane: Landfills (biomass:btu_methane_landfill)

units:waste_in_place_tons, metadata:The wastewater energy output is estimated for each landfill considering total waste in place, landfill size, and location (arid or non-arid climate). Note: this dataset doesn't include all landfill_output in the United States due to gaps in either precise geographic location or waste in place. Source: EPA, Landfill Methane Outreach Program (LMOP), April 2008. For more information on the data development, please refer to: (http://www.nrel.gov/docs/fy06osti/39181.pdf). Although, the document contains the methodology for the development of an older assessment, the information is applicable to this assessment as well. The difference is only in the data's time period.

Methane: Manure Management (biomass:btu_methane_methane_emissions)

{units:'tonnes\/yr',metadata:'The following animal types were included in this analysis: diary cows, beef cows, hogs and pigs, sheep, chickens and layers, broilers, and turkey. The methane emissions were calculated by animal type and manure management system at a county level.Source: USDA, National Agricultural Statistics Service, 2002 data. For more information on the data development, please refer to http:\/\/www.nrel.gov\/docs\/fy06osti\/39181.pdf.'}

Methane: Wastewater (biomass:btu_methane_wastewater)

{units:kw, metadata:The wastewater energy output is estimated for each landfill considering total waste in place, landfill size, and location (arid or non-arid climate). Note: this dataset doesn't include all wastewater_output in the United States due to gaps in either precise geographic location or waste in place. Source: EPA, Landfill Methane Outreach Program (LMOP), April 2008. For more information on the data development, please refer to: (http://www.nrel.gov/docs/fy06osti/39181.pdf). Although, the document contains the methodology for the development of an older assessment, the information is applicable to this assessment as well. The difference is only in the data's time period.

BTU - State: Cotton Gin Trash (biomass:btu_state_cotton_gin_trash)

Units: Dry Tons, metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - State: Cotton Residue (biomass:btu_state_cotton_residue)

Units: Dry Tons, metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - State: Manure Management (biomass:btu_state_manure_management)

Units: Dry Tons, metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - State: Orchard & Vineyard Pruning (biomass:btu_state_orchard_vineyard_pruning)

Units: Dry Tons, metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - State: Rice Hulls (biomass:btu_state_rice_hulls)

Units: Dry Tons, metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - State: Rice Straw (biomass:btu_state_rice_straw)

Units: Dry Tons, metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - State: Sugarcane Trash (biomass:btu_state_sugarcane_trash)

Units: Dry Tons, metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

BTU - State: Wheat Dust (biomass:btu_state_wheat_dust)

Units: Dry Tons, metadata: BT2 Energy Crops 2022 $60/dry ton. These data are derived from the Billion Ton Update produced by Oak Ridge National Laboratory for the Department of Energy Office of Biomass Program. More information about the Billion Ton Update can be found at the Office of Biomass Program website: (http://www1.eere.energy.gov/biomass/billion_ton_update.html)

Wood: Forest Residues (biomass:btu_wood_forest_residues)

Source: USDA USFS 2007 data. A. Milbrandt, A Geographic Perspective on the Current Biomass Resource Availability in the United States NREL TP-560-39181. http://www.nrel.gov/docs/fy06osti/39181.pdf

Wood: Primary Mill Residues (biomass:btu_wood_primary_mill_residues)

Source: USDA USFS 2007 data. A. Milbrandt, A Geographic Perspective on the Current Biomass Resource Availability in the United States NREL TP-560-39181. http://www.nrel.gov/docs/fy06osti/39181.pdf

Wood: Urban Wood & Secondary Mill Residues (biomass:btu_wood_urbanwood)

Units:thou. tonnes/yr, metadata: Urban wood waste includes wood residues from MSW (wood chips and pallets), utility tree trimming and/or private tree companies, and construction and demolition sites. Source: U.S. Census Bureau, 2000 Population data, BioCycle Journal, State of Garbage in America, January 2004\; County Business Patterns 2002. Secondary mill residues include wood scraps and sawdust from woodworking shops - furniture factories, wood container and pallet mills, and wholesale lumberyards. Data on the number of businesses by county was gathered from the U.S. Census Bureau, 2002 County Business Patterns. For more information on the data development, please refer to: http://www.nrel.gov/docs/fy06osti/39181.pdf.

NREL California 50m Wind Resource (data_res:ca_50mwind)

Abstract: Annual average wind resource potential of California at a 50 meter height. Supplemental Information: This data set was produced by TrueWind Solutions using their Mesomap system and historical weather data, under funding from the California Energy Commission. It has been validated by NREL and wind energy meteorological consultants. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 11, datum WGS 84 projection system.

cageol_poly_dd (gt_prospector:cageol_poly_dd)

These digital maps are a reformulation of previously published maps, primarily maps of states. The reformulation gives all the maps the same structure and format, allowing them to be combined into regional maps. The associated data tables have information about age and lithology of the map units, also in a standard format.

Cooling Degree Days Polygon Global 1 Degree NASA 2007 (swera:clim_cdd10_nasa_low)

Cooling Degree Days above 10° C (degree days)The monthly accumulation of degrees when the daily mean temperature is above 10° C.NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Nov 2007)22-year Monthly Average & Annual Sum (July 1983 - June 2005) Parameter: Cooling Degree Days Above 10 degrees C (degree days)Internet: http://eosweb.larc.nasa.gov/sse/Note 1: SSE Methodology & Accuracy sections onlineNote 2: Lat/Lon values indicate the lower left corner of a 1x1 degree region. Negative values are south and west; positive values are north and east. Boundaries of the -90/-180 region are -90 to -89 (south) and -180 to -179 (west). The last region, 89/180, is bounded by 89 to 90 (north) and 179 to 180 (east). The mid-point of the region is +0.5 added to the the Lat/Lon value. These data are regional averages; not point data. These data are regional averages; not point data.Created: December 10, 2007See the NASA Surface meteorology and Solar Energy (SSE) web site at http://eosweb.larc.nasa.gov/sse/. The source data was downloaded from the SSE website at Data Retrieval: Meteorology and Solar Energy > Global data sets as text files. The tabular data was then converted to the shapefile format. Source: U.S. National Aeronautics and Space Administration (NASA), Surface meteorology and Solar Energy (SSE)

Heating Degree Days Polygon Global 1 Degree NASA 2007 (swera:clim_hdd18_nasa_low)

Heating Degree Days below 18° C (degree days)The monthly accumulation of degrees when the daily mean temperature is below 18° C.NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Nov 2007)22-year Monthly Average & Annual Sum (July 1983 - June 2005)Parameter: Heating Degree Days Below 18 degrees C (degree days)Internet: http://eosweb.larc.nasa.gov/sse/Note 1: SSE Methodology & Accuracy sections onlineNote 2: Lat/Lon values indicate the lower left corner of a 1x1 degree region. Negative values are south and west; positive values are north and east. Boundaries of the -90/-180 region are -90 to -89 (south) and -180 to -179 (west). The last region, 89/180, is bounded by 89 to 90 (north) and 179 to 180 (east). The mid-point of the region is +0.5 added to the the Lat/Lon value. These data are regional averages; not point data.Created: December 10, 2007See the NASA Surface meteorology and Solar Energy (SSE) web site at http://eosweb.larc.nasa.gov/sse/. The source data was downloaded from the SSE website at Data Retrieval: Meteorology and Solar Energy > Global data sets as text files. The tabular data was then converted to the shapefile format. Source: U.S. National Aeronautics and Space Administration (NASA), Surface meteorology and Solar Energy (SSE)

Atmospheric Pressure Polygon Global 1 Degree NASA 2007 (swera:clim_ps_nasa_low)

Atmospheric Pressure (kPa)NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Nov 2007)22-year Monthly & Annual Average (July 1983 - June 2005)Parameter: Atmospheric Pressure (kPa)Internet: http://eosweb.larc.nasa.gov/sse/Note 1: SSE Methodology & Accuracy sections onlineNote 2: Lat/Lon values indicate the lower left corner of a 1x1 degree region. Negative values are south and west; positive values are north and east. Boundaries of the -90/-180 region are -90 to -89 (south) and -180 to -179 (west). The last region, 89/180, is bounded by 89 to 90 (north) and 179 to 180 (east). The mid-point of the region is +0.5 added to the the Lat/Lon value. These data are regional averages; not point data.Created: May 13, 2008See the NASA Surface meteorology and Solar Energy (SSE) web site at http://eosweb.larc.nasa.gov/sse/. The source data was downloaded from the SSE website at the Data Retrieval: Meteorology and Solar Energy > Global data sets as text files. The tabular data was then converted to the shapefile format. Units:kilopascal (kPa). Source: U.S. National Aeronautics and Space Administration (NASA), Surface meteorology and Solar Energy (SSE)

Relative Humidity Polygon Global 1 Degree NASA 2007 (swera:clim_rh10m_nasa_low)

Relative Humidity at 10 m Above The Surface Of The Earth (%)NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Nov 2007)22-year Monthly & Annual Average (July 1983 - June 2005)Parameter: Relative Humidity at 10 m Above The Surface Of The Earth (%)Internet: http://eosweb.larc.nasa.gov/sse/Note 1: SSE Methodology & Accuracy sections onlineNote 2: Lat/Lon values indicate the lower left corner of a 1x1 degree region. Negative values are south and west; positive values are north and east. Boundaries of the -90/-180 region are -90 to -89 (south) and -180 to -179 (west). The last region, 89/180, is bounded by 89 to 90 (north) and 179 to 180 (east). The mid-point of the region is +0.5 added to the the Lat/Lon value. These data are regional averages; not point data.Created: December 10, 2007See the NASA Surface meteorology and Solar Energy (SSE) web site at http://eosweb.larc.nasa.gov/sse/. The source data was downloaded from the SSE website at Data Retrieval: Meteorology and Solar Energy > Global data sets as text files. The tabular data was then converted to the shapefile format. Source: U.S. National Aeronautics and Space Administration (NASA), Surface meteorology and Solar Energy (SSE)

Air Temperature Polygon Global 1 Degree NASA 2007 (swera:clim_temp_nasa_low)

Air Temperature at 10 m Above The Surface Of The Earth (deg C)NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Nov 2007)22-year Monthly & Annual Average (July 1983 - June 2005)Parameter: Air Temperature at 10 m Above The Surface Of The Earth (deg C)Internet: http://eosweb.larc.nasa.gov/sse/Note 1: SSE Methodology & Accuracy sections onlineNote 2: Lat/Lon values indicate the lower left corner of a 1x1 degree region. Negative values are south and west; positive values are north and east. Boundaries of the -90/-180 region are -90 to -89 (south) and -180 to -179 (west). The last region, 89/180, is bounded by 89 to 90 (north) and 179 to 180 (east). The mid-point of the region is +0.5 added to the the Lat/Lon value. These data are regional averages; not point data.Created: November 27, 2007See the NASA Surface meteorology and Solar Energy (SSE) web site at http://eosweb.larc.nasa.gov/sse/. The source data was downloaded from the SSE website at the Data Retrieval: Meteorology and Solar Energy > Global data sets as text files. The tabular data was then converted to the shapefile format. Source: U.S. National Aeronautics and Space Administration (NASA), Surface meteorology and Solar Energy (SSE)

Earth Skin Temperature Polygon Global 1 Degree NASA 2007 (swera:clim_tskin_nasa_low)

Earth Skin Temperature (° C) NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Nov 2007)22-year Monthly & Annual Average (July 1983 - June 2005)Parameter: Earth Skin Temperature (deg C)Internet: http://eosweb.larc.nasa.gov/sse/Note 1: SSE Methodology & Accuracy sections onlineNote 2: Lat/Lon values indicate the lower left corner of a 1x1 degree region. Negative values are south and west; positive values are north and east. Boundaries of the -90/-180 region are -90 to -89 (south) and -180 to -179 (west). The last region, 89/180, is bounded by 89 to 90 (north) and 179 to 180 (east). The mid-point of the region is +0.5 added to the the Lat/Lon value. These data are regional averages; not point data.Created: November 27, 2007See the NASA Surface meteorology and Solar Energy (SSE) web site at http://eosweb.larc.nasa.gov/sse/. The source data was downloaded from the SSE website at Data Retrieval: Meteorology and Solar Energy > Global data sets as text files. The tabular data was then converted to the shapefile format. Source: U.S. National Aeronautics and Space Administration (NASA), Surface meteorology and Solar Energy (SSE)

co_fed_minerals (gt_prospector:co_fed_minerals)

NREL Colorado 50m Wind Resource (data_res:colorado_50mwind)

Abstract: Annual average wind resource potential for the state of Colorado, United States at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. Source: AWS TrueWind/NREL

NREL Connecticut 50m Wind Resource (data_res:connecticut_50mwind)

Abstract: Annual average wind resource potential for the state of Connecticut at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. Source: AWS TrueWind/NREL

CSP Landcover (workinglayers:csp_landcover)

RE_Atlas Concentrated Solar Power (Filtered) (re_atlas:csp_slope_filter)

Solar: 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. The insolation values represent the resource available to concentrating systems that track the sun throughout the day. The data are created using the SUNY Satellite Solar Radiation model (Perez, et.al., 2002). The data are averaged from hourly model output over 12 years (1998-2009). 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. The direct beam radiation is then calculated using the atmospheric water vapor, trace gases, and aerosols, which are derived from a variety of sources. Where possible, existing ground measurement stations are used to validate the data. Annual average direct normal resource data (as described above), filtered to eliminate areas with slope greater than or equal to 5%. Percent slope is calculated using the U.S. Geological Survey National Elevation Dataset at a 1 arc second (nominally 90 m) resolution. Source: Perez-SUNY/NREL, 2012 Link: http://www.nrel.gov/gis

Solar DNI Polygon N.Africa to E.China 10km DLR 2003 (swera:dni_dlr_high)

SRID 4326 of two available coordinate systems. Data of high resolution (10kmx10km) Direct Normal Irradiance (DNI) for the years 2000, 2002 and 2003. The data are available for monthly and annual sums stored in an ESRI-Shapefile. Please read the country report for additional background information. Data included for Bangladesh, China, Ethiopia, Ghana, Kenya, Nepal, Sri Lanka, and United Arab Emirates. Units: KWh/m sq. per day. Source: DLR - Deutsches Zentrum für Luft- und Raumfahrt

Solar DNI Polygon N.Africa to E.China 10km DLR 2003 (swera:dni_dlr_high_900913)

SRID 900913 of two available coordinate systems. Data of high resolution (10kmx10km) Direct Normal Irradiance (DNI) for the years 2000, 2002 and 2003. The data are available for monthly and annual sums stored in a ESRI-Shapefile. Please read the country report for additional background information. Data included for Bangladesh, China, Ethiopia, Ghana, Kenya, Nepal, Sri Lanka, and United Arab Emirates. Units: KWh/m sq. per day. Source: DLR - Deutsches Zentrum für Luft- und Raumfahrt

Solar DNI Polygon Turkey 10km GeoModel 2010 (swera:dni_geomodel_high)

SRID 4326 of two available coordinate systems. Developed by NREL and the U.S. Trade and Development Agency, this geographic toolkit that allows users to relate the renewable energy resource (solar and wind) data to other geographic data, such as land use, protected areas, elevation, etc. The GsT was completely redesigned and re-released in November 2010 to provide a more modern, easier-to-use interface with considerably faster analytical querying capabilities. The revised version of the Geospatial Toolkit for Turkey is available using the following link: http://www.nrel.gov/international/downloads/gst_turkey.exe units: kWh/m sq. per day, DNI 10km Resolution by GeoModelSource: GeoModelAccess shared data and shapefiles.

Solar DNI Polygon Turkey 10km GeoModel 2010 (swera:dni_geomodel_high_900913)

SRID 900913 of two available coordinate systems. Developed by NREL and the U.S. Trade and Development Agency, this geographic toolkit that allows users to relate the renewable energy resource (solar and wind) data to other geographic data, such as land use, protected areas, elevation, etc. The GsT was completely redesigned and re-released in November 2010 to provide a more modern, easier-to-use interface with considerably faster analytical querying capabilities. The revised version of the Geospatial Toolkit for Turkey is available using the following link: http://www.nrel.gov/international/downloads/gst_turkey.exe units: kWh/m sq. per day, DNI 10km Resolution by GeoModelSource: GeoModelAccess shared data and shapefiles.

Solar DNI Polygon Brazil 10km INPE (swera:dni_inpe_high)

SRID 4326 of two available coordinate systems. Normal direct solar radiation in kWh/m2/day for 1 year organized into cells with 10km x 10km units:KWh/m sq. per day, Source: INPE (National Institute for Space Research) and LABSOLAR (Laboratory of Solar Energy/Federal University of Santa Catarina) - Brazil

Solar DNI Polygon Brazil 10km INPE (swera:dni_inpe_high_900913)

SRID 900913 of two available coordinate systems. Normal direct solar radiation in kWh/m2/day for 1 year organized into cells with 10km x 10km units:KWh/m sq. per day, Source: INPE (National Institute for Space Research) and LABSOLAR (Laboratory of Solar Energy/Federal University of Santa Catarina) - Brazil

Solar DNI Polygon Brazil 40km INPE (swera:dni_inpe_mod)

SRID 4326 of two available coordinate systems. Normal direct solar radiation in kWh/m2/day for 1 year organized into cells with 40km x 40km units:KWh/m sq. per day, Source: INPE (National Institute for Space Research) and LABSOLAR (Laboratory of Solar Energy/Federal University of Santa Catarina) - Brazil

Solar DNI Polygon Brazil 40km INPE (swera:dni_inpe_mod_900913)

SRID 900913 of two available coordinate systems. Normal direct solar radiation in kWh/m2/day for 1 year organized into cells with 40km x 40km Source: INPE (National Institute for Space Research) and LABSOLAR (Laboratory of Solar Energy/Federal University of Santa Catarina) - Brazil

Solar DNI Polygon Global 1 Degree NASA 2008 (swera:dni_nasa_low)

Direct Normal Irradiance (kWh/m^2/day)NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Jan 2008)22-year Monthly & Annual Average (July 1983 - June 2005) Source: U.S. National Aeronautics and Space Administration (NASA), Surface meteorology and Solar Energy (SSE)

Solar DNI Polygon Multiple Countries 40km NREL (swera:dni_nrel_mod)

Monthly Average Solar Resource for horizontal and tilted flat-plates, and 2-axis tracking concentrating collectors. These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. Countries included in dataset include: Africa, Bangladesh, Brazil, Caribbean, Central America, China, East Asia, Ethiopia, Ghana, Kenya, Mexico, Nepal, South America, Sri Lanka, and the United States. Units: kWh/m^2/day Source: U.S. National Renewable Energy Laboratory (NREL)

Solar DNI Polygon Multiple Countries 40km NREL (swera:dni_nrel_mod_900913)

Monthly Average Solar Resource for horizontal and tilted flat-plates, and 2-axis tracking concentrating collectors. These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. Countries included in dataset include: Africa, Bangladesh, Brazil, Caribbean, Central America, China, East Asia, Ethiopia, Ghana, Kenya, Mexico, Nepal, South America, Sri Lanka, and the United States. Units: kWh/m^2/day Source: U.S. National Renewable Energy Laboratory (NREL)

Solar DNI Polygon Multiple Countries 10km SUNY (swera:dni_suny_high)

High resolution monthly average direct normal irradiance (DNI) solar resource for Afghanistan, Bhutan, Central America, Cuba, India, Pakistan, United States. units:KWh/m sq. per day, Source: SUNY Albany

Solar DNI Polygon Multiple Countries 10km SUNY (swera:dni_suny_high_900913)

High resolution monthly average direct normal irradiance (DNI) solar resource for Afghanistan, Bhutan, Central America, Cuba, India, Pakistan, United States. units:KWh/m sq. per day, Source: SUNY Albany

Solar DNI Annual GeoTIFF Namibia 1km SolarGIS 2012 (irena:dni_year_nam_tiled)

DNI Namibia (SolarGIS) Direct Normal Irradiation (c) 2012 GeoModel Solar http://solargis.info Annual Solar DNI Values. Units: kWh/m2/month Annual and monthly long-term average representing years 1994-2011.

EGS Favorability 2009 (gt_prospector:egsfavorability2009)

Source data for deep EGS includes temperature at depth from 3 to 10 km provided by Southern Methodist University Geothermal Laboratory (Blackwell and Richards, 2009) and analyses (for regions with temperatures >= 150 degrees C) performed by NREL (2009). Class values reflect relative favorability, with 1 being most favorable, 5 being least favorable, and 999 not having been assessed due to temperatures less than 150 degrees C at 10 km depth.

Geomorphology Exclusion Grid EU MENA (irena:eumena_geomorph)

Geomorphology exclusion of the EU and MENA regions.

Hydrography Grid EU MENA (irena:eumena_hydrogr)

Hydrography of the EU and MENA regions.

Protected Areas Grid EU MENA (irena:eumena_protect)

Protected area of the EU and MENA regions.

Urban Areas Grid EU MENA (irena:eumena_urban)

Urban areas of the EU and MENA regions.

faults_500k (gt_prospector:faults_500k)

Data was digitized from original scribe sheets used to prepare the published Geologic Map of Wyoming (Love and Christiansen, 1985), consequently at a 1:500,000 scale.

favorabilitysurface (gt_prospector:favorabilitysurface)

NULL

gb_wells (gt_prospector:gb_wells)

Temperature at depth (O&G wells): Great Basin well database, Source: U.S. Geological Survey (http://pubs.usgs.gov/of/1999/of99-425/webmaps/database.xls)

gbgrstns (gt_prospector:gbgrstns)

Gravity station points: Great Basin, pointset data, Source: Nevada Bureau of Mines and Geology (NBMG) (ftp://ftp.nbmg.unr.edu/pub/geothermal/07_Geophysics_Data/GBGrStns.zip)

gbkgra (gt_prospector:gbkgra)

NULL

gbpowerplants (gt_prospector:gbpowerplants)

SMU Temperature at Depth Map: Great Basin Power Plants

geohgb_0 (gt_prospector:geohgb_0)

Geothermometry (waters): GB hot spring & well analyses, Source: Great Basin College and the University of Nevada, Reno

NREL Georgia 50m Wind Resource (data_res:georgia_50mwind)

Abstract: Annual average wind resource potential for the state of Georgia at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 17, datum WGS 84 projection system. Source: AWS TrueWind/NREL

geothermal_geologic_zones (gt_prospector:geothermal_geologic_zones)

NULL

geothermallcoe_noexclusionsforatlas (gt_prospector:geothermallcoe_noexclusionsforatlas)

Qualitative assessment of geothermal potential (Enhanced Geothermal System EGS) for the US based on Levelized Cost of Electricity.

RE_Atlas Geothermal (IHS) (re_atlas:geothermalpoint)

Map does not include shallow Deep Enhanced Geothermal Systems (EGS) resources located near hydrothermal sites or USGS assessment of undiscovered hydrothermal resources. Source data for deep EGS includes temperature at depth from 3 to 10 km provided by Southern Methodist University Geothermal Laboratory (Blackwell & Richards, 2009) and analyses (for regions with temperatures ≥150°C) performed by NREL (2009). N/A regions have temperatures less than 150°C at 10 km depth and were not assessed for deep EGS potential. Temperature at depth data for deep EGS in Alaska and Hawaii not available. Qualitative classes are based on temperature and depth ranges. Temperature values are not exclusive to any single class and may be located at different depths from one class to the next. Classes express approximate favorability for geothermal resource, with a lower number indicating the possibility of a higher potential value.

Solar GHI Polygon Multiple Countries 10km DLR 2000-2003 (swera:ghi_dlr_high)

Data of high resolution (10kmx10km) Direct Normal Irradiance (DNI) for Bangladesh, China, Ethiopia, Ghana, Kenya, Nepal, Sri Lanka, United Arab Emirates. Years collected between 2000 to 2003, varying for each individual country included. units:KWh/m sq. per day, Source: DLR - Deutsches Zentrum für Luft- und Raumfahrt

Solar GHI Polygon Multiple Countries 10km DLR 2000-2003 (swera:ghi_dlr_high_900913)

Data of high resolution (10kmx10km) Direct Normal Irradiance (DNI) for Bangladesh, China, Ethiopia, Ghana, Kenya, Nepal, Sri Lanka, United Arab Emirates. Years collected between 2000 to 2003, varying for each individual country included. units:KWh/m sq. per day, Source: DLR - Deutsches Zentrum für Luft- und Raumfahrt

Solar GHI Polygon Turkey 10km GeoModel (swera:ghi_geomodel_high)

SRID 4326 of two available coordinate systems. Solar GHI 10 km resolution by GeoModel for Turkey. Units: kWh/m sq. per day. Source: GeoModel

Solar GHI Polygon Turkey 10km GeoModel (swera:ghi_geomodel_high_900913)

SRID 900913 of two available coordinate systems. Solar GHI 10 km resolution by GeoModel for Turkey. Units: kWh/m sq. per day. Source: GeoModel

Solar GHI Polygon Brazil 10km INPE 2009 (swera:ghi_inpe_high)

SRID 4326 of two available coordinate systems. Global horizontal solar radiation in kWh/m2/day for 1 year organized into cells with 10km x 10km. The assessment of reliability levels of the BRASIL-SR model were performed through the evaluation of the deviations shown by the estimated values for solar radiation flux vis-à-vis the values measured at the surface (ground truth). This evaluation was done in two phases. The first phase consisted in an inter-comparison between the core radiation transfer models adopted by the SWERA Project to map the solar energy in the various countries participating in the project. The HELIOSAT model took part in this phase like benchmark due to its employment to map solar energy resources in countries from European Union. In the second phase, the solar flux estimates provided by the BRASIL-SR model were compared with measured values acquired at several solarimetric stations spread along the Brazilian territory. Source: INPE (National Institute for Space Research) and LABSOLAR (Laboratory of Solar Energy/Federal University of Santa Catarina) - Brazil

Solar GHI Polygon Brazil 10km INPE 2009 (swera:ghi_inpe_high_900913)

SRID 900913 of two available coordinate systems. Global horizontal solar radiation in kWh/m2/day for 1 year organized into cells with 10km x 10km. The assessment of reliability levels of the BRASIL-SR model were performed through the evaluation of the deviations shown by the estimated values for solar radiation flux vis-à-vis the values measured at the surface (ground truth). This evaluation was done in two phases. The first phase consisted in an inter-comparison between the core radiation transfer models adopted by the SWERA Project to map the solar energy in the various countries participating in the project. The HELIOSAT model took part in this phase like benchmark due to its employment to map solar energy resources in countries from European Union. In the second phase, the solar flux estimates provided by the BRASIL-SR model were compared with measured values acquired at several solarimetric stations spread along the Brazilian territory. Source: INPE (National Institute for Space Research) and LABSOLAR (Laboratory of Solar Energy/Federal University of Santa Catarina) - Brazil

Solar GHI Polygon S.America 40km INPE 2009 (swera:ghi_inpe_mod)

SRID 4326 of two available coordinate systems. Global Horizontal Solar Radiation for South America with 40km resolution. Units: KWh/m sq. per day, Source: INPE (National Institute for Spatial Research) and LABSOLAR (Laboratory of Solar Energy/Federal University of Santa Catarina) - Brazil

Solar GHI Polygon S.America 40km INPE 2009 (swera:ghi_inpe_mod_900913)

SRID 900913 of two available coordinate systems. Global Horizontal Solar Radiation for South America with 40km resolution. Units: KWh/m sq. per day, Source: INPE (National Institute for Spatial Research) and LABSOLAR (Laboratory of Solar Energy/Federal University of Santa Catarina) - Brazil

Solar GHI Polygon Global 1 Degree NASA 2008 (swera:ghi_nasa_low)

Global Horizontal IrradianceNASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Jan 2008)22-year Monthly & Annual Average (July 1983 - June 2005) Parameter: Insolation Incident On A Horizontal Surface (kWh/m^2/day) Internet: http://eosweb.larc.nasa.gov/sse/ Note 1: SSE Methodology & Accuracy sections online Note 2: Lat/Lon values indicate the lower left corner of a 1x1 degree region. Negative values are south and west; positive values are north and east. Boundaries of the -90/-180 region are -90 to -89 (south) and -180 to -179 (west). The last region, 89/180, is bounded by 89 to 90 (north) and 179 to 180 (east). The mid-point of the region is +0.5 added to the the Lat/Lon value. These data are regional averages; not point data.Created: March 12, 2008See the NASA Surface meteorology and Solar Energy (SSE) web site at http://eosweb.larc.nasa.gov/sse/. The source data was downloaded from the SSE website at Data Retrieval: Meteorology and Solar Energy > Global data sets as text files. The tabular data was then converted to the shapefile format. Source: U.S. National Aeronautics and Space Administration (NASA), Surface meteorology and Solar Energy (SSE)

Solar GHI Polygon Multiple Countries 40km NREL 2006 (swera:ghi_nrel_mod)

SRID 4326 of two available coordinate systems. Monthly average solar resource for horizontal flat-plate collectors for Africa, Bangladesh, Brazil, Caribbean, Central AMerica, Eas Asia, Ethiopia, Ghana, Kenya, Mexico, Nepal, South America, and Sri Lanka. These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. Existing ground measurement stations are used to validate the data where possible. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties associated with meteorological input to the model. The local cloud cover can vary significantly even within a single grid cell as a result of terrain effects and other microclimate influences. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain. Source: NREL

Solar GHI Polygon Multiple Countries 40km NREL 2006 (swera:ghi_nrel_mod_900913)

SRID 900913 of two available coordinate systems. Monthly average solar resource for horizontal flat-plate collectors for Africa, Bangladesh, Brazil, Caribbean, Central AMerica, Eas Asia, Ethiopia, Ghana, Kenya, Mexico, Nepal, South America, and Sri Lanka. These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. Existing ground measurement stations are used to validate the data where possible. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties associated with meteorological input to the model. The local cloud cover can vary significantly even within a single grid cell as a result of terrain effects and other microclimate influences. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain. Source: NREL

Solar GHI Polygon Multiple Countries 10km SUNY (swera:ghi_suny_high)

SRID 4326 of two available coordinate systems. Monthly global horizontal irradiance for Afghanistan, Bhutan, Central America, Cuba, India, Pakistan, and the United States. Cell size 10km x 10km. Units: kWh/m sq. per day Source: SUNY Albany

Solar GHI Polygon Multiple Countries 10km SUNY (swera:ghi_suny_high_900913)

SRID 900913 of two available coordinate systems. Monthly global horizontal irradiance for Afghanistan, Bhutan, Central America, Cuba, India, Pakistan, and the United States. Cell size 10km x 10km. Units: kWh/m sq. per day Source: SUNY Albany

Land Cover GeoTIFF East Hemisphere GeoModel 2000 (irena:glc00_east_tiled)

Global Land Cover 2000 (GLC2000) Global Land Cover 2000 © 2003 European Communities Resolution: 0:00:32.142857 Values / definition 1 evergreen broadleaved forests 2 deciduous broadleaved forests, closed (> 40%) 3 deciduous broadleaved forests, open (15-40%) 4 evergreen needle-leaved forest 5 deciduous needle-leaved forest 6 mixed forest 7 evergreen broadleaved - swamp forest 8 evergreen broadleaved - mangrove forest 9 mosaic - tree cover dominant with other vegetation component (natural, crop component) 10 burnt tree cover 11 evergreen shrubland 12 deciduous shrubland 13 grassland 14 sparsely vegetated cover 15 wetlands 16 croplands 17 mosaic - cropland dominant / tree cover, other natural vegetation 18 mosaic - cropland dominant / shrub, grass cover 19 bare areas 20 water bodies 21 snow and ice 22 artificial surfaces and associated areas 23 cover unknown, no data

Land Cover GeoTIFF West Hemisphere GeoModel 2000 (irena:glc00_west_tiled)

Global Land Cover 2000 (GLC2000) Global Land Cover 2000 © 2003 European Communities Resolution: 0:00:32.142857 Values / definition 1 evergreen broadleaved forests 2 deciduous broadleaved forests, closed (> 40%) 3 deciduous broadleaved forests, open (15-40%) 4 evergreen needle-leaved forest 5 deciduous needle-leaved forest 6 mixed forest 7 evergreen broadleaved - swamp forest 8 evergreen broadleaved - mangrove forest 9 mosaic - tree cover dominant with other vegetation component (natural, crop component) 10 burnt tree cover 11 evergreen shrubland 12 deciduous shrubland 13 grassland 14 sparsely vegetated cover 15 wetlands 16 croplands 17 mosaic - cropland dominant / tree cover, other natural vegetation 18 mosaic - cropland dominant / shrub, grass cover 19 bare areas 20 water bodies 21 snow and ice 22 artificial surfaces and associated areas 23 cover unknown, no data

global_wind_grid (workinglayers:global_wind_grid)

global_wind_grid_east (workinglayers:global_wind_grid_east)

global_wind_grid_no_us (workinglayers:global_wind_grid_no_us)

Wind Polygon Multiple Countries 200m NREL (swera:global_wind_grid_no_us)

SRID 4326 of two available SRIDs.. Wind resource polygon at 200 meter resolution for Mexico, Cuba, Dominican Republic, Belize, Guatemala, Honduras, El Salvador, Nicaragua, Ghana, China, Mongolia, Pakistan, Afghanistan, some parts of Russia, and some offshore resource availability for the countries above.

Wind Polygon Multiple Countries 200m NREL (swera:global_wind_grid_no_us_900913)

SRID 900913 of two available SRIDs.. Wind resource polygon at 200 meter resolution for Mexico, Cuba, Dominican Republic, Belize, Guatemala, Honduras, El Salvador, Nicaragua, Ghana, China, Mongolia, Pakistan, Afghanistan, some parts of Russia, and some offshore resource availability for the countries above.

global_wind_grid_west (workinglayers:global_wind_grid_west)

global_wind_grid_west_no_us (workinglayers:global_wind_grid_west_no_us)

Wind Speed 30km Offshore NOAA 2006, 2008, 2009 (swera:global_wind_offshore)

SRID 4326 of two available coordinate systems. GIS data for offshore wind speed (meters/second). Specified to Exclusive Economic Zones (EEZ).Wind resource based on NOAA blended sea winds and monthly wind speed at 30km resolution, using a 0.11 wind sheer to extrapolate 10m - 90m. Annual average >= 10 months of data, no nulls. Units:m/s at 90m ASL. Source: National Renewable Energy Laboratory (NREL)

Wind Speed 30km Offshore NOAA 2006, 2008, 2009 (swera:global_wind_offshore_900913)

SRID 900913 of two available coordinate systems. GIS data for offshore wind speed (meters/second). Specified to Exclusive Economic Zones (EEZ).Wind resource based on NOAA blended sea winds and monthly wind speed at 30km resolution, using a 0.11 wind sheer to extrapolate 10m - 90m. Annual average >= 10 months of data, no nulls. Units:m/s at 90m ASL. Source: National Renewable Energy Laboratory (NREL)

NREL Great Lakes 90m Offshore Wind Resource (data_res:great_lakes_90mwindspeed_off)

Abstract: Annual average offshore wind speed for the Great Lakes (Indiana, Illinois, Michigan, Minnesota, New York, Ohio, Pennsylvania, and Wisconsin) at a 90 meter height. Supplemental Information: The annual wind speed estimates were produced by AWS Truepower for an offshore mapping project using their MesoMap system and historical weather data. This shapefile was generated from raster datasets with a 200 m spatial esolution and a projection of UTM zone 15, datum WGS 84 and then projected to Geographic Decimal Degrees, datum WGS 84. Source: AWS Truepower/NREL

Elevation Multipolygon Afghanistan NREL 1993 (nrel:gstk_afghanistan_01_elevation)

Afghanistan Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Polygon Afghanistan NREL 1997 (nrel:gstk_afghanistan_02_landuse)

Afghanistan Landuse Layer Source: Afghanistan Information Mangement SErvice (AIMS) (1997) Description: Land use/land cover categories. Spatial Resolution: 1:250,000

Municipal Solid Waste Multipolygon Afghanistan NREL 2007 (nrel:gstk_afghanistan_03_msw)

Afghanistan Municipal Solid Waste Layer Source: National Renewable Energy Laboratory (2007) Description: Estimated municipal solid waste residue, based on population. Spatial Resolution: point locations

Direct Solar Multipolygon Afghanistan NREL 2008 (nrel:gstk_afghanistan_13_solar_direct)

Afghanistan Direct Solar Layer Source: State University of New York - Perez Model(2008) Description: Direct normal irradiance (DNI) averaged annually and monthly for the period April 2002 - Sept 2005. Spatial Resolution: 0.1 degrees (nominally 10 km)

Global Solar Multipolygon Afghanistan NREL 2008 (nrel:gstk_afghanistan_14_solar_glo)

Afghanistan Global Solar Layer Source: State University of New York - Perez Model(2008) Description: Global horizontal irradiance (GHI) averaged annually and monthly for the period April 2002 - Sept 2005. Spatial Resolution: 0.1 degrees (nominally 10 km)

Wind Resource Multipolygon Afghanistan NREL 2007 (nrel:gstk_afghanistan_20_wind)

Afghanistan Wind Resource Layer Source: National Renewable Energy Laboratory (NREL) and AWS Truepower (2007) Description: Annual mean wind power density (W/m2) at 50 m height above ground level. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Spatial Resolution: 1 km

Lakes Multipolygon Afghanistan NREL 1997 (nrel:gstk_afghanistan_30_lakes)

Afghanistan Lakes Layer Source: Afghanistan Information Mangement SErvice (AIMS) (1997) Description: Lake polygon features from the U.S. Defense Mapping Agency 1:100,000 scale topo maps. Spatial Resolution: 1:100,000

Protected Areas Polygon Afghanistan NREL 2005 (nrel:gstk_afghanistan_31_protectedarea)

Afghanistan Protected Areas Layer Source: World Database on Protected Areas Consortium, copyright World Conservation Union (IUCN) and UNEP-World Conservation Monitoring Centre (UNEP-WCMC) (2005) Description: Database of protected areas of IUCN categories I through VI, other protected areas and areas defined under international agreements. Spatial Resolution: Varied, compiled from multiple sources

State Boundaries Multipolygon Afghanistan NREL 1998 (nrel:gstk_afghanistan_38_subcountrybnd1)

Afghanistan State Boundaries Layer Source: Afghanistan Information Mangement SErvice (AIMS) (1998) Description: Provincial administrative boundaries of Afghanistan. Spatial Resolution: 1:250,000

Country Boundary Multipolygon Afghanistan NREL 2002 (nrel:gstk_afghanistan_39_countryboundary)

Afghanistan Country Boundary Layer Source: Afghanistan Information Mangement Service (AIMS) (2002) Description: International administrative boundaries of Afghanistan, mapped at 1:100,000 scale from the U.S. Defense Mapping Agency topo maps. Spatial Resolution: 1:100,000

Rivers Multilinestring Afghanistan NREL 1990 (nrel:gstk_afghanistan_40_rivers)

Afghanistan Rivers Layer Source: U.S. Agency for International Development (USAID) (1990) Description: Major rivers. Spatial Resolution: 1:100,000

Roads Multilinestring Afghanistan NREL 1998 (nrel:gstk_afghanistan_43_roads)

Afghanistan Roads Layer Source: Afghanistan Information Mangement Service (AIMS) (1998) Description: Major road network. Spatial Resolution: 1:100,000

Transmission Lines Linestring Afghanistan NREL 2006 (nrel:gstk_afghanistan_44_transmissionline)

Afghanistan Transmission Lines Layer Source: digitized from Power and Gas Grid Map of South Asia (2006) Description: Utility electric transmission lines. Spatial Resolution: Not stated.

Power Plants Point Afghanistan NREL 2006 (nrel:gstk_afghanistan_51_powerplant)

Afghanistan Power Plants Layer Source: digitized from Power and Gas Grid Map of South Asia (2006) Description: Power plants. Spatial Resolution: Not stated.

Facilities Point Afghanistan NREL 2003 (nrel:gstk_afghanistan_52_facilities)

Afghanistan Facilities Layer Source: Afghanistan Information Mangement Service (AIMS) (2003) Description: Health facility locations (basic health centers, mobile control centers, prov. Spatial Resolution: point

Airports Point Afghanistan NREL 2000 (nrel:gstk_afghanistan_53_airports)

Afghanistan Airports Layer Source: Afghanistan Information Mangement Service (AIMS) (2000) Description: Airport locations. Spatial Resolution: 1:250,000

Geothermal Point Afghanistan NREL 2004 (nrel:gstk_afghanistan_54_geoth)

Afghanistan Geothermal Layer Source: digitized from Geothermal Energy in Afghanistan: Prospects and Potential (Saba, Najaf, Musazai, and Taraki) (2004) Description: Hydrothermal resource locations >20 degrees C. Spatial Resolution: not stated

Cities Point Afghanistan NREL 1997 (nrel:gstk_afghanistan_59_cities)

Afghanistan Cities Layer Source: Afghanistan Information Mangement Service (AIMS) (1997) Description: Settlements of Afghanistan Spatial Resolution: 1:100,000

Elevation Polygon Bangladesh NREL 1993 (nrel:gstk_bangladesh_01_elevation)

Bangladesh Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Bangladesh NREL 1993 (nrel:gstk_bangladesh_02_landuse)

Bangladesh Landuse Layer Source: U.S. Geological Survey Global Land Use/Land Cover dataset (1993) Description: Land use/land cover categories, using the U.S. Geological Survey Modified Level 2 legend. Spatial Resolution: 1 km.

Direct Solar Multipolygon Bangladesh NREL 2004 (nrel:gstk_bangladesh_13_solar_direct)

Bangladesh Direct Solar Layer Source: Deutsches Zentrum für Luft- und Raumfahrt (DLR) (2004) Description: Direct normal irradiance (DNI) averaged annually and monthly for the years 2000, 2002, and 2003. Spatial Resolution: 0.1 degrees (nominally 10 km)

Global Solar Multipolygon Bangladesh NREL 2004 (nrel:gstk_bangladesh_14_solar_glo)

Bangladesh Global Solar Layer Source: Deutsches Zentrum für Luft- und Raumfahrt (DLR) (2004) Description: Global horizontal irradiance (GHI) averaged annually and monthly for the years 2000, 2002, and 2003. Spatial Resolution: 0.1 degrees (nominally 10 km)

Wind Resource Multipolygon Bangladesh NREL 2008 (nrel:gstk_bangladesh_20_wind)

Bangladesh Wind Resource Layer Source: Risø Technical University of Denmark (Risø DTU) (2008) Description: Simulated annual mean wind power density (W/m2).at 50 m height above ground level as described in the mesoscale model. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Spatial Resolution: 5 km

Protected Areas Multipolygon Bangladesh NREL 2005 (nrel:gstk_bangladesh_31_protectedarea)

Bangladesh Protected Areas Layer Source: World Database on Protected Areas Consortium, copyright World Conservation Union (IUCN) and UNEP-World Conservation Monitoring Centre (UNEP-WCMC) (2005) Description: Database of protected areas of IUCN categories I through VI, other protected areas and areas defined under international agreements. Spatial Resolution: Varied, compiled from multiple sources

State Boundaries Multipolygon Bangladesh NREL 1998 (nrel:gstk_bangladesh_38_subcountrybnd1)

Bangladesh State Boundaries Layer Source: ESRI ArcWorld Supplement (1998) Description: First level internal administrative boundaries. Spatial Resolution: 1:3,000,000

Country Boundary Multipolygon Bangladesh NREL 1998 (nrel:gstk_bangladesh_39_countryboundary)

Bangladesh Country Boundary Layer Source: ESRI ArcWorld Supplement (1998) Description: Country level administrative boundaries. Spatial Resolution: 1:3,000,000

Rivers Multilinestring Bangladesh NREL 1997 (nrel:gstk_bangladesh_40_rivers)

Bangladesh Rivers Layer Source: Bangladesh Water Resources Planning Organization (1997) Description: Major rivers. Spatial Resolution: 1:50,000

Roads Multilinestring Bangladesh NREL 2005 (nrel:gstk_bangladesh_43_roads)

Bangladesh Roads Layer Source: Bangladesh Department of Roads and Highway (Unknown, before 2005) Description: National and regional road network of Bangladesh, and the feeder type A roads (roads connecting Thana HQ with the existing road network). Spatial Resolution: Unknown

Transmission Lines Linestring Bangladesh NREL 1996 (nrel:gstk_bangladesh_44_transmissionline)

Bangladesh Transmission Lines Layer Source: Power Transmission Lines, Bangladesh Power Development Board (1996-1997)) Description: Electric power transmission lines of Bangladesh. Spatial Resolution: 1:3,000,000

Power Plants Point Bangladesh NREL 2005 (nrel:gstk_bangladesh_51_powerplant)

Bangladesh Power Plants Layer Source: Bangladesh Power Development Board (Unknown, before 2005) Description: Grid substations. Spatial Resolution: 1:3,000,000

Facilities Point Bangladesh NREL 1997 (nrel:gstk_bangladesh_52_facilities)

Bangladesh Facilities Layer Source: Pennsylvania State University Libraries, Pattee Maproom (1997) Description: Cultural landmarks of Bangladesh. Spatial Resolution: Unknown

Airports Point Bangladesh NREL 2005 (nrel:gstk_bangladesh_53_airports)

Bangladesh Airports Layer Source: Bangladesh Civil Aviation Authority (Unknown, before 2005) Description: Aerodrome locations, including all airports and airfields. Spatial Resolution: Unknown

Cities Point Bangladesh NREL 1997 (nrel:gstk_bangladesh_59_cities)

Bangladesh Cities Layer Source: Pennsylvania State University Libraries, Pattee Maproom (1997) Description: Populated places in Bangladesh. . Spatial Resolution: Unknown

Elevation Multipolygon Bhutan NREL 1993 (nrel:gstk_bhutan_01_elevation)

Bhutan Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Bhutan NREL 1993 (nrel:gstk_bhutan_02_landuse)

Bhutan Landuse Layer Source: U.S. Geological Survey Global Land Use/Land Cover dataset (1993) Description: Land use/land cover categories, using the U.S. Geological Survey Modified Level 2 legend. Spatial Resolution: 1 km.

Direct Solar Multipolygon Bhutan NREL 2008 (nrel:gstk_bhutan_13_solar_direct)

Bhutan Direct Solar Layer Source: State University of New York - Perez Model(2008) Description: Direct normal irradiance (DNI) averaged annually and monthly for the years 2002-2007. Spatial Resolution: 0.1 degrees (nominally 10 km)

Global Solar Multipolygon Bhutan NREL 2008 (nrel:gstk_bhutan_14_solar_glo)

Bhutan Global Solar Layer Source: State University of New York - Perez Model(2008) Description: Global horizontal irradiance (GHI) averaged annually and monthly for the years 2002-2007. Spatial Resolution: 0.1 degrees (nominally 10 km)

Tilt Solar Multipolygon Bhutan NREL 2008 (nrel:gstk_bhutan_16_solar_tilt)

Bhutan Tilt Solar Layer Source: State University of New York - Perez Model(2008) Description: Solar resource for a fixed flat plat collector, facing the equator with a tilt equal to the cell's latitude, averaged annually and monthly for the years 2002-2007. Spatial Resolution: 0.1 degrees (nominally 10 km)

Wind Resource Polygon Bhutan NREL 2008 (nrel:gstk_bhutan_20_wind)

Bhutan Wind Resource Layer Source: National Renewable Energy Laboratory (NREL) and AWS Truepower (2008) Description: Annual mean wind power density (W/m2) at 50 m height above ground level. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Spatial Resolution: 1 km

Protected Areas Multipolygon Bhutan NREL (nrel:gstk_bhutan_31_protectedarea)

Bhutan Protected Areas Layer Source: Bhutan Department of Energy (Date Unknown) Description: Parks and other national reserves. Spatial Resolution: Unknown

State Boundaries Polygon Bhutan NREL (nrel:gstk_bhutan_38_subcountrybnd1)

Bhutan State Boundaries Layer Source: Bhutan Department of Energy (Date Unknown) Description: First level internal administrative boundaries. Spatial Resolution: Unknown

Country Boundary Polygon Bhutan NREL (nrel:gstk_bhutan_39_countryboundary)

Bhutan Country Boundary Layer Source: Bhutan Department of Energy (Date Unknown) Description: Country level administrative boundaries. Spatial Resolution: Unknown

Rivers Multilinestring Bhutan NREL (nrel:gstk_bhutan_40_rivers)

Bhutan Rivers Layer Source: Bhutan Department of Energy (Date Unknown) Description: Major rivers. Spatial Resolution: Unknown

Roads Multilinestring Bhutan NREL (nrel:gstk_bhutan_43_roads)

Bhutan Roads Layer Source: Bhutan Department of Energy (Date Unknown) Description: National road network. Spatial Resolution: Unknown

Transmission Lines Multilinestring Bhutan NREL (nrel:gstk_bhutan_44_transmissionline)

Bhutan Transmission Lines Layer Source: Bhutan Department of Energy (Date Unknown) Description: Electric power transmission lines of Bhutan. Spatial Resolution: Unknown

Power Plants Point Bhutan NREL (nrel:gstk_bhutan_51_powerplant)

Bhutan Power Plants Layer Source: Carbon Monitoring for Action (CARMA) carma.org Description: Power plants. Spatial Resolution: Unknown

Cities Point Bhutan NREL (nrel:gstk_bhutan_59_cities)

Bhutan Cities Layer Source: Bhutan Department of Energy (Date Unknown) Description: Populated places in Bhutan Spatial Resolution: Unknown

Elevation Multipolygon Brazil NREL 1993 (nrel:gstk_brazil_01_elevation)

Brazil Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 10 km, averaged from 1 km resolution data.

Landuse Multipolygon Brazil NREL 2001 (nrel:gstk_brazil_02_landuse)

Brazil Landuse Layer Source: World Wildlife Fund Terrestrial Ecosystems (2001) Description: Terrestrial ecosystem/land use characterization. Spatial Resolution: 1:3,000,000

Direct Solar Multipolygon Brazil NREL 2000 (nrel:gstk_brazil_13_solar_direct)

Brazil Direct Solar Layer Source: INPE (National Institute for Spatial Research) and LABSOLAR (Laboratory of Solar Energy/Federal University of Santa Catarina) - Brazil (2000/2001) Description: Direct normal irradiance (DNI) averaged annually and monthly. Spatial Resolution: 0.1 degrees (nominally 10 km)

Global Solar Multipolygon Brazil NREL 2000 (nrel:gstk_brazil_14_solar_glo)

Brazil Global Solar Layer Source: INPE (National Institute for Spatial Research) and LABSOLAR (Laboratory of Solar Energy/Federal University of Santa Catarina) - Brazil (2000/2001) Description: Global horizontal irradiance (GHI) averaged annually and monthly. Spatial Resolution: 0.1 degrees (nominally 10 km)

Tilt Solar Multipolygon Brazil NREL 2000 (nrel:gstk_brazil_16_solar_tilt)

Brazil Tilt Solar Layer Source: INPE (National Institute for Spatial Research) and LABSOLAR (Laboratory of Solar Energy/Federal University of Santa Catarina) - Brazil (2000/2001) Description: Solar resource for a fixed flat plat collector, facing the equator with a tilt equal to the cell's latitude, averaged annually and monthly. Spatial Resolution: 0.1 degrees (nominally 10 km)

Wind Resource Multipolygon Brazil NREL 2004 (nrel:gstk_brazil_20_wind)

Brazil Wind Resource Layer Source: CEPEL (Electric Energy Research Center/Federal University of Rio de Janeiro) - Brazil (2004) Description: Annual mean wind power density (W/m2) at 50 m height above ground level. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Spatial Resolution: 40 km

Lakes Polygon Brazil NREL 2001 (nrel:gstk_brazil_30_lakes)

Brazil Lakes Layer Source: DPI (Images Processing Division) - National Institute for Spacial Researches - Brazil (2001) Description: Major lakes. Spatial Resolution: Unknown

Protected Areas Multipolygon Brazil NREL 2003 (nrel:gstk_brazil_31_protectedarea)

Brazil Protected Areas Layer Source: IBAMA (Brazilian Institute for the Environment and Natural Renewable Resources) - Ministry of the Environment - Brazil (2003) Description: Parks and other national reserves. Spatial Resolution: Unknown

District Boundaries Multipolygon Brazil NREL (nrel:gstk_brazil_37_subcountrybnd2)

Brazil District Boundaries Layer Source: Metadata Not Available Description: Metadata Not Available Spatial Resolution: Metadata Not Available

State Boundaries Multipolygon Brazil NREL 2001 (nrel:gstk_brazil_38_subcountrybnd1)

Brazil State Boundaries Layer Source: DPI (Images Processing Division) - National Institute for Spacial Researches - Brazil (2001) Description: First level internal administrative boundaries. Spatial Resolution: Unknown

Country Boundary Multipolygon Brazil NREL 2000 (nrel:gstk_brazil_39_countryboundary)

Brazil Country Boundary Layer Source: DPI (Images Processing Division) - National Institute for Spacial Researches - Brazil (2000) Description: Country level administrative boundaries. Spatial Resolution: Unknown

Rivers Multilinestring Brazil NREL 2001 (nrel:gstk_brazil_40_rivers)

Brazil Rivers Layer Source: DPI (Images Processing Division) - National Institute for Spacial Researches - Brazil (2001) Description: Major rivers. Spatial Resolution: Unknown

Railroads Multilinestring Brazil NREL (nrel:gstk_brazil_42_railroad)

Brazil Railroads Layer Source: Ministry of Transportation - Brazil (Unknown) Description: Main roads. Spatial Resolution: Unknown

Roads Multilinestring Brazil NREL 2001 (nrel:gstk_brazil_43_roads)

Brazil Roads Layer Source: DPI (Images Processing Division) - National Institute of Spatial Researches - Brazil (2001) Description: Main roads. Spatial Resolution: Unknown

Transmission Lines Multilinestring Brazil NREL 2004 (nrel:gstk_brazil_44_transmissionline)

Brazil Transmission Lines Layer Source: ELETROBRAS (Brazilian Electric Central Inc.), Ministry of Mines and Energy (2004) Description: Electric power transmission lines 69 - 750 kV. Spatial Resolution: Unknown

Power Plants Point Brazil NREL 2002 (nrel:gstk_brazil_51_powerplant)

Brazil Power Plants Layer Source: ONS (National Operator of the Electric System) - Brazil (2002) Description: Power plants. Spatial Resolution: Unknown

Airports Point Brazil NREL 2004 (nrel:gstk_brazil_53_airports)

Brazil Airports Layer Source: ROTAER, a publication of Department of Air Space Control - Ministry of Aeronautic - Brazil (2004) Description: Airports. Spatial Resolution: Unknown

Cities Point Brazil NREL 2000 (nrel:gstk_brazil_59_cities)

Brazil Cities Layer Source: DPI (Images Processing Division) - National Institute of Spatial Researches - Brazil (2000) Description: Cities or major population centers in Brazil. Spatial Resolution: Unknown

Elevation Multipolygon Cambodia NREL 1993 (nrel:gstk_cambodia_01_elevation)

Cambodia Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Cambodia NREL 2010 (nrel:gstk_cambodia_02_landuse)

Cambodia Landuse Layer Source: ESA & UCLouvain GlobCover dataset (2010) Description: Land use/land cover categories Spatial resolution: 0.3km

Tilt Solar Multipolygon Cambodia NREL 2007 (nrel:gstk_cambodia_12_solar_tilt)

Cambodia Tilt Solar Layer Source: National Renewable Energy Lab CSR dataset (2007) Description: Solar resource for a fixed flat plat collector, facing the equator with a tilt equal to the cell's latitude, averaged annually and monthly. Spatial Resolution: 40 km

Direct Solar Multipolygon Cambodia NREL 2007 (nrel:gstk_cambodia_13_solar_direct)

Cambodia Direct Solar Layer Source: National Renewable Energy Lab CSR dataset (2007) Description: Direct normal irradiance (DNI) averaged annually and monthly. Spatial Resolution: 40 km

Global Solar Multipolygon Cambodia NREL 2007 (nrel:gstk_cambodia_14_solar_glo)

Cambodia Global Solar Layer Source: National Renewable Energy Lab CSR dataset (2007) Description: Global horizontal irradiance (GHI) averaged annually and monthly. Spatial Resolution: 40 km

Wind Resource Multipolygon Cambodia NREL 2001 (nrel:gstk_cambodia_20_wind)

Cambodia Wind Resource Layer Source: Wind Energy Resource Atlas of Southeast Asia (2001) Description: Annual mean wind power density (W/m2) at 65 m height above ground level. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Spatial Resolution: 1 km

Protected Areas Multipolygon Cambodia NREL 2013 (nrel:gstk_cambodia_31_protectedarea)

Cambodia Protected Areas Layer Source: OpenDevelopment Cambodia protected area dataset (2013) Description: Protected areas of Cambodia. Spatial Resolution: Not Stated

District Boundaries Multipolygon Cambodia NREL 2011 (nrel:gstk_cambodia_37_subcountrybnd2)

Cambodia District Boundaries Layer Source: OpenDevelopment Cambodia economic census 2011 dataset Description: District level administrative boundaries. Spatial Resolution: Not Stated

Province Boundaries Multipolygon Cambodia NREL 2011 (nrel:gstk_cambodia_38_subcountrybnd1)

Cambodia Province Boundaries Layer Source: OpenDevelopment Cambodia economic census 2011 dataset Description: Province level administrative boundaries. Spatial Resolution: Not Stated

Country Boundary Multipolygon Cambodia NREL 2011 (nrel:gstk_cambodia_39_countryboundary)

Cambodia Country Boundary Layer Source: OpenDevelopment Cambodia economic census 2011 dataset Description: Country level administrative boundaries. Spatial Resolution: Not Stated

Rivers Multilinestring Cambodia NREL 2008 (nrel:gstk_cambodia_40_rivers)

Cambodia Rivers Layer Source: ESRI Data & Maps, rivers (2008) Description: Major rivers. Spatial resolution: 1:15,000,000

Railroads Multilinestring Cambodia NREL 1992 (nrel:gstk_cambodia_42_railroads)

Cambodia Railroads Layer Source: Digital Chart of the World (1992) Description: Railroad lines. Spatial Resolution: 1:1,000,000

Roads Multilinestring Cambodia NREL 1992 (nrel:gstk_cambodia_43_roads)

Cambodia Roads Layer Source: Digital Chart of the World (1992) Description: Major road network. Spatial Resolution: 1:1,000,000

Transmission Lines Multilinestring Cambodia NREL 2013 (nrel:gstk_cambodia_44_transmissionline)

Cambodia Transmission Lines Layer Source: OpenDevelopment Cambodia hydropower transmission dataset (2013) Description: Utility electric transmission lines. Spatial Resolution: Not stated.

Power Plants Point Cambodia NREL 2013 (nrel:gstk_cambodia_51_powerplant)

Cambodia Power Plants Layer Source: Data from CARMA (www.carma.org) & OpenDevelopment Cambodia hydropower plants (2013) Description: Power Plants Spatial resolution: Not stated.

Airports Point Cambodia NREL 1992 (nrel:gstk_cambodia_53_airports)

Cambodia Airports Layer Source: Digital Chart of the World (1992) Description: Airport locations. Spatial Resolution: 1:1,000,000

Cities Point Cambodia NREL 1992 (nrel:gstk_cambodia_59_cities)

Cambodia Cities Layer Source: Digital Chart of the World (1992) Description: Populated places Spatial Resolution: 1:1,000,000

Elevation Multipolygon El Salvador NREL 1993 (nrel:gstk_elsalvador_01_elevation)

El Salvador Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon El Salvador NREL 2004 (nrel:gstk_elsalvador_02_landuse)

El Salvador Landuse Layer Source: Minesterio de Medio Ambiente y Recursos Naturales (received Jun 2004) Description: Land use/land cover categories Spatial Resolution: Unknown

Tilt Solar Multipolygon El Salvador NREL 2004 (nrel:gstk_elsalvador_12_solar_tilt)

El Salvador Tilt Solar Layer Source: National Renewable Energy Laboratory (NREL) Climatological Solar Radiation Model (2004) Description: Solar resource for a flat plate collector tilted towards the equation with a fixed tilt equal to the latitude, annual average and monthly values. Data were developed using NREL's Climatological Solar Radiation model, using information on cloud cover, atmospheric water vapor and trace gases, and atmospheric aerosols falling on a horizontal surface. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties of the model. Spatial Resolution: 40 km

Direct Solar Multipolygon El Salvador NREL 2005 (nrel:gstk_elsalvador_13_solar_direct)

El Salvador Direct Solar Layer Source: State University of New York - Perez Model(2005) Description: Direct normal irradiance (DNI) averaged annually and monthly for the years 1998-2002. Spatial Resolution: 0.1 degrees (nominally 10 km)

Global Solar Multipolygon El Salvador NREL 2005 (nrel:gstk_elsalvador_14_solar_glo)

El Salvador Global Solar Layer Source: State University of New York - Perez Model(2005) Description: Global horizontal irradiance (GHI) averaged annually and monthly for the years 1998-2002. Spatial Resolution: 0.1 degrees (nominally 10 km)

Wind Resource Multipolygon El Salvador NREL 2004 (nrel:gstk_elsalvador_20_wind)

El Salvador Wind Resource Layer Source: National Renewable Energy Laboratory (NREL) and AWS Truepower (2004) Description: Annual mean wind power density (W/m2) at 50 m height above ground level. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Spatial Resolution: 1 km

Lakes Polygon El Salvador NREL 2004 (nrel:gstk_elsalvador_30_lakes)

El Salvador Lakes Layer Source: Minesterio de Medio Ambiente y Recursos Naturales (received Jun 2004) Description: Lakes and lagoons of El Salvador Spatial Resolution: Unknown

Protected Areas Multipolygon El Salvador NREL 2004 (nrel:gstk_elsalvador_31_protectedarea)

El Salvador Protected Areas Layer Source: Minesterio de Medio Ambiente y Recursos Naturales (received Jun 2004) Description: Database of protected areas within El Salvador Spatial Resolution: Unknown

Country Boundary Polygon El Salvador NREL 2004 (nrel:gstk_elsalvador_39_countryboundary)

El Salvador Country Boundary Layer Source: Minesterio de Medio Ambiente y Recursos Naturales (received Jun 2004) Description: Country level administrative boundaries. Spatial Resolution: Unknown

Rivers Linestring El Salvador NREL 2004 (nrel:gstk_elsalvador_40_rivers)

El Salvador Rivers Layer Source: Minesterio de Medio Ambiente y Recursos Naturales (received Jun 2004) Description: Major rivers. Spatial Resolution: Unknown

Railroads Linestring El Salvador NREL 2004 (nrel:gstk_elsalvador_42_railroad)

El Salvador Railroads Layer Source: Minesterio de Medio Ambiente y Recursos Naturales (received Jun 2004) Description: Major rail lines of El Salvador Spatial Resolution: Unknown

Roads Linestring El Salvador NREL 2004 (nrel:gstk_elsalvador_43_roads)

El Salvador Roads Layer Source: Minesterio de Medio Ambiente y Recursos Naturales (received Jun 2004) Description: National and regional road network of El Salvador. Spatial Resolution: Unknown

Transmission Lines Linestring El Salvador NREL 2004 (nrel:gstk_elsalvador_44_transmissionline)

El Salvador Transmission Lines Layer Source: Minesterio de Medio Ambiente y Recursos Naturales (received Jun 2004) Description: Electric power transmission lines of El Salvador. Spatial Resolution: Unknown

Power Plants Point El Salvador NREL 2004 (nrel:gstk_elsalvador_51_powerplant)

El Salvador Power Plants Layer Source: Minesterio de Medio Ambiente y Recursos Naturales (received Jun 2004) Description: Power plants in El Salvador. Spatial Resolution: Unknown

Facilities Point El Salvador NREL 2004 (nrel:gstk_elsalvador_52_facilities)

El Salvador Facilities Layer Source: Minesterio de Medio Ambiente y Recursos Naturales (received Jun 2004) Description: Hospitals, schools and telecommunications facilities in El Salvador. Spatial Resolution: Unknown

Airports Point El Salvador NREL 2004 (nrel:gstk_elsalvador_53_airports)

El Salvador Airports Layer Source: Minesterio de Medio Ambiente y Recursos Naturales (received Jun 2004) Description: Airport locations in El Salvador. Spatial Resolution: Unknown

Cities Point El Salvador NREL 2004 (nrel:gstk_elsalvador_59_cities)

El Salvador Cities Layer Source: Minesterio de Medio Ambiente y Recursos Naturales (received Jun 2004) Description: Populated places in El Salvador Spatial Resolution: Unknown

Elevation Multipolygon Ghana NREL 1993 (nrel:gstk_ghana_01_elevation)

Ghana Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Ghana NREL 2005 (nrel:gstk_ghana_02_landuse)

Ghana Landuse Layer Source: Data collected for NREL by the Ghana Energy Commission - original source not stated (received Nov. 2005) Description: Land use/land cover categories Spatial Resolution: Unknown

Tilt Solar Multipolygon Ghana NREL 2004 (nrel:gstk_ghana_12_solar_tilt)

Ghana Tilt Solar Layer Source: Deutsches Zentrum für Luft- und Raumfahrt (DLR) (2004) Description: Fixed flat plate facing the equator with tilt = latitude, averaged annually and monthly for the years 2000, 2001, and 2002. Spatial Resolution: 0.1 degrees (nominally 10 km)

Direct Solar Multipolygon Ghana NREL 2004 (nrel:gstk_ghana_13_solar_direct)

Ghana Direct Solar Layer Source: Deutsches Zentrum für Luft- und Raumfahrt (DLR) (2004) Description: Direct normal irradiance (DNI) averaged annually and monthly for the years 2000, 2001, and 2002. Spatial Resolution: 0.1 degrees (nominally 10 km)

Global Solar Multipolygon Ghana NREL 2004 (nrel:gstk_ghana_14_solar_glo)

Ghana Global Solar Layer Source: Deutsches Zentrum für Luft- und Raumfahrt (DLR) (2004) Description: Global horizontal irradiance (GHI) averaged annually and monthly for the years 2000, 2001, and 2002. Spatial Resolution: 0.1 degrees (nominally 10 km)

Wind Resource Multipolygon Ghana NREL 2004 (nrel:gstk_ghana_20_wind)

Ghana Wind Resource Layer Source: National Renewable Energy Laboratory (NREL) and AWS Truepower (2004) Description: Annual mean wind power density (W/m2) at 50 m height above ground level. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Spatial Resolution: 1 km

Lakes Polygon Ghana NREL 1992 (nrel:gstk_ghana_30_lakes)

Ghana Lakes Layer Source: Digital Chart of the World (1992) Description: Major water features Spatial Resolution: 1:1,000,000

Protected Areas Polygon Ghana NREL 2005 (nrel:gstk_ghana_31_protectedarea)

Ghana Protected Areas Layer Source: Data collected for NREL by the Ghana Energy Commission - original source not stated (received Nov. 2005) Description: Database of protected forest areas Spatial Resolution: Unknown

Province Boundaries Multipolygon Ghana NREL 2005 (nrel:gstk_ghana_38_subcountrybnd1)

Ghana Province Boundaries Layer Source: Data collected for NREL by the Ghana Energy Commission - original source not stated (received Nov. 2005) Description: First level internal administrative boundaries. Spatial Resolution: Unknown

Country Boundary Polygon Ghana NREL 2005 (nrel:gstk_ghana_39_countryboundary)

Ghana Country Boundary Layer Source: Data collected for NREL by the Ghana Energy Commission - original source not stated (received Nov. 2005) Description: Country level administrative boundaries. Spatial Resolution: Unknown

Rivers Linestring Ghana NREL 1992 (nrel:gstk_ghana_40_rivers)

Ghana Rivers Layer Source: Digital Chart of the World (1992) Description: Major rivers. Spatial Resolution: 1:1,000,000

Railroads Linestring Ghana NREL 1992 (nrel:gstk_ghana_42_railroad)

Ghana Railroads Layer Source: Digital Chart of the World (1992) Description: Major rail lines. Spatial Resolution: 1:1,000,000

Roads Linestring Ghana NREL 1992 (nrel:gstk_ghana_43_roads)

Ghana Roads Layer Source: Digital Chart of the World (1992) Description: National road network. Spatial Resolution: 1:1,000,000

Transmission Lines Multilinestring Ghana NREL 2005 (nrel:gstk_ghana_44_transmissionline)

Ghana Transmission Lines Layer Source: Data collected for NREL by the Ghana Energy Commission - original source not stated (received Nov. 2005) Description: Electric power transmission lines. Spatial Resolution: Unknown

Airports Point Ghana NREL 1992 (nrel:gstk_ghana_53_airports)

Ghana Airports Layer Source: Digital Chart of the World (1992) Description: Airport locations. Spatial Resolution: 1:1,000,000

Cities Point Ghana NREL 2005 (nrel:gstk_ghana_59_cities)

Ghana Cities Layer Source: Data collected for NREL by the Ghana Energy Commission - original source not stated (received Nov. 2005) Description: Populated places Spatial Resolution: Unknown

Elevation Multipolygon Guatemala NREL 1993 (nrel:gstk_guatemala_01_elevation)

Guatemala Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Guatemala NREL 2001 (nrel:gstk_guatemala_02_landuse)

Guatemala Landuse Layer Source: Ministerio de Agricultura, Ganaderia y Alimentacion (Jun 2001) Description: Land use/land cover categories Spatial Resolution: 1:250,000

Tilt Solar Multipolygon Guatemala NREL 2004 (nrel:gstk_guatemala_12_solar_tilt)

Guatemala Tilt Solar Layer Source: National Renewable Energy Laboratory (NREL) Climatological Solar Radiation Model (2004) Description: Solar resource for a flat plate collector tilted towards the equation with a fixed tilt equal to the latitude, annual average and monthly values. Data were developed using NREL's Climatological Solar Radiation model, using information on cloud cover, atmospheric water vapor and trace gases, and atmospheric aerosols falling on a horizontal surface. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties of the model. Spatial Resolution: 40 km

Direct Solar Multipolygon Guatemala NREL 2005 (nrel:gstk_guatemala_13_solar_direct)

Guatemala Direct Solar Layer Source: State University of New York - Perez Model(2005) Description: Direct normal irradiance (DNI) averaged annually and monthly for the years 1998-2002. Spatial Resolution: 0.1 degrees (nominally 10 km)

Global Solar Multipolygon Guatemala NREL 2005 (nrel:gstk_guatemala_14_solar_glo)

Guatemala Global Solar Layer Source: State University of New York - Perez Model(2005) Description: Global horizontal irradiance (GHI) averaged annually and monthly for the years 1998-2002. Spatial Resolution: 0.1 degrees (nominally 10 km)

Wind Resource Polygon Guatemala NREL 2004 (nrel:gstk_guatemala_20_wind)

Guatemala Wind Resource Layer Source: National Renewable Energy Laboratory (NREL) and AWS Truepower (2004) Description: Annual mean wind power density (W/m2) at 50 m height above ground level. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Spatial Resolution: 1 km

Lakes Polygon Guatemala NREL 2001 (nrel:gstk_guatemala_30_lakes)

Guatemala Lakes Layer Source: Ministerio de Agricultura, Ganaderia y Alimentacion (Jun 2001) Description: Lakes, lagoons, mangrove swamps, marsh, river margins, and areas subject to flooding Spatial Resolution: 1:250,000

Protected Areas Polygon Guatemala NREL 2001 (nrel:gstk_guatemala_31_protectedarea)

Guatemala Protected Areas Layer Source: Ministerio de Agricultura, Ganaderia y Alimentacion (Jun 2001) Description: Database of protected areas within Guatemala Spatial Resolution: 1:250,000

Country Boundary Polygon Guatemala NREL 2001 (nrel:gstk_guatemala_39_countryboundary)

Guatemala Country Boundary Layer Source: Ministerio de Agricultura, Ganaderia y Alimentacion (Jun 2001) Description: Country level administrative boundaries. Spatial Resolution: 1:250,000

Rivers Linestring Guatemala NREL 2001 (nrel:gstk_guatemala_40_rivers)

Guatemala Rivers Layer Source: Ministerio de Agricultura, Ganaderia y Alimentacion (Jun 2001) Description: Major rivers. Spatial Resolution: 1:250,000

Railroads Linestring Guatemala NREL 2001 (nrel:gstk_guatemala_42_railroad)

Guatemala Railroads Layer Source: Ministerio de Agricultura, Ganaderia y Alimentacion (Jun 2001) Description: Major rail lines of Guatemala Spatial Resolution: 1:250,000

Roads Multilinestring Guatemala NREL 2001 (nrel:gstk_guatemala_43_roads)

Guatemala Roads Layer Source: Ministerio de Agricultura, Ganaderia y Alimentacion (Jun 2001) Description: National and regional road network of Bangladesh, and the feeder type A roads (roads connecting Thana HQ with the existing road network). Spatial Resolution: 1:250,000

Transmission Lines Linestring Guatemala NREL 2001 (nrel:gstk_guatemala_44_transmissionline)

Guatemala Transmission Lines Layer Source: Ministerio de Agricultura, Ganaderia y Alimentacion (Jun 2001) Description: Electric power transmission lines of Guatemala. Spatial Resolution: 1:250,000

Airports Point Guatemala NREL 2001 (nrel:gstk_guatemala_53_airports)

Guatemala Airports Layer Source: Ministerio de Agricultura, Ganaderia y Alimentacion (Jun 2001) Description: Airport locations in Guatemala. Spatial Resolution: 1:250,000

Cities Point Guatemala NREL 2001 (nrel:gstk_guatemala_59_cities)

Guatemala Cities Layer Source: Ministerio de Agricultura, Ganaderia y Alimentacion (Jun 2001) Description: Populated places in Guatemala Spatial Resolution: 1:250,000

Elevation Multipolygon Hebei NREL 1993 (nrel:gstk_hebei_01_elevation)

Hebei Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Hebei NREL 1993 (nrel:gstk_hebei_02_landuse)

Hebei Landuse Layer Source: U.S. Geological Survey Global Land Use/Land Cover dataset (1993) Description: Land use/land cover categories, using the U.S. Geological Survey Modified Level 2 legend. Spatial Resolution: 1 km.

Direct Solar Multipolygon Hebei NREL 2004 (nrel:gstk_hebei_11_solar_direct)

Hebei Direct Solar Layer Source: National Renewable Energy Laboratory (NREL) Climatological Solar Radiation Model (2004) Description: Direct normal solar resource, annual average and monthly values. Data were developed using NREL's Climatological Solar Radiation model, using information on cloud cover, atmospheric water vapor and trace gases, and atmospheric aerosols falling on a horizontal surface. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties of the model. Spatial Resolution: 40 km

Tilt Solar Multipolygon Hebei NREL 2004 (nrel:gstk_hebei_12_solar_tilt)

Hebei Tilt Solar Layer Source: National Renewable Energy Laboratory (NREL) Climatological Solar Radiation Model (2004) Description: Solar resource for a flat plate collector tilted towards the equation with a fixed tilt equal to the latitude, annual average and monthly values. Data were developed using NREL's Climatological Solar Radiation model, using information on cloud cover, atmospheric water vapor and trace gases, and atmospheric aerosols falling on a horizontal surface. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties of the model. Spatial Resolution: 40 km

Wind Resource Multipolygon Hebei NREL 2005 (nrel:gstk_hebei_20_wind)

Hebei Wind Resource Layer Source: National Renewable Energy Laboratory (NREL) and AWS Truepower (2005) Description: Annual mean wind power density (W/m2) at 50 m height above ground level. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Spatial Resolution: 1 km

Protected Areas Multipolygon Hebei NREL 2005 (nrel:gstk_hebei_31_protectedarea)

Hebei Protected Areas Layer Source: World Database on Protected Areas Consortium, copyright World Conservation Union (IUCN) and UNEP-World Conservation Monitoring Centre (UNEP-WCMC) (2005) Description: Database of protected areas of IUCN categories I through VI, other protected areas and areas defined under international agreements. Spatial Resolution: Varied, compiled from multiple sources

Country Boundary Multipolygon Hebei NREL 1998 (nrel:gstk_hebei_39_countryboundary)

Hebei Country Boundary Layer Source: ESRI ArcWorld Supplement (1998) Description: Second level internal administrative boundaries. Spatial Resolution: 1:3,000,000

Rivers Multilinestring Hebei NREL 1998 (nrel:gstk_hebei_40_rivers)

Hebei Rivers Layer Source: ESRI ArcWorld (1998) Description: Major rivers. Spatial Resolution: 1:3,000,000

Railroads Multilinestring Hebei NREL 1998 (nrel:gstk_hebei_42_railroad)

Hebei Railroads Layer Source: ESRI ArcWorld (1998) Description: Major rail lines of Hebei Spatial Resolution: 1:3,000,000

Roads Multilinestring Hebei NREL 1998 (nrel:gstk_hebei_43_roads)

Hebei Roads Layer Source: ESRI ArcWorld (1998) Description: National and regional road network of Hebei Spatial Resolution: 1:3,000,000

Transmission Lines Multilinestring Hebei NREL (nrel:gstk_hebei_44_transmissionline)

Hebei Transmission Lines Layer Source: Unknown Description: Electric power transmission lines of Hebei. Spatial Resolution: Unknown

Airports Point Hebei NREL 1998 (nrel:gstk_hebei_53_airports)

Hebei Airports Layer Source: ESRI ArcWorld (1998) Description: Airport locations in Hebei. Spatial Resolution: 1:3,000,000

Cities Point Hebei NREL 1998 (nrel:gstk_hebei_59_cities)

Hebei Cities Layer Source: ESRI ArcWorld (1998) Description: Populated places in Hebei Spatial Resolution: 1:3,000,000

Elevation Multipolygon Honduras NREL 1993 (nrel:gstk_honduras_01_elevation)

Honduras Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Honduras NREL 2003 (nrel:gstk_honduras_02_landuse)

Honduras Landuse Layer Source: Oficina de Electrification Social (received Aug 2003) Description: Land use/land cover categories Spatial Resolution: Unknown

Tilt Solar Multipolygon Honduras NREL 2004 (nrel:gstk_honduras_12_solar_tilt)

Honduras Tilt Solar Layer Source: National Renewable Energy Laboratory (NREL) Climatological Solar Radiation Model (2004) Description: Solar resource for a flat plate collector tilted towards the equation with a fixed tilt equal to the latitude, annual average and monthly values. Data were developed using NREL's Climatological Solar Radiation model, using information on cloud cover, atmospheric water vapor and trace gases, and atmospheric aerosols falling on a horizontal surface. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties of the model. Spatial Resolution: 40 km

Direct Solar Multipolygon Honduras NREL 2005 (nrel:gstk_honduras_13_solar_direct)

Honduras Direct Solar Layer Source: State University of New York - Perez Model(2005) Description: Direct normal irradiance (DNI) averaged annually and monthly for the years 1998-2002. Spatial Resolution: 0.1 degrees (nominally 10 km)

Global Solar Multipolygon Honduras NREL 2005 (nrel:gstk_honduras_14_solar_glo)

Honduras Global Solar Layer Source: State University of New York - Perez Model(2005) Description: Global horizontal irradiance (GHI) averaged annually and monthly for the years 1998-2002. Spatial Resolution: 0.1 degrees (nominally 10 km)

Wind Resource Multipolygon Honduras NREL 2004 (nrel:gstk_honduras_20_wind)

Honduras Wind Resource Layer Source: National Renewable Energy Laboratory (NREL) and AWS Truepower (2004) Description: Annual mean wind power density (W/m2) at 50 m height above ground level. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Spatial Resolution: 1 km

Protected Areas Multipolygon Honduras NREL 2003 (nrel:gstk_honduras_31_protectedarea)

Honduras Protected Areas Layer Source: Oficina de Electrification Social (received Aug 2003) Description: Database of protected areas within Honduras Spatial Resolution: Unknown

Country Boundary Polygon Honduras NREL 2003 (nrel:gstk_honduras_39_countryboundary)

Honduras Country Boundary Layer Source: Oficina de Electrification Social (received Aug 2003) Description: Country level administrative boundaries. Spatial Resolution: Unknown

Rivers Multilinestring Honduras NREL 2003 (nrel:gstk_honduras_40_rivers)

Honduras Rivers Layer Source: Oficina de Electrification Social (received Aug 2003) Description: Major rivers. Spatial Resolution: Unknown

Railroads Linestring Honduras NREL 2003 (nrel:gstk_honduras_42_railroad)

Honduras Railroads Layer Source: Oficina de Electrification Social (received Aug 2003) Description: Major rail lines of Honduras Spatial Resolution: Unknown

Roads Linestring Honduras NREL 2003 (nrel:gstk_honduras_43_roads)

Honduras Roads Layer Source: Oficina de Electrification Social (received Aug 2003) Description: National and regional road network of Honduras Spatial Resolution: Unknown

Transmission Lines Linestring Honduras NREL 2003 (nrel:gstk_honduras_44_transmissionline)

Honduras Transmission Lines Layer Source: Oficina de Electrification Social (received Aug 2003) Description: Electric power transmission lines of Honduras. Spatial Resolution: Unknown

Power Plants Point Honduras NREL 2003 (nrel:gstk_honduras_51_powerplant)

Honduras Power Plants Layer Source: Oficina de Electrification Social (received Aug 2003) Description: Power plants in Honduras. Spatial Resolution: Unknown

Airports Point Honduras NREL 2003 (nrel:gstk_honduras_53_airports)

Honduras Airports Layer Source: Oficina de Electrification Social (received Aug 2003) Description: Airport locations in Honduras. Spatial Resolution: Unknown

Cities Point Honduras NREL 2003 (nrel:gstk_honduras_59_cities)

Honduras Cities Layer Source: Oficina de Electrification Social (received Aug 2003) Description: Populated places in Honduras Spatial Resolution: Unknown

Elevation Multipolygon India NREL 1993 (nrel:gstk_india_01_elevation)

India Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon India NREL 1993 (nrel:gstk_india_02_landuse)

India Landuse Layer Source: U.S. Geological Survey Global Land Use/Land Cover dataset (1993) Description: Land use/land cover categories, using the U.S. Geological Survey Modified Level 2 legend. Spatial Resolution: 1 km.

Direct Solar Multipolygon India NREL 2010 (nrel:gstk_india_13_solar_direct)

India Direct Solar Layer Source: SUNY/Albany (2010) Description: Direct normal irradiance (DNI) averaged annually and monthly from April 2004 to March 2009. Spatial Resolution: 6 arc-minutes (nominally 10 km)

Global Solar Multipolygon India NREL 2010 (nrel:gstk_india_14_solar_glo)

India Global Solar Layer Source: SUNY/Albany (2010) Description: Global horizontal irradiance (GHI) averaged annually and monthly from April 2004 to March 2009. Spatial Resolution: 6 arc-minutes (nominally 10 km)

Lakes Polygon India NREL 2010 (nrel:gstk_india_30_lakes)

India Lakes Layer Source: Government of India, received 2010 Description: Major lakes of India. Spatial Resolution: Unknown

Protected Areas Multipolygon India NREL 2005 (nrel:gstk_india_31_protectedarea)

India Protected Areas Layer Source: World Database on Protected Areas Consortium, copyright World Conservation Union (IUCN) and UNEP-World Conservation Monitoring Centre (UNEP-WCMC) (2005) Description: Database of protected areas of IUCN categories I through VI, other protected areas and areas defined under international agreements. Spatial Resolution: Varied, compiled from multiple sources

State Boundaries Multipolygon India NREL 2010 (nrel:gstk_india_38_subcountrybnd1)

India State Boundaries Layer Source: Government of India, received 2010 Description: First level internal administrative boundaries. Spatial Resolution: Unknown

Country Boundary Multipolygon India NREL 2010 (nrel:gstk_india_39_countryboundary)

India Country Boundary Layer Source: Government of India, received 2010 Description: Country level administrative boundaries. Spatial Resolution: Unknown

Rivers Linestring India NREL 2010 (nrel:gstk_india_40_rivers)

India Rivers Layer Source: Government of India, received 2010 Description: Major rivers of India. Spatial Resolution: Unknown

Roads Multilinestring India NREL 2010 (nrel:gstk_india_43_roads)

India Roads Layer Source: Government of India, received 2010 Description: Major roads in India. Spatial Resolution: Unknown

Transmission Lines Multilinestring India NREL 2006 (nrel:gstk_india_44_transmissionline)

India Transmission Lines Layer Source: Power and Gas Grid Map of South Asia (2006) prepared for USAID under SARI/Energy program. Description: Electric power transmission lines of India. Spatial Resolution: Unknown

Power Plants Point India NREL 2010 (nrel:gstk_india_51_powerplant)

India Power Plants Layer Source: Government of India, received 2010 Description: Power plant locations in India. Spatial Resolution: Unknown

Cities Point India NREL 2010 (nrel:gstk_india_59_cities)

India Cities Layer Source: Government of India, received 2010 Description: Populated places in India. Spatial Resolution: Unknown

Elevation Multipolygon Indonesia NREL 1993 (nrel:gstk_indonesia_01_elevation)

Indonesia Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Indonesia NREL 2010 (nrel:gstk_indonesia_02_landuse)

Indonesia Landuse Layer Source: ESA & UCLouvain GlobCover dataset (2010) Description: Land use/land cover categories Spatial resolution: 0.3km

Tilt Solar Multipolygon Indonesia NREL 2008 (nrel:gstk_indonesia_12_solar_tilt)

Indonesia Tilt Solar Layer Source: NASA Surface Meteorology and Solar Energy Dataset (2008) Description: Solar resource for a fixed flat plat collector, facing the equator with a tilt equal to the cell's latitude, averaged annually and monthly. Spatial Resolution: ~100 km

Direct Solar Multipolygon Indonesia NREL 2008 (nrel:gstk_indonesia_13_solar_direct)

Indonesia Direct Solar Layer Source: NASA Surface Meteorology and Solar Energy Dataset (2008) Description: Direct normal irradiance (DNI) averaged annually and monthly. Spatial Resolution: ~100 km

Global Solar Multipolygon Indonesia NREL 2008 (nrel:gstk_indonesia_14_solar_glo)

Indonesia Global Solar Layer Source: NASA Surface Meteorology and Solar Energy Dataset (2008) Description: Global horizontal irradiance (GHI), averaged annually and monthly Spatial Resolution: ~100 km

Protected Areas Multipolygon Indonesia NREL 2005 (nrel:gstk_indonesia_31_protectedarea)

Indonesia Protected Areas Layer Source: World Database on Protected Areas Consortium, copyright World Conservation Union (IUCN) and UNEP-World Conservation Monitoring Centre (UNEP-WCMC) (2005) Description: Database of protected areas of IUCN categories I through VI, other protected areas and areas defined under international agreements. Spatial Resolution: Varied, compiled from multiple sources

District Boundaries Multipolygon Indonesia NREL (nrel:gstk_indonesia_37_subcountrybnd2)

Indonesia District Boundaries Layer Source: data provided by MCC-I Description: Second level internal administrative boundaries (district). Spatial Resolution: 1:250,000

Province Boundaries Multipolygon Indonesia NREL (nrel:gstk_indonesia_38_subcountrybnd1)

Indonesia Province Boundaries Layer Source: data provided by MCC-I Description: First level internal administrative boundaries (province). Spatial Resolution: 1:250,000

Country Boundary Multipolygon Indonesia NREL (nrel:gstk_indonesia_39_countryboundary)

Indonesia Country Boundary Layer Source: data provided by MCC-I Description: Country level administrative boundaries. Spatial Resolution: Unknown

Rivers Multilinestring Indonesia NREL 2008 (nrel:gstk_indonesia_40_rivers)

Indonesia Rivers Layer Source: ESRI Data & Maps, rivers (2008) Description: Major rivers. Spatial Reference: 1:15,000,000

Railroads Multilinestring Indonesia NREL 1992 (nrel:gstk_indonesia_42_railroads)

Indonesia Railroads Layer Source: Digital Chart of the World (1992) Description: Railroad lines. Spatial Resolution: 1:1,000,000

Roads Multilinestring Indonesia NREL 1992 (nrel:gstk_indonesia_43_roads)

Indonesia Roads Layer Source: Digital Chart of the World (1992) Description: Major road network. Spatial Resolution: 1:1,000,000

Power Plants Point Indonesia NREL (nrel:gstk_indonesia_51_powerplant)

Indonesia Power Plants Layer Source: Data from CARMA (www.carma.org) Description: Power plants. Spatial Resolution: Not stated.

Airports Point Indonesia NREL 1992 (nrel:gstk_indonesia_53_airports)

Indonesia Airports Layer Source: Digital Chart of the World (1992) Description: Airport locations. Spatial Resolution: 1:1,000,000

Cities Point Indonesia NREL 1992 (nrel:gstk_indonesia_59_cities)

Indonesia Cities Layer Source: Digital Chart of the World (1992) Description: Populated places Spatial Resolution: 1:1,000,000

Elevation Multipolygon Kenya NREL 1993 (nrel:gstk_kenya_01_elevation)

Kenya Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Kenya NREL 2013 (nrel:gstk_kenya_02_landuse)

Kenya Landuse Layer Source: MODIS satellite (2013) Description: Land use/land cover categories from the MODIS satellite. Spatial Resolution: 500m

Tilt Solar Multipolygon Kenya NREL 2004 (nrel:gstk_kenya_12_solar_tilt)

Kenya Tilt Solar Layer Source: National Renewable Energy Laboratory (NREL) Climatological Solar Radiation Model (2004) Description: Solar resource for a flat plate collector tilted towards the equation with a fixed tilt equal to the latitude, annual average and monthly values. Data were developed using NREL's Climatological Solar Radiation model, using information on cloud cover, atmospheric water vapor and trace gases, and atmospheric aerosols falling on a horizontal surface. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties of the model. Spatial Resolution: 40km

Direct Solar Multipolygon Kenya NREL 2004 (nrel:gstk_kenya_13_solar_direct)

Kenya Direct Solar Layer Source: Deutsches Zentrum für Luft- und Raumfahrt (DLR) (2004) Description: Data of high resolution (10kmx10km) Direct Normal Irradiance (DNI) for Kenya for the years 2000, 2001 and 2002. The data are available for monthly and annual sums stored in a ESRI-Shapefile. Spatial Resolution: 0.1 degrees (nominally 10 km)

Global Solar Multipolygon Kenya NREL 2004 (nrel:gstk_kenya_14_solar_glo)

Kenya Global Solar Layer Source: Deutsches Zentrum für Luft- und Raumfahrt (DLR) (2004) Description: Data of high resolution (10kmx10km) Global Horizontal Irradiance (GHI) for Kenya for the years 2000, 2001 and 2002. The data are available for monthly and annual sums stored in a ESRI-Shapefile. Spatial Resolution: 0.1 degrees (nominally 10 km)

Wind Speed Multipolygon Kenya NREL (nrel:gstk_kenya_20a_wind_speed_050)

Kenya Wind Speed Layer Source: Riso National Laboratory, DTU, Denmark. Description: Annual mean wind speed (m/s) at 50 meters above ground level. Spatial Resolution: 5 km

Wind Power Multipolygon Kenya NREL (nrel:gstk_kenya_20b_wind_power_050)

Kenya Wind Power Layer Source: Riso National Laboratory, DTU, Denmark. Description: Annual mean wind power density (W/m2) at 50 meters above ground level. Spatial Resolution: 5 km

Wind Offshore Resource Multipolygon Kenya NREL (nrel:gstk_kenya_21_windoffshore)

Kenya Wind Offshore Resource Layer Source: National Renewable Energy Laboratory Description: GIS data for offshore wind speed (meters/second). Specified to Exclusive Economic Zones (EEZ).Wind resource based on NOAA blended sea winds and monthly wind speed at 30km resolution, using a 0.11 wind sheer to extrapolate 10m - 90m. Annual average >= 10 months of data, no nulls. Spatial Resolution: 30km

Population Density Multipolygon Kenya NREL 2011 (nrel:gstk_kenya_29_popdensity)

Kenya Population Density Layer Source: Center for International Earth Science Information Network - CIESIN - Columbia University, International Food Policy Research Institute - IFPRI, The World Bank, and Centro Internacional de Agricultura Tropical - CIAT (2011) Description: The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated data sets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to assign population values (counts, in persons) to grid cells. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT). This data provides a time series of raster population density data for data integration. Spatial Resolution: Unknown

Lakes Multipolygon Kenya NREL 1992 (nrel:gstk_kenya_30_lakes)

Kenya Lakes Layer Source: Digital Chart of the World (1992) Description: Major water features. Spatial Resolution: 1:1,000,000

Protected Areas Multipolygon Kenya NREL 2005 (nrel:gstk_kenya_31_protectedarea)

Kenya Protected Areas Layer Source: World Database on Protected Areas Consortium, copyright World Conservation Union (IUCN) and UNEP-World Conservation Monitoring Centre (UNEP-WCMC) (2005) Description: Database of protected areas of IUCN categories I through VI, other protected areas and areas defined under international agreements. Spatial Resolution: Varied, compiled from multiple sources

Sub-Ward Boundary Multipolygon Kenya NREL 2011 (nrel:gstk_kenya_34_subcountrybnd5)

Kenya Sub-Ward Boundary Layer Source: Data were extracted from the Global Administrative Areas (GADM)database, version 2.0 (http://www.gadm.org) (2011) Description: Sub-Ward level administrative boundaries. Spatial Resolution: Unknown

Ward Boundary Multipolygon Kenya NREL 2011 (nrel:gstk_kenya_35_subcountrybnd4)

Kenya Ward Boundary Layer Source: Data were extracted from the Global Administrative Areas (GADM)database, version 2.0 (http://www.gadm.org) (2011) Description: Ward level administrative boundaries. Spatial Resolution: Unknown

Constituency Boundaries Multipolygon Kenya NREL 2011 (nrel:gstk_kenya_36_subcountrybnd3)

Kenya Constituency Boundaries Layer Source: Data were extracted from the Global Administrative Areas (GADM)database, version 2.0 (http://www.gadm.org) (2011) Description: Constituency level administrative boundaries. Spatial Resolution: Unknown

County Boundaries Multipolygon Kenya NREL 2011 (nrel:gstk_kenya_37_subcountrybnd2)

Kenya County Boundaries Layer Source: Data were extracted from the Global Administrative Areas (GADM)database, version 2.0 (http://www.gadm.org) (2011) Description: County level administrative boundaries. Spatial Resolution: Unknown

Province Boundaries Multipolygon Kenya NREL 2011 (nrel:gstk_kenya_38_subcountrybnd1)

Kenya Province Boundaries Layer Source: Data were extracted from the Global Administrative Areas (GADM)database, version 2.0 (http://www.gadm.org) (2011) Description: Province level administrative boundaries. Spatial Resolution: Unknown

Country Boundary Multipolygon Kenya NREL 2011 (nrel:gstk_kenya_39_countryboundary)

Kenya Country Boundary Layer Source: Data were extracted from the Global Administrative Areas (GADM)database, version 2.0 (http://www.gadm.org) (2011) Description: Country level administrative boundaries. Spatial Resolution: Unknown

Rivers Multilinestring Kenya NREL 1992 (nrel:gstk_kenya_40_rivers)

Kenya Rivers Layer Source: Digital Chart of the World (1992) Description: Major rivers. Spatial Resolution: 1:1,000,000

Railroads Multilinestring Kenya NREL 1992 (nrel:gstk_kenya_42_railroads)

Kenya Railroads Layer Source: Digital Chart of the World (1992) Description: Major rail lines. Spatial Resolution: 1:1,000,000

Roads Multilinestring Kenya NREL 2005 (nrel:gstk_kenya_43_roads)

Kenya Roads Layer Source: Data were compiled by Africon Limited under contract for the AICD study led by the World Bank. Data were obtained from the Kenya Roads Board (KRB) and pertain to December 2005. Description: Data on road surface type, condition and traffic volume were compiled by Africon Limited for the AICD study led by the World Bank. Data from the Kenya Roads Board (KRB) were reviewed and transport experts were consulted in an effort to derive estimates for all of the primary and secondary road network. The following attributes were collected: LINKNO: ID of the link , ROADNO: ID of the road , STARTKM: Start of link (0) ENDKM: End of link LENGTHKM: Length of link (km) , STARTDESC: Name of the locality where the link starts , ENDDESC: Name of the locality where the link finishes , ROADCLASS: Local classification CLASS: World Bank functional classification , REGION: Name of the 1st level of administrative division (province) , WIDTH: Width of road (m) , LANES: Number of lanes , TYPE: Description of surface type , SURFTYPE: Classification of surface type (paved or unpaved) , CONDITION: Description of road condition , AADT: Estimated average annual daily traffic Attribute values may be unknown (or value = 0) for any of the descriptive characteristics. Spatial Resolution: Unknown

Transmission Lines Multilinestring Kenya NREL (nrel:gstk_kenya_44_transmissionline)

Kenya Transmission Lines Layer Source: A variety of sources were consulted, including documents and maps from national utilities, regional power pools and the World Bank. Description: Data for medium and high voltage transmission lines were compiled for the AICD study led by the World Bank. A variety of sources were consulted, including regional power pool documents and maps from World Bank project documents. Locations are approximate, intended to reflect main connections, and are not representative of actual path on the ground. The following attributes were collected: VOLTAGE_KV: Transmission line capacity in kilovolts, FROM_NM: Name of the locality where the link starts, TO_NM: Name of the locality where the link ends, STATUS: Status of link (Existing, Planned, Proposed, Under Study), SOURCES: Source of location or attribute information, PROJECT_NM: Name of project (planned links). Spatial Resolution: Unknown

Logging Residues Multipolygon Kenya NREL 2000 (nrel:gstk_kenya_46_forestresidues)

Kenya Logging Residues Layer Source: World Resources Institute (2000) Description: Logging residues from industrial wood plantations. This data illustrated the amoutn of logging residues generated at industrial tree plantations in Kenya. The tree plantations' location and area are based on estimates by FAO in 2000 and distributed by the World Resources Institute. The analysis assumes that on average, wood yield is about 7m3/ha/yr and that logging residues represent 40% of timber harvesting. Conversion to tonnes assumes 0.5t/m3. Spatial Resolution: Unknown

Active Geothermal Areas Multipolygon Kenya NREL (nrel:gstk_kenya_47_geothbasins)

Kenya Active Geothermal Areas Layer Source: Geothermal Development Company (GDC) of Kenya Description: Active and prospective geothermal resource areas. Spatial Resolution: Unknown

Power Plants Point Kenya NREL (nrel:gstk_kenya_51_powerplant)

Kenya Power Plants Layer Source: Data from the Platts World Electric Power Plants Database were georeferenced using auxiliary GIS datasets, documents and maps from national utilities, regional power pools and the World Bank. Description: Data for power plants with total installed generating capacity > 10 mw. Spatial Resolution: Unknown

Airports Point Kenya NREL 1992 (nrel:gstk_kenya_53_airports)

Kenya Airports Layer Source: Digital Chart of the World (1992) Description: Airport locations. Spatial Resolution: 1:1,000,000

Geothermal Drilling Locations Point Kenya NREL (nrel:gstk_kenya_55_geoth)

Kenya Geothermal Drilling Locations Layer Source: Geothermal Development Company (GDC) of Kenya Description: Geothermal drilling locations within Menengai Crater geothermal area digitized from Geothermal Development Company map. Spatial Resolution: Unknown

Sugar Factories Co-Generation Point Kenya NREL 2013 (nrel:gstk_kenya_57_sugarfac_cogen)

Kenya Sugar Factories Co-Generation Layer Source: Baseline Study for Sugar Agribusiness in Kenya by Kenana Engineering and Technical Service Co. Ltd. (2013) Description: Sugar factories co-generation capacity. The location of sugar factories in Kenya and their co-generation capacity. Information about existing, under construction, and planned power generation capacity at sugar factories was gathered from companies web sites and media releases. Estimated power generation capacity assumes that for every tonne of cane crushed, about 100 kWh are produced. Conversion to MW assumes that sugar plants in kenya operate 7,128 hours annually. Spatial Resolution: Unknown

Cities Point Kenya NREL 2011 (nrel:gstk_kenya_59_cities)

Kenya Cities Layer Source: Center for International Earth Science Information Network - CIESIN - Columbia University, International Food Policy Research Institute - IFPRI, The World Bank, and Centro Internacional de Agricultura Tropical - CIAT (2011) Description: The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated data sets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to assign population values (counts, in persons) to grid cells. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).This data provides populated place (point) data with consistent population estimates. Spatial Resolution: Unknown

Elevation Multipolygon Malaysia NREL 1993 (nrel:gstk_malaysia_01_elevation)

Malaysia Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Malaysia NREL 2010 (nrel:gstk_malaysia_02_landuse)

Malaysia Landuse Layer Source: ESA & UCLouvain GlobCover dataset (2010) Description: Land use/land cover categories Spatial resolution: 0.3km

Tilt Solar Multipolygon Malaysia NREL 2008 (nrel:gstk_malaysia_12_solar_tilt)

Malaysia Tilt Solar Layer Source: NASA Surface Meteorology and Solar Energy Dataset (2008) Description: Solar resource for a fixed flat plat collector, facing the equator with a tilt equal to the cell's latitude, averaged annually and monthly. Spatial Resolution: ~100 km

Direct Solar Multipolygon Malaysia NREL 2008 (nrel:gstk_malaysia_13_solar_direct)

Malaysia Direct Solar Layer Source: NASA Surface Meteorology and Solar Energy Dataset (2008) Description: Direct normal irradiance (DNI) averaged annually and monthly. Spatial Resolution: ~100 km

Global Solar Multipolygon Malaysia NREL 2008 (nrel:gstk_malaysia_14_solar_glo)

Malaysia Global Solar Layer Source: NASA Surface Meteorology and Solar Energy Dataset (2008) Description: Global horizontal irradiance (GHI), averaged annually and monthly Spatial Resolution: ~100 km

Protected Areas Multipolygon Malaysia NREL 2005 (nrel:gstk_malaysia_31_protectedarea)

Malaysia Protected Areas Layer Source: World Database on Protected Areas Consortium, copyright World Conservation Union (IUCN) and UNEP-World Conservation Monitoring Centre (UNEP-WCMC) (2005) Description: Database of protected areas of IUCN categories I through VI, other protected areas and areas defined under international agreements. Spatial Resolution: Varied, compiled from multiple sources

District Boundaries Multipolygon Malaysia NREL 2012 (nrel:gstk_malaysia_37_subcountrybnd2)

Malaysia District Boundaries Layer Source: Global Administrative Areas (GADM) dataset (2012) Description: District level administrative boundaries. Spatial Resolution: Not Stated

Province Boundaries Multipolygon Malaysia NREL 2012 (nrel:gstk_malaysia_38_subcountrybnd1)

Malaysia Province Boundaries Layer Source: Global Administrative Areas (GADM) dataset (2012) Description: Province level administrative boundaries. Spatial Resolution: Not Stated

Country Boundary Multipolygon Malaysia NREL 2012 (nrel:gstk_malaysia_39_countryboundary)

Malaysia Country Boundary Layer Source: Global Administrative Areas (GADM) dataset (2012) Description: Country level administrative boundaries. Spatial Resolution: Not Stated

Rivers Multilinestring Malaysia NREL 2008 (nrel:gstk_malaysia_40_rivers)

Malaysia Major Rivers Layer Source: ESRI Data & Maps, rivers (2008) Description: Major rivers. Spatial resolution: 1:15,000,000

Railroads Multilinestring Malaysia NREL 1992 (nrel:gstk_malaysia_42_railroads)

Malaysia Railroads Layer Source: Digital Chart of the World (1992) Description: Railroad lines. Spatial Resolution: 1:1,000,000

Roads Multilinestring Malaysia NREL 1992 (nrel:gstk_malaysia_43_roads)

Malaysia Roads Layer Source: Digital Chart of the World (1992) Description: Major road network. Spatial Resolution: 1:1,000,000

Power Plants Point Malaysia NREL (nrel:gstk_malaysia_51_powerplant)

Malaysia Power Plants Layer Source: Data from CARMA (www.carma.org) Description: Power plants. Spatial Resolution: Not stated.

Airports Point Malaysia NREL 1992 (nrel:gstk_malaysia_53_airports)

Malaysia Airports Layer Source: Digital Chart of the World (1992) Description: Airport locations. Spatial Resolution: 1:1,000,000

Cities Point Malaysia NREL 1992 (nrel:gstk_malaysia_59_cities)

Malaysia Cities Layer Source: Digital Chart of the World (1992) Description: Populated places Spatial Resolution: 1:1,000,000

Elevation Multipolygon Nepal NREL 1993 (nrel:gstk_nepal_01_elevation)

Nepal Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Nepal NREL 1993 (nrel:gstk_nepal_02_landuse)

Nepal Landuse Layer Source: U.S. Geological Survey Global Land Use/Land Cover dataset (1993) Description: Land use/land cover categories, using the U.S. Geological Survey Modified Level 2 legend. Spatial Resolution: 1 km.

Solar Tilt Multipolygon Nepal NREL 2005 (nrel:gstk_nepal_12_solar_tilt)

Nepal Solar Tilt Layer Source: National Renewable Energy Laboratory (2005) Description: Solar resource for a flat plate collector tilted towards the equation with a fixed tilt equal to the latitude, annual average and monthly values. Data were developed using NREL's Climatological Solar Radiation model, using information on cloud cover, atmospheric water vapor and trace gases, and atmospheric aerosols falling on a horizontal surface. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties of the model. Spatial Resolution: 40 km

Direct Solar Multipolygon Nepal NREL 2004 (nrel:gstk_nepal_13_solar_direct)

Nepal Direct Solar Layer Source: Deutsches Zentrum für Luft- und Raumfahrt (DLR) (2004) Description: Direct normal irradiance (DNI) averaged annually and monthly for the years 2000, 2002, and 2003. Spatial Resolution: 0.1 degrees (nominally 10 km)

Global Solar Multipolygon Nepal NREL 2004 (nrel:gstk_nepal_14_solar_glo)

Nepal Global Solar Layer Source: Deutsches Zentrum für Luft- und Raumfahrt (DLR) (2004) Description: Global horizontal irradiance (GHI) averaged annually and monthly for the years 2000, 2002, and 2003. Spatial Resolution: 0.1 degrees (nominally 10 km)

Wind Resource Polygon Nepal NREL 2008 (nrel:gstk_nepal_20_wind)

Nepal Wind Resource Layer Source: Risø Technical University of Denmark (Risø DTU) (2008) Description: Simulated annual mean wind power density (W/m2).at 50 m height above ground level as described in the mesoscale model. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Spatial Resolution: 5 km

Lakes Multipolygon Nepal NREL (nrel:gstk_nepal_30_lakes)

Nepal Lakes Layer Source: Nepal Alternative Energy Promostion Centre - Energy Sector Assistance Programme Description: Spatial Resolution: Unknown

Protected Areas Polygon Nepal NREL 2005 (nrel:gstk_nepal_31_protectedarea)

Nepal Protected Areas Layer Source: World Database on Protected Areas Consortium, copyright World Conservation Union (IUCN) and UNEP-World Conservation Monitoring Centre (UNEP-WCMC) (2005) Description: Database of protected areas of IUCN categories I through VI, other protected areas and areas defined under international agreements. Spatial Resolution: Varied, compiled from multiple sources

State Boundaries Polygon Nepal NREL (nrel:gstk_nepal_38_subcountrybnd1)

Nepal State Boundaries Layer Source: Nepal Alternative Energy Promostion Centre - Energy Sector Assistance Programme Description: First level internal administrative boundaries. Spatial Resolution: Unknown

Country Boundary Polygon Nepal NREL (nrel:gstk_nepal_39_countryboundary)

Nepal Country Boundary Layer Source: Nepal Alternative Energy Promostion Centre - Energy Sector Assistance Programme Description: Country level administrative boundaries. Spatial Resolution: Unknown

Rivers Multilinestring Nepal NREL (nrel:gstk_nepal_40_rivers)

Nepal Rivers Layer Source: Nepal Alternative Energy Promostion Centre - Energy Sector Assistance Programme Description: Major rivers of Nepal. Spatial Resolution: Unknown

Roads Multilinestring Nepal NREL (nrel:gstk_nepal_43_roads)

Nepal Roads Layer Source: Nepal Alternative Energy Promostion Centre - Energy Sector Assistance Programme Description: Major roads of Nepal. Spatial Resolution: Unknown

Transmission Lines Linestring Nepal NREL (nrel:gstk_nepal_44_transmissionline)

Nepal Transmission Lines Layer Source: Nepal Alternative Energy Promostion Centre - Energy Sector Assistance Programme Description: Electric transmission lines in Nepal. Spatial Resolution: Unknown

Power Plants Point Nepal NREL (nrel:gstk_nepal_51_powerplant)

Nepal Power Plants Layer Source: Nepal Alternative Energy Promostion Centre - Energy Sector Assistance Programme Description: Major power plants. Spatial Resolution: Unknown

Cities Point Nepal NREL (nrel:gstk_nepal_59_cities)

Nepal Cities Layer Source: Nepal Alternative Energy Promostion Centre - Energy Sector Assistance Programme Description: Populated places in Nepal. Spatial Resolution: Unknown

Elevation Multipolygon Nicaragua NREL 1993 (nrel:gstk_nicaragua_01_elevation)

Nicaragua Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Nicaragua NREL 2004 (nrel:gstk_nicaragua_02_landuse)

Nicaragua Landuse Layer Source: Comision Nacional de Energia (received Mar 2004) Description: Land use/land cover categories Spatial Resolution: Unknown

Tilt Solar Multipolygon Nicaragua NREL 2004 (nrel:gstk_nicaragua_12_solar_tilt)

Nicaragua Tilt Solar Layer Source: National Renewable Energy Laboratory (NREL) Climatological Solar Radiation Model (2004) Description: Solar resource for a flat plate collector tilted towards the equation with a fixed tilt equal to the latitude, annual average and monthly values. Data were developed using NREL's Climatological Solar Radiation model, using information on cloud cover, atmospheric water vapor and trace gases, and atmospheric aerosols falling on a horizontal surface. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties of the model. Spatial Resolution: 40 km

Direct Solar Multipolygon Nicaragua NREL 2005 (nrel:gstk_nicaragua_13_solar_direct)

Nicaragua Direct Solar Layer Source: State University of New York - Perez Model(2005) Description: Direct normal irradiance (DNI) averaged annually and monthly for the years 1998-2002. Spatial Resolution: 0.1 degrees (nominally 10 km)

Global Solar Multipolygon Nicaragua NREL 2005 (nrel:gstk_nicaragua_14_solar_glo)

Nicaragua Global Solar Layer Source: State University of New York - Perez Model(2005) Description: Global horizontal irradiance (GHI) averaged annually and monthly for the years 1998-2002. Spatial Resolution: 0.1 degrees (nominally 10 km)

Wind Resource Multipolygon Nicaragua NREL 2004 (nrel:gstk_nicaragua_20_wind)

Nicaragua Wind Resource Layer Source: National Renewable Energy Laboratory (NREL) and AWS Truepower (2004) Description: Annual mean wind power density (W/m2) at 50 m height above ground level. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Spatial Resolution: 1 km

Lakes Polygon Nicaragua NREL 2004 (nrel:gstk_nicaragua_30_lakes)

Nicaragua Lakes Layer Source: Comision Nacional de Energia (received Mar 2004) Description: Lakes and lagoons of Nicaragua Spatial Resolution: Unknown

Protected Areas Multipolygon Nicaragua NREL 2004 (nrel:gstk_nicaragua_31_protectedarea)

Nicaragua Protected Areas Layer Source: Comision Nacional de Energia (received Mar 2004) Description: Database of protected areas within Nicaragua Spatial Resolution: Unknown

Country Boundary Multipolygon Nicaragua NREL 2004 (nrel:gstk_nicaragua_39_countryboundary)

Nicaragua Country Boundary Layer Source: Comision Nacional de Energia (received Mar 2004) Description: Country level administrative boundaries. Spatial Resolution: Unknown

Rivers Linestring Nicaragua NREL 2004 (nrel:gstk_nicaragua_40_rivers)

Nicaragua Rivers Layer Source: Comision Nacional de Energia (received Mar 2004) Description: Major rivers. Spatial Resolution: Unknown

Railroads Linestring Nicaragua NREL 2004 (nrel:gstk_nicaragua_42_railroad)

Nicaragua Railroads Layer Source: Comision Nacional de Energia (received Mar 2004) Description: Major rail lines of Nicaragua Spatial Resolution: Unknown

Roads Linestring Nicaragua NREL 2004 (nrel:gstk_nicaragua_43_roads)

Nicaragua Roads Layer Source: Comision Nacional de Energia (received Mar 2004) Description: National and regional road network of Spatial Resolution: Unknown

Transmission Lines Multilinestring Nicaragua NREL 2004 (nrel:gstk_nicaragua_44_transmissionline)

Nicaragua Transmission Lines Layer Source: Comision Nacional de Energia (received Mar 2004) Description: Electric power transmission lines of Nicaragua. Spatial Resolution: Unknown

Airports Point Nicaragua NREL 2004 (nrel:gstk_nicaragua_53_airports)

Nicaragua Airports Layer Source: Comision Nacional de Energia (received Mar 2004) Description: Airport locations in Nicaragua. Spatial Resolution: Unknown

Cities Point Nicaragua NREL 2004 (nrel:gstk_nicaragua_59_cities)

Nicaragua Cities Layer Source: Comision Nacional de Energia (received Mar 2004) Description: Populated places in Nicaragua Spatial Resolution: Unknown

Elevation Multipolygon Oaxaca NREL 1993 (nrel:gstk_oaxaca_01_elevation)

Oaxaca Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Oaxaca NREL 2003 (nrel:gstk_oaxaca_02_landuse)

Oaxaca Landuse Layer Source: Instituto de Investigaciones Electricas (received April 2003) Description: Land use/land cover categories Spatial Resolution: Unknown

Tilt Solar Multipolygon Oaxaca NREL 2004 (nrel:gstk_oaxaca_12_solar_tilt)

Oaxaca Tilt Solar Layer Source: National Renewable Energy Laboratory (NREL) Climatological Solar Radiation Model (2004) Description: Solar resource for a flat plate collector tilted towards the equation with a fixed tilt equal to the latitude, annual average and monthly values. Data were developed using NREL's Climatological Solar Radiation model, using information on cloud cover, atmospheric water vapor and trace gases, and atmospheric aerosols falling on a horizontal surface. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties of the model. Spatial Resolution: 40 km

Direct Solar Multipolygon Oaxaca NREL 2005 (nrel:gstk_oaxaca_13_solar_direct)

Oaxaca Direct Solar Layer Source: State University of New York - Perez Model(2005) Description: Direct normal irradiance (DNI) averaged annually and monthly for the years 1998-2002. Spatial Resolution: 0.1 degrees (nominally 10 km)

Global Solar Multipolygon Oaxaca NREL 2005 (nrel:gstk_oaxaca_14_solar_glo)

Oaxaca Global Solar Layer Source: State University of New York - Perez Model(2005) Description: Global horizontal irradiance (GHI) averaged annually and monthly for the years 1998-2002. Spatial Resolution: 0.1 degrees (nominally 10 km)

Wind Resource Multipolygon Oaxaca NREL 2003 (nrel:gstk_oaxaca_20_wind)

Oaxaca Wind Resource Layer Source: National Renewable Energy Laboratory (NREL) and AWS Truepower (2003) Description: Annual mean wind power density (W/m2) at 50 m height above ground level. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Spatial Resolution: 400 m

Lakes Polygon Oaxaca NREL 2003 (nrel:gstk_oaxaca_30_lakes)

Oaxaca Lakes Layer Source: Instituto de Investigaciones Electricas (received April 2003) Description: Lakes and lagoons of Oaxaca Spatial Resolution: Unknown

Protected Areas Multipolygon Oaxaca NREL 2003 (nrel:gstk_oaxaca_31_protectedarea)

Oaxaca Protected Areas Layer Source: Instituto de Investigaciones Electricas (received April 2003) Description: Database of protected areas within Oaxaca Spatial Resolution: Unknown

Country Boundary Multipolygon Oaxaca NREL 2003 (nrel:gstk_oaxaca_39_countryboundary)

Oaxaca Country Boundary Layer Source: Instituto de Investigaciones Electricas (received April 2003) Description: Country level administrative boundaries. Spatial Resolution: Unknown

Rivers Linestring Oaxaca NREL 2003 (nrel:gstk_oaxaca_40_rivers)

Oaxaca Rivers Layer Source: Instituto de Investigaciones Electricas (received April 2003) Description: Major rivers. Spatial Resolution: Unknown

Railroads Linestring Oaxaca NREL 2003 (nrel:gstk_oaxaca_42_railroad)

Oaxaca Railroads Layer Source: Instituto de Investigaciones Electricas (received April 2003) Description: Major rail lines of Oaxaca Spatial Resolution: Unknown

Roads Linestring Oaxaca NREL 2003 (nrel:gstk_oaxaca_43_roads)

Oaxaca Roads Layer Source: Instituto de Investigaciones Electricas (received April 2003) Description: National and regional road network of Oaxaca Spatial Resolution: Unknown

Transmission Lines Linestring Oaxaca NREL 2003 (nrel:gstk_oaxaca_44_transmissionline)

Oaxaca Transmission Lines Layer Source: Instituto de Investigaciones Electricas (received April 2003) Description: Electric power transmission lines of Oaxaca. Spatial Resolution: Unknown

Airports Point Oaxaca NREL 2003 (nrel:gstk_oaxaca_53_airports)

Oaxaca Airports Layer Source: Instituto de Investigaciones Electricas (received April 2003) Description: Airport locations in Oaxaca. Spatial Resolution: Unknown

Cities Point Oaxaca NREL 2003 (nrel:gstk_oaxaca_59_cities)

Oaxaca Cities Layer Source: Instituto de Investigaciones Electricas (received April 2003) Description: Populated places in Oaxaca Spatial Resolution: Unknown

Elevation Multipolygon Pakistan NREL 1993 (nrel:gstk_pakistan_01_elevation)

Pakistan Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Pakistan NREL 1993 (nrel:gstk_pakistan_02_landuse)

Pakistan Landuse Layer Source: U.S. Geological Survey Global Land Use/Land Cover dataset (1993) Description: Land use/land cover categories, using the U.S. Geological Survey Modified Level 2 legend. Spatial Resolution: 1 km.

Solar Tilt Multipolygon Pakistan NREL (nrel:gstk_pakistan_12_solar_tilt)

Pakistan Solar Tilt Layer Source: Metadata Not Available Description: Metadata Not Available Spatial Resolution: Metadata Not Available

Direct Solar Multipolygon Pakistan NREL 2008 (nrel:gstk_pakistan_13_solar_direct)

Pakistan Direct Solar Layer Source: State University of New York - Perez Model(2008) Description: Direct normal irradiance (DNI) averaged annually and monthly for the period April 2002 - Sept 2005. Spatial Resolution: 0.1 degrees (nominally 10 km)

Global Solar Multipolygon Pakistan NREL 2008 (nrel:gstk_pakistan_14_solar_glo)

Pakistan Global Solar Layer Source: State University of New York - Perez Model(2008) Description: Global horizontal irradiance (GHI) averaged annually and monthly for the period April 2002 - Sept 2005. Spatial Resolution: 0.1 degrees (nominally 10 km)

Wind Resource Polygon Pakistan NREL 2007 (nrel:gstk_pakistan_20_wind)

Pakistan Wind Resource Layer Source: National Renewable Energy Laboratory (NREL) and AWS Truepower (2007) Description: Annual mean wind power density (W/m2) at 50 m height above ground level. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Spatial Resolution: 1 km

Protected Areas Multipolygon Pakistan NREL 2005 (nrel:gstk_pakistan_31_protectedarea)

Pakistan Protected Areas Layer Source: World Database on Protected Areas Consortium, copyright World Conservation Union (IUCN) and UNEP-World Conservation Monitoring Centre (UNEP-WCMC) (2005) Description: Database of protected areas of IUCN categories I through VI, other protected areas and areas defined under international agreements. Spatial Resolution: Varied, compiled from multiple sources

State Boundaries Polygon Pakistan NREL 2008 (nrel:gstk_pakistan_38_subcountrybnd1)

Pakistan State Boundaries Layer Source: ESRI Data & Maps, cntry08 (2008) Description: First level internal administrative boundaries. Spatial resolution: 1:15,000,000

Country Boundary Polygon Pakistan NREL 2008 (nrel:gstk_pakistan_39_countryboundary)

Pakistan Country Boundary Layer Source: ESRI Data & Maps, admin (2008) Description: Country level administrative boundaries Spatial resolution: 1:15,000,000

Rivers Multilinestring Pakistan NREL 2008 (nrel:gstk_pakistan_40_rivers)

Pakistan Rivers Layer Source: ESRI Data & Maps, rivers (2008) Description: Major rivers. Spatial resolution: 1:15,000,000

Railroads Linestring Pakistan NREL 1992 (nrel:gstk_pakistan_42_railroad)

Pakistan Railroads Layer Source: Digital Chart of the World (1992) Description: Railroad lines. Spatial Resolution: 1:1,000,000

Roads Multilinestring Pakistan NREL 1992 (nrel:gstk_pakistan_43_roads)

Pakistan Roads Layer Source: Digital Chart of the World (1992) Description: Major road network. Spatial Resolution: 1:1,000,000

Transmission Lines Linestring Pakistan NREL 2006 (nrel:gstk_pakistan_44_transmissionline)

Pakistan Transmission Lines Layer Source: digitized from Power and Gas Grid Map of South Asia (2006) Description: Utility electric transmission lines. Spatial Resolution: Not stated.

Power Plants Point Pakistan NREL 2006 (nrel:gstk_pakistan_51_powerplant)

Pakistan Power Plants Layer Source: digitized from Power and Gas Grid Map of South Asia (2006) Description: Power plants. Spatial Resolution: Not stated.

Airports Point Pakistan NREL 1992 (nrel:gstk_pakistan_53_airports)

Pakistan Airports Layer Source: Digital Chart of the World (1992) Description: Airport locations. Spatial Resolution: 1:1,000,000

Geothermal Point Pakistan NREL (nrel:gstk_pakistan_54_geoth)

Pakistan Geothermal Layer Source: digitized from the Hydrogeological Map of Pakistan (not stated) Description: Artesian wells and hot springs in Pakistan. Spatial Resolution: 1:5,000,000

Cities Point Pakistan NREL 1992 (nrel:gstk_pakistan_59_cities)

Pakistan Cities Layer Source: Digital Chart of the World (1992) Description: Populated places Spatial Resolution: 1:1,000,000

Elevation Multipolygon Philippines NREL 1993 (nrel:gstk_philippines_01_elevation)

Philippines Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Philippines NREL 2010 (nrel:gstk_philippines_02_landuse)

Philippines Landuse Layer Source: National Mapping and Resource Information Authority (2010) Description: Land use/land cover categories Spatial Resolution: Not Stated

Tsunami Risk Multipolygon Philippines NREL 1975 (nrel:gstk_philippines_03_tsunami_freq)

Philippines Tsunami Risk Layer Source: UNEP Global Risk Data Platform (composite source data 1975-2009) Description: This dataset includes an estimate of tsunami frequency. It is based on two sources: 1) A comprehensive list of reports and scientific papers compiled and utilized in producing tsunami hazard maps as well as finding return periods of future events. 2) Applying numerical tsunami models and zooming on selected areas. Unit is expected affected percentage of each pixel over a minimum return period of 500 years. This product was designed by International Centre for Geohazards /NGI for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: GIS processing International Centre for Geohazards /NGI. Spatial Resolution: 0.5 arc-minutes

Landslide Frequency Multipolygon Philippines NREL 1975 (nrel:gstk_philippines_05_landslide_freq_bypr)

Philippines Landslide Frequency Layer Source: UNEP Global Risk Data Platform (composite source data 1975-2009) Description: This dataset includes an estimate of the annual frequency of landslide triggered by precipitations. It depends on the combination of trigger and susceptibility defined by six parameters: slope factor, lithological (or geological) conditions, soil moisture condition, vegetation cover, precipitation and seismic conditions. Unit is expected annual probability and percentage of pixel of occurrence of a potentially destructive landslide event x 1000000. This product was designed by International Centre for Geohazards /NGI for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: GIS processing International Centre for Geohazards /NGI. Spatial Resolution: 0.5 arc-minutes

Fire Frequency Multipolygon Philippines NREL 1975 (nrel:gstk_philippines_06_fire_freq)

Philippines Fire Frequency Layer Source: UNEP Global Risk Data Platform (composite source data 1975-2009) Description: This dataset includes an estimate of the annual frequency of fires. This product was designed by International Centre for Geohazards /NGI for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: GIS processing International Centre for Geohazards /NGI. Spatial Resolution: 0.5 arc-minutes

Earthquake Frequency Multipolygon Philippines NREL 1973 (nrel:gstk_philippines_07_earthquake_freq)

Philippines Earthquake Frequency Layer Source: UNEP Global Risk Data Platform (composite source data 1973-2007) Description: This dataset includes an estimate of earthquake frequency of MMI categories higher than 9 over the period 1973-2007. It is based on Modified Mercalli Intensity map available in the Shakemap Atlas from USGS. Unit is expected average number of events per 1000 years. This product was compiled by UNEP/GRID-Europe for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: GIS processing Shakemap Atlas from USGS, compilation and global hazard distribution UNEP/GRID-Europe. Spatial Resolution: 0.5 arc-minutes

Drought Cnt Multipolygon Philippines NREL 1980 (nrel:gstk_philippines_08_drought_events_count)

Philippines Drought Cnt Layer Source: UNEP Global Risk Data Platform (composite source data 1980-2001) Description: This dataset includes an estimate of number of drought eventsbetween 1980-2001. It is based on two sources: 1) a global monthly gridded precipitation dataset obtained from the Climatic Research Unit (University of East Anglia); and 2) a GIS modeling of global Standardized Precipitation Index based on Brad Lyon's (IRI, Columbia University) methodology. It was modeled using global data. Spatial Resolution: 0.5 arc-minutes

Cyclone Wind Frequency Multipolygon Philippines NREL 1975 (nrel:gstk_philippines_09_cyclone_wind_freq)

Philippines Cyclone Wind Frequency Layer Source: UNEP Global Risk Data Platform (composite source data 1975-2009) Description: This dataset includes an estimate of wind triggered by tropical cyclone frequency of Saffir-Simpson category 1. It is based on three sources: 1) A compilation of best tracks dataset from WMO Regional Specialised Meteorological Centres (RSMCs) and Tropical Cyclone Warning Centres (TCWCs). As well as personal communication with Dr. Varigonda Subrahmanyam, Dr. James Weyman, Kiichi Sasaki, Philippe CAROFF, Jim Davidson, Simon Mc Gree, Steve Ready, Peter Kreft, Henrike Brecht. 2) A GIS modeling based on an initial equation from Greg Holland, which was further modified to take into consideration the movement of the cyclones through time. 3) A Digital Elevation Model (SRTM). Unit is expected average number of event per 1000 years. This product was designed by UNEP/GRID-Europe for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: GIS processing UNEP/GRID-Europe. Spatial Resolution: 0.5 arc-minutes

Cyclone Surge Frequency Multipolygon Philippines NREL 1975 (nrel:gstk_philippines_10_cyclone_surge_freq)

Philippines Cyclone Surge Frequency Layer Source: UNEP Global Risk Data Platform (composite source data 1975-2009) Description: This dataset includes an estimate of surges triggered by tropical cyclone frequency of Saffir-Simpson category 1. It is based on three sources: 1) A compilation of best tracks dataset from WMO Regional Specialised Meteorological Centres (RSMCs) and Tropical Cyclone Warning Centres (TCWCs). As well as personal communication with Dr. Varigonda Subrahmanyam, Dr. James Weyman, Kiichi Sasaki, Philippe CAROFF, Jim Davidson, Simon Mc Gree, Steve Ready, Peter Kreft, Henrike Brecht. 2) A GIS modeling based on an initial equation from Greg Holland, which was further modified to take into consideration the movement of the cyclones through time. 3) A Digital Elevation Model (SRTM). Unit is expected average number of event per 1000 years. This product was designed by UNEP/GRID-Europe for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: GIS processing UNEP/GRID-Europe. Spatial Resolution: 0.5 arc-minutes

Tilt Solar Multipolygon Philippines NREL 2007 (nrel:gstk_philippines_12_solar_tilt)

Philippines Tilt Solar Layer Source: National Renewable Energy Lab CSR dataset (2007) Description: Solar resource for a fixed flat plat collector, facing the equator with a tilt equal to the cell's latitude, averaged annually and monthly. Spatial Resolution: 40 km

Direct Solar Multipolygon Philippines NREL 2007 (nrel:gstk_philippines_13_solar_direct)

Philippines Direct Solar Layer Source: National Renewable Energy Lab CSR dataset (2007) Description: Direct normal irradiance (DNI) averaged annually and monthly. Spatial Resolution: 40 km

Global Solar Multipolygon Philippines NREL 2007 (nrel:gstk_philippines_14_solar_glo)

Philippines Global Solar Layer Source: National Renewable Energy Lab CSR dataset (2007) Description: Global horizontal irradiance (GHI) averaged annually and monthly. Spatial Resolution: 40 km

Wind Speed 80M Multipolygon Philippines NREL 2014 (nrel:gstk_philippines_20a_wind_speed_080)

Philippines Wind Speed 80m Layer Source: 3Tier (2014) Description: Annual mean wind speed (m/s) at 80 m height above ground level. Data was modeled by 3Tier and has not been modified by NREL. Spatial Resolution: ~1 km

Wind Speed 100M Multipolygon Philippines NREL 2014 (nrel:gstk_philippines_20a_wind_speed_100)

Philippines Wind Speed 100m Layer Source: 3Tier (2014) Description: Annual mean wind speed (m/s) at 100 m height above ground level. Data was modeled by 3Tier and has not been modified by NREL. Spatial Resolution: ~1 km

Wind Power 80M Multipolygon Philippines NREL 2014 (nrel:gstk_philippines_20b_wind_power_080)

Philippines Wind Power 80m Layer Source: 3Tier (2014) Description: Annual mean wind power density (W/m2) at 80 m height above ground level. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Data was modeled by 3Tier and has not been modified by NREL. Spatial Resolution: ~1 km

Mindanao Hydropower Resource Point Philippines NREL (nrel:gstk_philippines_25_mindanao_hydro)

Philippines Mindanao Hydropower Resource Layer Source: Building Low Emission Alternative to Develop Economic Resilience and Sustainability Project (B-LEADERS) Description: Hydropower resources of Mindanao island group. Color gradient of points representative of lower resource availability (white) to higher resource availability (dark blue). Spatial Resolution: Unknown.

Luzon Biomass Resource Multipolygon Philippines NREL (nrel:gstk_philippines_27g_luzon_biomass)

Philippines Luzon Biomass Resource Layer Source: Building Low Emission Alternative to Develop Economic Resilience and Sustainability Project (B-LEADERS) Description: Biomass resources of Luzon island group. Spatial Resolution: Unknown.

Mindanao Biomass Resource Point Philippines NREL (nrel:gstk_philippines_27h_mindanao_biomass)

Philippines Mindanao Biomass Resource Layer Source: Building Low Emission Alternative to Develop Economic Resilience and Sustainability Project (B-LEADERS) Description: Biomass resources of Mindanao island group. Spatial Resolution: Unknown

Visayas Biomass Resource Point Philippines NREL (nrel:gstk_philippines_27i_visayas_biomass)

Philippines Visayas Biomass Resource Layer Source: Building Low Emission Alternative to Develop Economic Resilience and Sustainability Project (B-LEADERS) Description: Biomass resources of Visayas island group. Spatial Resolution: Unknown.

Population Density Multipolygon Philippines NREL 2007 (nrel:gstk_philippines_29_popdensity)

Philippines Population Density Layer Source: Philippines GIS Data Clearinghouse seaport dataset (2007) Description: Number of people per 90 square meters. Spatial Resolution: Unknown.

Protected Areas Multipolygon Philippines NREL 2014 (nrel:gstk_philippines_31_protectedarea)

Philippines Protected Areas Layer Source: Protected Planet (2014) Description: Culled from the World Database on Protected Areas incorporating the UN List of Protected Areas Spatial Resolution: Not Stated

Municipality Boundaries Multipolygon Philippines NREL 2012 (nrel:gstk_philippines_36_subcountrybnd3)

Philippines Municipality Boundaries Layer Source: Global Administrative Areas (GADM) dataset (2012) Description: Sub-district level administrative boundaries. Spatial Resolution: Not Stated

City Boundaries Multipolygon Philippines NREL 2012 (nrel:gstk_philippines_37_subcountrybnd2)

Philippines City Boundaries Layer Source: Global Administrative Areas (GADM) dataset (2012) Description: District level administrative boundaries. Spatial Resolution: Not Stated

Province Boundaries Multipolygon Philippines NREL 2012 (nrel:gstk_philippines_38_subcountrybnd1)

Philippines Province Boundaries Layer Source: Global Administrative Areas (GADM) dataset (2012) Description: Province level administrative boundaries. Spatial Resolution: Not Stated

Country Boundary Multipolygon Philippines NREL 2012 (nrel:gstk_philippines_39_countryboundary)

Philippines Country Boundary Layer Source: Global Administrative Areas (GADM) dataset (2012) Description: Country level administrative boundaries. Spatial Resolution: Not Stated

Rivers Multilinestring Philippines NREL 2008 (nrel:gstk_philippines_40_rivers)

Philippines Major Rivers Layer Source: ESRI Data & Maps, rivers (2008) Description: Major rivers. Spatial resolution: 1:15,000,000

Railroads Multilinestring Philippines NREL 1992 (nrel:gstk_philippines_42_railroads)

Philippines Railroads Layer Source: Digital Chart of the World (1992) Description: Railroad lines. Spatial Resolution: 1:1,000,000

Roads Multilinestring Philippines NREL 2012 (nrel:gstk_philippines_43_roads)

Philippines Roads Layer Source: Philippines GIS Data CLearinghouse roads dataset (2012) Description: Major road network. Spatial Resolution: 1:1,000,000

Transmission Lines Multilinestring Philippines NREL 2006 (nrel:gstk_philippines_44_transmissionline)

Philippines Transmission Lines Layer Source: Digitized from GENI Philippine Power Grid Map 2006 Description: Utility electric transmission lines. Line size is representative of lower kV capacity (thin line) to higher kV capacity (wide line). Spatial Resolution: Not stated.

Power Plants Point Philippines NREL 2014 (nrel:gstk_philippines_51_powerplant)

Philippines Power Plants Layer Source: Data from CARMA (www.carma.org) & OpenDevelopment Cambodia hydropower plants (2014) Description: Power plants. Color gradient of points representative of lower energy produced (light brown) to higher energy produced (dark brown) in MWh. Downloaded 6 October 2014. Spatial resolution: Not stated.

Airports Point Philippines NREL 1997 (nrel:gstk_philippines_53_airports)

Philippines Airports Layer Source: Philippines GIS Data CLearinghouse airport dataset (1997) Description: Airport locations. Spatial Resolution: Not Stated

Seaports Point Philippines NREL 1997 (nrel:gstk_philippines_54_seaports)

Philippines Seaports Layer Source: Philippines GIS Data CLearinghouse seaport dataset (1997) Description: Seaport locations. Spatial Resolution: Not Stated

Volcano Hazard Point Philippines NREL (nrel:gstk_philippines_58_volcanoes)

Philippines Volcano Hazard Layer Source: UNEP/DEWA/GRID-Europe Description: This dataset includes an estimate of volcanoes events for the period 1980- March 2011. 10 kilometers buffers have been applied on 2 to 3 VEI events, and 20 km on 4 and 5 VEI events. Eruption events were provided by Smithsonian Institution, Volcanoes of the world database. Buffers were added by UNEP/GRID-Europe for the Global Assessment Report on Risk Reduction (GAR). Spatial Resolution: Not Stated

Cities Point Philippines NREL 1992 (nrel:gstk_philippines_59_cities)

Philippines Cities Layer Source: Digital Chart of the World (1992) Description: Populated places Spatial Resolution: 1:1,000,000

Elevation Multipolygon Sri Lanka NREL 1993 (nrel:gstk_srilanka_01_elevation)

Sri Lanka Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Sri Lanka NREL 2003 (nrel:gstk_srilanka_02_landuse)

Sri Lanka Landuse Layer Source: received from Ceylon Electricity Board, May 2003 Description: Land use/land cover categories. Spatial Resolution: Unknown

Tilt Solar Multipolygon Sri Lanka NREL 2004 (nrel:gstk_srilanka_12_solar_tilt)

Sri Lanka Tilt Solar Layer Source: National Renewable Energy Laboratory (NREL) Climatological Solar Radiation Model (2004) Description: Solar resource for a flat plate collector tilted towards the equation with a fixed tilt equal to the latitude, annual average and monthly values. Data were developed using NREL's Climatological Solar Radiation model, using information on cloud cover, atmospheric water vapor and trace gases, and atmospheric aerosols falling on a horizontal surface. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties of the model. Spatial Resolution: 40 km

Direct Solar Multipolygon Sri Lanka NREL 2004 (nrel:gstk_srilanka_13_solar_direct)

Sri Lanka Direct Solar Layer Source: Deutsches Zentrum für Luft- und Raumfahrt (DLR) (2004) Description: Direct normal irradiance (DNI) averaged annually and monthly for the years 2000, 2002, and 2003. Spatial Resolution: 0.1 degrees (nominally 10 km)

Global Solar Multipolygon Sri Lanka NREL 2004 (nrel:gstk_srilanka_14_solar_glo)

Sri Lanka Global Solar Layer Source: Deutsches Zentrum für Luft- und Raumfahrt (DLR) (2004) Description: Global horizontal irradiance (GHI) averaged annually and monthly for the years 2000, 2002, and 2003. Spatial Resolution: 0.1 degrees (nominally 10 km)

Wind Resource Polygon Sri Lanka NREL 2008 (nrel:gstk_srilanka_20_wind)

Sri Lanka Wind Resource Layer Source: National Renewable Energy Laboratory (NREL) and AWS Truepower (2008) Description: Annual and monthly mean wind power density (W/m2) and wind speed (m/s) at 50 m height above ground level. Other wind profile parameters are included for use by HOMER to simulate an hourly wind profile. Spatial Resolution: 400 m

Hydro Point Sri Lanka NREL 2005 (nrel:gstk_srilanka_25_hydro)

Sri Lanka Hydro Layer Source: National Renewable Energy Laboratory (NREL), 2005 Description: Annual and monthly microhydro resource potential estimates for 100 m intervals along streams/rivers in Sri Lanka. Spatial Resolution: 100 m

Lakes Polygon Sri Lanka NREL 2003 (nrel:gstk_srilanka_30_lakes)

Sri Lanka Lakes Layer Source: received from Ceylon Electricity Board, May 2003 Description: Major lakes and reservoirs. Spatial Resolution: Unknown

Protected Areas Polygon Sri Lanka NREL 2003 (nrel:gstk_srilanka_31_protectedarea)

Sri Lanka Protected Areas Layer Source: received from Ceylon Electricity Board, May 2003 Description: Parks and other national reserves. Spatial Resolution: Unknown

Country Boundary Multipolygon Sri Lanka NREL 2003 (nrel:gstk_srilanka_39_countryboundary)

Sri Lanka Country Boundary Layer Source: received from Ceylon Electricity Board, May 2003 Description: Country level administrative boundaries. Spatial Resolution: Unknown

Rivers Linestring Sri Lanka NREL 2003 (nrel:gstk_srilanka_40_rivers)

Sri Lanka Rivers Layer Source: received from Ceylon Electricity Board, May 2003 Description: Major rivers. Spatial Resolution: Unknown

Railroads Linestring Sri Lanka NREL 2003 (nrel:gstk_srilanka_42_railroad)

Sri Lanka Railroads Layer Source: received from Ceylon Electricity Board, May 2003 Description: National road network. Spatial Resolution: Unknown

Roads Multilinestring Sri Lanka NREL 2003 (nrel:gstk_srilanka_43_roads)

Sri Lanka Roads Layer Source: received from Ceylon Electricity Board, May 2003 Description: National road network. Spatial Resolution: Unknown

Transmission Lines Multilinestring Sri Lanka NREL 2003 (nrel:gstk_srilanka_44_transmissionline)

Sri Lanka Transmission Lines Layer Source: received from Ceylon Electricity Board, May 2003 Description: Electric power transmission lines of Sri Lanka. Spatial Resolution: Unknown

Protected Area Points Point Sri Lanka NREL 2003 (nrel:gstk_srilanka_50_protectedarea)

Sri Lanka Protected Area Points Layer Source: received from Ceylon Electricity Board, May 2003 Description: Point locations of historic sites in Sri Lanka. Spatial Resolution: Unknown

Power Plants Point Sri Lanka NREL 2003 (nrel:gstk_srilanka_51_powerplant)

Sri Lanka Power Plants Layer Source: received from Ceylon Electricity Board, May 2003 Description: Power plants. Spatial Resolution: Unknown

Cities Point Sri Lanka NREL 2003 (nrel:gstk_srilanka_59_cities)

Sri Lanka Cities Layer Source: received from Ceylon Electricity Board, May 2003 Description: Populated places in Sri Lanka. Spatial Resolution: Unknown

Elevation Multipolygon Thailand NREL 1993 (nrel:gstk_thailand_01_elevation)

Thailand Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Thailand NREL 2013 (nrel:gstk_thailand_02_landuse)

Thailand Landuse Layer Source: MODIS satellite (2013) Description: Land use/land cover categories from the MODIS satellite. Spatial Resolution: 500m

Tilt Solar Multipolygon Thailand NREL 2004 (nrel:gstk_thailand_12_solar_tilt)

Thailand Tilt Solar Layer Source: National Renewable Energy Laboratory (NREL) Climatological Solar Radiation Model (2004) Description: Solar resource for a flat plate collector tilted towards the equator with a fixed tilt equal to the latitude, annual average and monthly values. Data were developed using NREL's Climatological Solar Radiation model, using information on cloud cover, atmospheric water vapor and trace gases, and atmospheric aerosols falling on a horizontal surface. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties of the model. Spatial Resolution: 40 km

Direct Solar Multipolygon Thailand NREL 2004 (nrel:gstk_thailand_13_solar_direct)

Thailand Direct Solar Layer Source: National Renewable Energy Laboratory (NREL) Climatological Solar Radiation Model (2004) Description: Direct normal solar resource, annual average and monthly values. Data were developed using NREL's Climatological Solar Radiation model, using information on cloud cover, atmospheric water vapor and trace gases, and atmospheric aerosols falling on a horizontal surface. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties of the model. Spatial Resolution: 40 km

Global Solar Multipolygon Thailand NREL (nrel:gstk_thailand_14_solar_glo)

Thailand Global Solar Layer Source: National Renewable Energy Laboratory (NREL) Climatological Description: Global horizontal solar resource, annual average and monthly values. Data were developed using NREL's Climatological Solar Radiation model, using information on cloud cover, atmospheric water vapor and trace gases, and atmospheric aerosols falling on a horizontal surface. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties of the model. Spatial Resolution: 40km

Wind Resource Multipolygon Thailand NREL 2001 (nrel:gstk_thailand_20_wind)

Thailand Wind Resource Layer Source: Wind Energy Resource Atlas of Southeast Asia (2001) Description: Annual mean wind power density (W/m2) at 65 m height above ground level. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Spatial Resolution: 1 km

Protected Areas Multipolygon Thailand NREL 2005 (nrel:gstk_thailand_31_protectedarea)

Thailand Protected Areas Layer Source: World Database on Protected Areas Consortium, copyright World Conservation Union (IUCN) and UNEP-World Conservation Monitoring Centre (UNEP-WCMC) (2005) Description: Database of protected areas of IUCN categories I through VI, other protected areas and areas defined under international agreements. Spatial Resolution: Varied, compiled from multiple sources

Village Boundaries Multipolygon Thailand NREL 2011 (nrel:gstk_thailand_36_subcountrybnd3)

Thailand Village Boundaries Layer Source: Data were extracted from the Global Administrative Areas (GADM)database, version 2.0 (http://www.gadm.org) (2011) Description: Sub-District level administrative boundaries. Spatial Resolution: Unknown

District Boundaries Multipolygon Thailand NREL 2011 (nrel:gstk_thailand_37_subcountrybnd2)

Thailand District Boundaries Layer Source: Data were extracted from the Global Administrative Areas (GADM)database, version 2.0 (http://www.gadm.org) (2011) Description: District level administrative boundaries. Spatial Resolution: Unknown

Province Boundaries Multipolygon Thailand NREL 2011 (nrel:gstk_thailand_38_subcountrybnd1)

Thailand Province Boundaries Layer Source: Data were extracted from the Global Administrative Areas (GADM)database, version 2.0 (http://www.gadm.org) (2011) Description: Province level administrative boundaries. Spatial Resolution: Unknown

Country Boundary Multipolygon Thailand NREL 2011 (nrel:gstk_thailand_39_countryboundary)

Thailand Country Boundary Layer Source: Data were extracted from the Global Administrative Areas (GADM)database, version 2.0 (http://www.gadm.org) (2011) Description: Country level administrative boundaries. Spatial Resolution: Unknown

Rivers Multilinestring Thailand NREL 1992 (nrel:gstk_thailand_40_rivers)

Thailand Rivers Layer Source: Digital Chart of the World (1992) Description: Major river systems. Spatial Resolution: 1:1,000,000

Railroads Multilinestring Thailand NREL 1992 (nrel:gstk_thailand_42_railroads)

Thailand Railroads Layer Source: Digital Chart of the World (1992) Description: Railroad lines. Spatial Resolution: 1:1,000,000

Roads Multilinestring Thailand NREL 1992 (nrel:gstk_thailand_43_roads)

Thailand Roads Layer Source: Digital Chart of the World (1992) Description: National, provincial and district road network. Spatial Resolution: 1:1,000,000

Power Plants Point Thailand NREL 2013 (nrel:gstk_thailand_51_powerplant)

Thailand Power Plants Layer Source: Data from CARMA (www.carma.org)(2013) Description: Power plants. Spatial Resolution: Not stated.

Airports Point Thailand NREL 1992 (nrel:gstk_thailand_53_airports)

Thailand Airports Layer Source: Digital Chart of the World (1992) Description: Airport locations. Spatial Resolution: 1:1,000,000

Cities Point Thailand NREL 1992 (nrel:gstk_thailand_59_cities)

Thailand Cities Layer Source: Digital Chart of the World (1992) Description: Populated places. Spatial Resolution: 1:1,000,000

Elevation Multipolygon Turkey NREL 1993 (nrel:gstk_turkey_01_elevation)

Turkey Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Polygon Turkey NREL 1993 (nrel:gstk_turkey_02_landuse)

Turkey Landuse Layer Source: U.S. Geological Survey Global Land Use/Land Cover dataset (1993) Description: Land use/land cover categories, using the U.S. Geological Survey Modified Level 2 legend. Spatial Resolution: 1 km.

Direct Solar Multipolygon Turkey NREL 2009 (nrel:gstk_turkey_13_solar_direct)

Turkey Direct Solar Layer Source: GeoModel s.r.o. (2009) Description: Direct normal irradiance (DNI) averaged annually and monthly from April 2004 to March 2009. Spatial Resolution: 5 arc-minutes (nominally 10 km)

Global Solar Multipolygon Turkey NREL 2009 (nrel:gstk_turkey_14_solar_glo)

Turkey Global Solar Layer Source: GeoModel s.r.o. (2009) Description: Global horizontal irradiance (GHI) averaged annually and monthly from April 2004 to March 2009. Spatial Resolution: 5 arc-minutes (nominally 10 km)

Tilt Solar Multipolygon Turkey NREL 2009 (nrel:gstk_turkey_16_solar_tilt)

Turkey Tilt Solar Layer Source: NREL, derived from GeoModel s.r.o. (2009) Description: Solar radiation information for a fixed flat plate collector facing the equator with a tilt equal to the latitude, averaged annually and monthly from April 2004 to March 2009. Spatial Resolution: 5 arc-minutes (nominally 10 km)

Lakes Multipolygon Turkey NREL 2009 (nrel:gstk_turkey_30_lakes)

Turkey Lakes Layer Source: Government of Turkey, received 2009 Description: Global horizontal irradiance (GHI) averaged annually and Spatial Resolution: Unknown

Protected Areas Multipolygon Turkey NREL 2005 (nrel:gstk_turkey_31_protectedarea)

Turkey Protected Areas Layer Source: World Database on Protected Areas Consortium, copyright World Conservation Union (IUCN) and UNEP-World Conservation Monitoring Centre (UNEP-WCMC) (2005) Description: Database of protected areas of IUCN categories I through VI, other protected areas and areas defined under international agreements. Spatial Resolution: Varied, compiled from multiple sources

State Boundaries Multipolygon Turkey NREL 2009 (nrel:gstk_turkey_38_subcountrybnd1)

Turkey State Boundaries Layer Source: Government of Turkey, received 2009 Description: First level internal administrative boundaries. Spatial Resolution: Unknown

Country Boundary Multipolygon Turkey NREL 2009 (nrel:gstk_turkey_39_countryboundary)

Turkey Country Boundary Layer Source: Government of Turkey, received 2009 Description: Country level administrative boundaries. Spatial Resolution: Unknown

Rivers Multilinestring Turkey NREL 2009 (nrel:gstk_turkey_40_rivers)

Turkey Rivers Layer Source: Government of Turkey, received 2009 Description: Major rivers. Spatial Resolution: Unknown

Railroads Multilinestring Turkey NREL 2009 (nrel:gstk_turkey_42_railroad)

Turkey Railroads Layer Source: Government of Turkey, received 2009 Description: Major railroad routes of Turkey Spatial Resolution: Unknown

Roads Multilinestring Turkey NREL 2009 (nrel:gstk_turkey_43_roads)

Turkey Roads Layer Source: Government of Turkey, received 2009 Description: Major roads in Turkey. Spatial Resolution: Unknown

Transmission Lines Multilinestring Turkey NREL 2009 (nrel:gstk_turkey_44_transmissionline)

Turkey Transmission Lines Layer Source: Government of Turkey, received 2009 Description: Electric power transmission lines of Turkey. Spatial Resolution: Unknown

Power Plants Point Turkey NREL 2009 (nrel:gstk_turkey_51_powerplant)

Turkey Power Plants Layer Source: Government of Turkey, received 2009 Description: Power plant locations in Turkey. Spatial Resolution: Unknown

Airports Point Turkey NREL 2009 (nrel:gstk_turkey_53_airports)

Turkey Airports Layer Source: Government of Turkey, received 2009 Description: Airport locations in Turkey. Spatial Resolution: Unknown

Cities Point Turkey NREL 2009 (nrel:gstk_turkey_59_cities)

Turkey Cities Layer Source: Government of Turkey, received 2009 Description: Populated places in Turkey. Spatial Resolution: Unknown

Elevation Multipolygon Vietnam NREL 1993 (nrel:gstk_vietnam_01_elevation)

Vietnam Elevation Layer Source: U.S. Geological Survey GTOPO30 dataset (1993) Description: Terrain elevation in meters and derived percent slope. Spatial Resolution: 1 km.

Landuse Multipolygon Vietnam NREL 1993 (nrel:gstk_vietnam_02_landuse)

Vietnam Landuse Layer Source: U.S. Geological Survey Global Land Use/Land Cover dataset (1993) Description: Land use/land cover categories, using the U.S. Geological Survey Modified Level 2 legend. Spatial Resolution: 1 km.

Tilt Solar Multipolygon Vietnam NREL 2007 (nrel:gstk_vietnam_12_solar_tilt)

Vietnam Tilt Solar Layer Source: National Renewable Energy Lab CSR dataset (2007) Description: Solar resource for a fixed flat plat collector, facing the equator with a tilt equal to the cell's latitude, averaged annually and monthly. Spatial Resolution: 40 km

Direct Solar Multipolygon Vietnam NREL 2007 (nrel:gstk_vietnam_13_solar_direct)

Vietnam Direct Solar Layer Source: National Renewable Energy Lab CSR dataset (2007) Description: Direct normal irradiance (DNI) averaged annually and monthly. Spatial Resolution: 40 km

Global Solar Multipolygon Vietnam NREL 2007 (nrel:gstk_vietnam_14_solar_glo)

Vietnam Global Solar Layer Source: National Renewable Energy Lab CSR dataset (2007) Description: Global horizontal irradiance (GHI) averaged annually and monthly. Spatial Resolution: 40 km

Wind Resource Multipolygon Vietnam NREL 2001 (nrel:gstk_vietnam_20_wind)

Vietnam Wind Resource Layer Source: Wind Energy Resource Atlas of Southeast Asia (2001) Description: Annual mean wind power density (W/m2) at 65 m height above ground level. Data has been summarized into one-quarter power class intervals, calculating an average power density value within the interval area. Spatial Resolution: 1 km

Biogas Multipolygon Vietnam NREL (nrel:gstk_vietnam_26_biomass_biogas)

Vietnam Biogas Layer Source: Data provided by Entec ESCO Vietnam. Description: Biogas resource. Spatial Resolution: Not Stated.

Rice Crop Residues Multipolygon Vietnam NREL (nrel:gstk_vietnam_27a_biomass_crop_rice)

Vietnam Rice Crop Residues Layer Source: Data provided by Entec ESCO Vietnam. Description: Rice biomass resource. Spatial Resolution: Not Stated.

Corn Crop Residues Multipolygon Vietnam NREL (nrel:gstk_vietnam_27b_biomass_crop_corn)

Vietnam Corn Crop Residues Layer Source: Data provided by Entec ESCO Vietnam. Description: Corn biomass resource. Spatial Resolution: Not Stated.

Cassava Crop Residues Multipolygon Vietnam NREL (nrel:gstk_vietnam_27c_biomass_crop_cassava)

Vietnam Cassava Crop Residues Layer Source: Data provided by Entec ESCO Vietnam. Description: Cassava biomass resource. Spatial Resolution: Not Stated.

Peanut Crop Residues Multipolygon Vietnam NREL (nrel:gstk_vietnam_27d_biomass_crop_peanut)

Vietnam Peanut Crop Residues Layer Source: Data provided by Entec ESCO Vietnam. Description: Peanut biomass resource. Spatial Resolution: Not Stated.

Sugarcane Crop Residues Multipolygon Vietnam NREL (nrel:gstk_vietnam_27e_biomass_crop_sugarcane)

Vietnam Sugarcane Crop Residues Layer Source: Data provided by Entec ESCO Vietnam. Description: Sugarcane biomass resource. Spatial Resolution: Not Stated.

All Crop Residues Multipolygon Vietnam NREL (nrel:gstk_vietnam_27f_all_crop_residues)

Vietnam All Crop Residues Layer Source: Data provided by Entec ESCO Vietnam. Description: Combination of all crop residue biomass resource. Spatial Resolution: Not Stated.

Protected Areas Multipolygon Vietnam NREL 2012 (nrel:gstk_vietnam_31_protectedarea)

Vietnam Protected Areas Layer Source: World Database on Protected Areas Consortium, copyright World Conservation Union (IUCN) and UNEP-World Conservation Monitoring Centre (UNEP-WCMC) (2012) Description: Database of protected areas of IUCN categories I through VI, other protected areas and areas defined under international agreements. Spatial Resolution: Varied, compiled from multiple sources

Poverty Multipolygon Vietnam NREL 2005 (nrel:gstk_vietnam_32_poverty_summary)

Vietnam Poverty Layer Source: International Food Policy Research Institute 2005. Description: Percent of population in poverty Spatial Resolution: Not Stated.

Electrification Multipolygon Vietnam NREL 2005 (nrel:gstk_vietnam_33_rural_electrification)

Vietnam Electrification Layer Source: International Food Policy Research Institute 2005. Description: Rural electrification ratio. Spatial Resolution: Not Stated.

Commune Boundaries Multipolygon Vietnam NREL (nrel:gstk_vietnam_36_subcountrybnd3)

Vietnam Commune Boundaries Layer Source: Data provided by Entec ESCO Vietnam. Description: Commune-level administrative boundaries. Spatial Resolution: 1:50000

District Boundaries Multipolygon Vietnam NREL (nrel:gstk_vietnam_37_subcountrybnd2)

Vietnam District Boundaries Layer Source: Data provided by Entec ESCO Vietnam. Description: District-level administrative boundaries. Spatial Resolution: 1:50000

Province Boundaries Multipolygon Vietnam NREL (nrel:gstk_vietnam_38_subcountrybnd1)

Vietnam Province Boundaries Layer Source: Data provided by Entec ESCO Vietnam. Description: Province-level administrative boundaries. Spatial Resolution: 1:50000

Country Boundary Multipolygon Vietnam NREL (nrel:gstk_vietnam_39_countryboundary)

Vietnam Country Boundary Layer Source: Data provided by Entec ESCO Vietnam. Description: Country-level administrative boundaries. Spatial Resolution: 1:50000

Rivers Linestring Vietnam NREL (nrel:gstk_vietnam_40_rivers)

Vietnam Rivers Layer Source: Data provided by Entec ESCO Vietnam. Description: Major rivers. Spatial Resolution: 1:50000

Railroads Linestring Vietnam NREL (nrel:gstk_vietnam_42_railroads)

Vietnam Railroads Layer Source: Data provided by Entec ESCO Vietnam. Description: Railroads. Spatial Resolution: 1:50000

Roads Linestring Vietnam NREL 1992 (nrel:gstk_vietnam_43_roads)

Vietnam Roads Layer Source: Digital Chart of the World (1992) Description: Major road network. Spatial Resolution: 1:1,000,000

Transmission Lines Linestring Vietnam NREL 2010 (nrel:gstk_vietnam_44_transmissionline)

Vietnam Transmission Lines Layer Source: Digitized from JETRO National Energy Grid Map (2010) Description: Utility electric transmission lines. Spatial Resolution: Not Stated.

Municipal Solid Waste Point Vietnam NREL (nrel:gstk_vietnam_50_biomass_msw)

Vietnam Municipal Solid Waste Layer Source: Data provided by Entec ESCO Vietnam. Description: Municipal solid waste biomass resource. Spatial Resolution: Not Stated.

Power Plants Point Vietnam NREL 2010 (nrel:gstk_vietnam_51_powerplant)

Vietnam Power Plants Layer Source: Digitized from JETRO National Energy Grid Map (2010) Description: Power plants. Spatial Resolution: Not Stated.

Airports Point Vietnam NREL 1992 (nrel:gstk_vietnam_53_airports)

Vietnam Airports Layer Source: Digital Chart of the World (1992) Description: Airport locations. Spatial Resolution: 1:1,000,000

Cities Point Vietnam NREL 1992 (nrel:gstk_vietnam_59_cities)

Vietnam Cities Layer Source: Digital Chart of the World (1992) Description: Populated places Spatial Resolution: 1:1,000,000

Active Leases (gt_prospector:gtp_datagap_active_leases)

Sites with Active Leases Geothermal Data Gap Analysis identified sites with active leases. Assessed data availability and proximity to existing projects produced by the National Renewable Energy Laboratory. Last updated December 4, 2012.

Fault Mapping (gt_prospector:gtp_datagap_fault_mapping)

Fault Mapping Geothermal Data Gap Analysis identified candidate sites for fault mapping. Assessed data availability and proximity to existing projects produced by the National Renewable Energy Laboratory. Last updated December 4, 2012.

Favorable Areas (gt_prospector:gtp_datagap_fav_areas)

Favorable Areas Geothermal Data Gap Analysis identified candidate site boundaries for favorable areas. Assessed data availability and proximity to existing projects produced by the National Renewable Energy Laboratory. Last updated November 28, 2012.

Geochemical Studies (gt_prospector:gtp_datagap_geochemical_studies)

Geochemical Studies Geothermal Data Gap Analysis identified candidate sites for geochemical studies. Assessed data availability and proximity to existing projects produced by the National Renewable Energy Laboratory. Last updated December 4, 2012.

Geologic Mapping (gt_prospector:gtp_datagap_geologic_mapping)

Geologic Mapping Geothermal Data Gap Analysis identified candidate sites for geologic mapping. Assessed data availability and proximity to existing projects produced by the National Renewable Energy Laboratory. Last updated December 4, 2012.

Geophysical Studies (gt_prospector:gtp_datagap_geophysical_studies)

Geophysical Studies Geothermal Data Gap Analysis identified candidate sites for geophysical studies. Assessed data availability and proximity to existing projects produced by the National Renewable Energy Laboratory. Last updated December 4, 2012.

Identified Site Boundaries (gt_prospector:gtp_datagap_identified_site_bndry)

Identified Site Boundaries & Power Density Geothermal Data Gap Analysis identified candidate site boundaries for top favorable areas. Assessed data availability and proximity to existing projects produced by the National Renewable Energy Laboratory. Last updated November 28, 2012.

Identified Sites Lacking at least One Data Type (gt_prospector:gtp_datagap_sites_lacking_data)

Identified Sites Lacking at least One Data Type Geothermal Data Gap Analysis identified candidate sites lacking at least one data type. Assessed data availability and proximity to existing projects produced by the National Renewable Energy Laboratory. Last updated December 4, 2012.

Well Data Collection (gt_prospector:gtp_datagap_well_data_collection)

Well Data Collection Geothermal Data Gap Analysis identified candidate sites for well data collection. Assessed data availability and proximity to existing projects produced by the National Renewable Energy Laboratory. Last updated December 4, 2012.

GT Fault Maps (gt_prospector:gtp_gaptype_fault_maps)

Data gap analysis funded by the Geothermal Technology Office aimed to determine high potential hydrothermal areas where critical data are needed to support initial exploration. Information was collected about existing data using a semi-automated process and data coverage maps were then created. Ten data types were chosen, including fault maps, geochemistry data, geological maps, geophysical data, lineament maps, mineral occurrence maps, structural maps, surface deformation maps, surface fault data, and well data. Some data types lack any usable data. A grid of the contiguous U.S. was created with 88,000 10-km by 10-km grid cells, and each cell was populated with the status of data availability corresponding to the data types. For more information, see: https://pangea.stanford.edu/ERE/db/GeoConf/papers/SGW/2013/Esposito.pdf

GT Geochemistry Data (gt_prospector:gtp_gaptype_geochemistry_data)

Data gap analysis funded by the Geothermal Technology Office aimed to determine high potential hydrothermal areas where critical data are needed to support initial exploration. Information was collected about existing data using a semi-automated process and data coverage maps were then created. Ten data types were chosen, including fault maps, geochemistry data, geological maps, geophysical data, lineament maps, mineral occurrence maps, structural maps, surface deformation maps, surface fault data, and well data. Some data types lack any usable data. A grid of the contiguous U.S. was created with 88,000 10-km by 10-km grid cells, and each cell was populated with the status of data availability corresponding to the data types. For more information, see: https://pangea.stanford.edu/ERE/db/GeoConf/papers/SGW/2013/Esposito.pdf

GT Geological Maps (gt_prospector:gtp_gaptype_geological_maps)

Data gap analysis funded by the Geothermal Technology Office aimed to determine high potential hydrothermal areas where critical data are needed to support initial exploration. Information was collected about existing data using a semi-automated process and data coverage maps were then created. Ten data types were chosen, including fault maps, geochemistry data, geological maps, geophysical data, lineament maps, mineral occurrence maps, structural maps, surface deformation maps, surface fault data, and well data. Some data types lack any usable data. A grid of the contiguous U.S. was created with 88,000 10-km by 10-km grid cells, and each cell was populated with the status of data availability corresponding to the data types. For more information, see: https://pangea.stanford.edu/ERE/db/GeoConf/papers/SGW/2013/Esposito.pdf

GT Geophysical Data (gt_prospector:gtp_gaptype_geophysical_data)

Data gap analysis funded by the Geothermal Technology Office aimed to determine high potential hydrothermal areas where critical data are needed to support initial exploration. Information was collected about existing data using a semi-automated process and data coverage maps were then created. Ten data types were chosen, including fault maps, geochemistry data, geological maps, geophysical data, lineament maps, mineral occurrence maps, structural maps, surface deformation maps, surface fault data, and well data. Some data types lack any usable data. A grid of the contiguous U.S. was created with 88,000 10-km by 10-km grid cells, and each cell was populated with the status of data availability corresponding to the data types. For more information, see: https://pangea.stanford.edu/ERE/db/GeoConf/papers/SGW/2013/Esposito.pdf

GT Well Data (gt_prospector:gtp_gaptype_well_data)

Data gap analysis funded by the Geothermal Technology Office aimed to determine high potential hydrothermal areas where critical data are needed to support initial exploration. Information was collected about existing data using a semi-automated process and data coverage maps were then created. Ten data types were chosen, including fault maps, geochemistry data, geological maps, geophysical data, lineament maps, mineral occurrence maps, structural maps, surface deformation maps, surface fault data, and well data. Some data types lack any usable data. A grid of the contiguous U.S. was created with 88,000 10-km by 10-km grid cells, and each cell was populated with the status of data availability corresponding to the data types. For more information, see: https://pangea.stanford.edu/ERE/db/GeoConf/papers/SGW/2013/Esposito.pdf

NREL Gulf of Mexico 90m Offshore Wind Resource (data_res:gulf_of_mexico_90mwindspeed_off)

Abstract: Annual average offshore wind speed for the western Gulf of Mexico (Texas and Louisiana) at a 90 meter height. Supplemental Information: The annual wind speed estimates were produced by AWS Truepower for an offshore mapping project using their MesoMap system and historical weather data. This shapefile was generated from raster datasets with a 200 m spatial resolution and a projection of UTM zone 15, datum WGS 84 and then projected to Geographic Decimal Degrees, datum WGS 84. Source: AWS Truepower/NREL

NREL Hydrogen Potential (data_res:h2renewables)

Abstract: Estimate the potential for producing hydrogen from key renewable resources (onshore wind, solar photovoltaic, and biomass) by county for the United States Supplemental Information: This study was conducted to estimate the potential for producing hydrogen from key renewable resources (onshore wind, solar photovoltaic, and biomass) by county in the United States and to create maps that allow the reader to easily visualize the results. To accomplish this objective, the authors analyzed renewable resource data both statistically and graphically utilizing a state-of-the-art Geographic Information System (GIS), a computer-based information system used to create and visualize geographic information. Land-use and environmental exclusions were applied to represent the most viable resources across the country. While wind, solar, and biomass are considered major renewable resources, other renewable energy resources could also be used for hydrogen production, thus contributing to hydrogen development locally and regionally. These additional resources include offshore wind, concentrating solar power, geothermal, hydropower, photoelectrochemical, and photobiological resources. This study found that approximately 1 billion metric tons of hydrogen could be produced annually from wind, solar, and biomass resources in the United States. The greatest potential for producing hydrogen from these key renewable resources is in the Great Plains region. In addition, this research suggests that renewable hydrogen has the potential to displace gasoline consumption in most states if and when a number of technical and scientific barriers can be overcome Source: ESRI and NREL

NREL Hawaii 50m Wind Resource (data_res:hawaii_50mwind)

Abstract: Annual average wind resource potential for the state of Hawaii at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 4, datum WGS 84 projection system. Source: TrueWind Solutions/NREL

idgeol_poly_dd (gt_prospector:idgeol_poly_dd)

These digital maps are a reformulation of previously published maps, primarily maps of states. The reformulation gives all the maps the same structure and format, allowing them to be combined into regional maps. The associated data tables have information about age and lithology of the map units, also in a standard format.

NREL Illinois 50m Wind Resource (data_res:il_50mwind)

Abstract: Annual average wind resource potential of Illinois at a 50 meter height. Supplemental Information: This data set was produced and validated by NREL using their WRAM model. This shapefile was generated from a raster dataset with a 1000 m resolution, in a Transverse Mercator projection with the following parameters: Projection: TRANSVERSE Zunits NO Units METERS Spheroid CLARKE1866 Xshift 0.0000000000 Yshift 0.0000000000 Parameters 1.00000000 /* scale factor at central meridian -89 30 0.000 /* longitude of central meridian 39 45 0.000 /* latitude of origin 0.00000 /* false easting (meters) 0.00000 /* false northing (meters) Source: NREL

Solar DNI Polygon India 10km NREL 2013 (swera:india_dni_ann_month)

This map depicts model estimates of annual average direct normal irradiance (DNI) at 10 km resolution based on hourly estimates of radiation over 10 years (2002-2011). The inputs are visible imagery from geostationary satellites, aerosol optical depth, water vapor, and ozone. Units: kWh/m sq. per day, Source: NREL

Solar GHI Polygon India 10km NREL 2013 (swera:india_ghi_ann_month)

This map depicts model estimates of annual average global horizontal irradiance (GHI) at 10 km resolution based on hourly estimates of radiation over 10 years (2002-2011). The inputs are visible imagery from geostationary satellites, aerosol optical depth, water vapor, and ozone. Units: kWh/m sq. per day, Source: NREL

NREL Indiana 50m Wind Resource (data_res:indiana_50mwind)

Abstract: Annual average wind resource potential for the state of Indiana at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 16 datum WGS 84 projection system. Source: AWS TrueWind/NREL

International Parks Polygon Global WDPA 2006 (swera:international_poly_wdpa2006)

SRID 4326 of two available coordinate systems. International Parks of the world as designated by the World Database on Protected Areas (WDPA).

International Parks Polygon Global WDPA 2006 (swera:international_poly_wdpa2006_900913)

SRID 900913 of two available coordinate systems. International Parks of the world as designated by the World Database on Protected Areas (WDPA).

NREL Iowa 50m Wind Resource (data_res:iowa_50m_wind)

Abstract: Annual average wind resource potential for the state of Iowa at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. Source: UNDEERC

irena_data_available (data_res:irena_data_available)

NREL Kansas 50m Wind Resource (data_res:kansas_50mwind)

Abstract: Annual average wind resource potential for the state of Kansas at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. Source: AWS TrueWind/NREL

kbf (gt_prospector:kbf)

NULL

kbge (gt_prospector:kbge)

NULL

kgra_merge (gt_prospector:kgra_merge)

NULL

NREL Kentucky 50m Wind Resource (data_res:ky_50mwind)

Abstract: Annual average wind resource potential for the state of Kentucky at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. Source: TrueWind Solutions/NREL

NREL Maine 50m Wind Resource (data_res:maine_50mwind)

Abstract: Annual average wind resource potential for the state of Maine at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. Source: AWS TrueWind/NREL

NREL Massachusetts 50m Wind Resource (data_res:massachusetts_50mwind)

Abstract: Annual average wind resource potential for the state of Massachusetts at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. Source: AWS TrueWind/NREL

NREL Michigan 50m Wind Resource (data_res:michigan_50mwind)

Abstract: Annual average wind resource potential for the state of Michigan at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 16, datum WGS 84 projection system. Source: AWS TrueWind/NREL

NREL Mid Atlantic 50m Wind Resource (data_res:midatl_50mwind)

Abstract: Annual average wind resource potential of the mid-Atlantic United States at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 17, datum WGS 84 projection system. Source: AWS TrueWind/NREL

NREL Minnesota 50m Wind Resource (data_res:minnesota_50m_wind)

minown (gt_prospector:minown)

This data was collected by the U.S. Bureau of Land Management (BLM) in New Mexico at both the New Mexico State Office and at the various field offices. This dataset is meant to depict the federal mineral (or subsurface) interest of land parcels within New Mexico. No attempt is made to depict the mineral interest of non-federal entities. BLMs Master Title Plats are the official land records of the federal government and serve as the primary data source for depiction of federal mineral interest lands. Auxilliary source are referenced, as well, for the depiction of federal mineral interest. Collection of this dataset began in the 1980s using the BLMs ADS software to digitize information at the 1:24,000 scale. In the mid to late 1990s the data was converted from ADS to ArcInfo software and merged into tiles of one degree of longitude by one half degree of latitude. These tiles were regularly updated. The tiles were merged into a statewide coverage. The source geodatabase for this shapefile was created by loading the merged ArcInfo coverage into a personal geodatabase. The geodatabase data were snapped to a more accurate GCDB derived land network, where available. In areas where GCDB was not available the data were snapped to digitized PLSS. This shapefile has been created by exporting the geodatabase feature class.

NREL Missouri 50m Wind Resource (data_res:missouri_50mwind)

Abstract: Annual average wind resource potential for the state of Missouri at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 15 datum WGS 84 projection system. Source: AWS TrueWind/NREL

National Parks Polygon Global WDPA 2006 (swera:national_iucn1to6_poly_wdpa2006)

National Parks of the world as designated by the World Database on Protected Areas.

National Parks (Other) Polygon Global WDPA 2006 (swera:national_otherareas_poly_wdpa2006)

Other National Parks not found in the National Parks Polygon Global WDPA 2006 layer as designated by the World Database on Protected Areas.

NREL North and South Dakota 50m Wind Resource (data_res:ndsd_50mwind)

Abstract: Annual average wind resource potential of North and South Dakota at a 50 meter height. Supplemental Information: This data set was produced and validated by NREL using their WRAM model. This shapefile was generated from a raster dataset with a 1000 m resolution, in a Lambert Azimuthal projection with the following parameters: Projection LAMBERT_AZIMUTHAL Datum NONE Zunits NO Units METERS Xshift 0.0000000000 Yshift 0.0000000000 Parameters 6370997.0000000000 0.0000000000 6370997.00000 /* radius of the sphere of reference -100 15 0.000 /* longitude of center of projection 46 3 0.000 /* latitude of center of projection 0.00000 /* false easting (meters) 0.00000 /* false northing (meters) Source: NREL

USDA Regions (BSM_KDF_v0:ne_100m_usda_4326)

NREL Nebraska 50m Wind Resource (data_res:nebraska_50mwind)

Abstract: Annual average wind resource potential for the state of Nebraska at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 14 datum WGS 84 projection system. Source: TrueWind Solutions/NREL

NREL Nevada 50m Wind Resource (data_res:nevada_50mwind)

Abstract: Annual average wind resource potential for the state of Nevada, United States at a 50 meter height. This dataset will be replaced when the southwest region has been completed, and the data may change when this region has been completed. Source: TrueWind Solutions/NREL

NREL New England 50m Wind Resource (data_res:neweng_wpc50_poly)

Abstract: Annual average wind resource potential for the New England Region at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. Source: AWS TrueWind/NREL

NREL New Mexico 50m Wind Resource (data_res:newmexico_50mwind)

Abstract: Annual average wind resource potential for the state of New Mexico at a 50 meter height. This dataset will be replaced when the southwest region has been completed, and the data may change when this region has been completed. Source: TrueWind Solutions/NREL

nfs_lands_merge (gt_prospector:nfs_lands_merge)

REQUIRED: A brief narrative summary of the data set.

NREL New Hampshire 50m Wind Resource (data_res:nhampsire_50mwind)

Abstract: Annual average wind resource potential for the state of New Hampshire at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. Source: AWS TrueWind/NREL

RE_Atlas Hydro (NPDs) (re_atlas:nonpowered_dams)

This data set contains a list of U.S. Existing Non-powered Dams (NPD) with hydropower potential greater than 1MW. This data set consists of geo-referenced digital data and associated attributes created in "Hadjerioua, B., Y. Wei, S.-C. Kao and B. T. Smith (2012), An Assessment of Energy Potential at Non-powered Dams in the United States, Technical Manual 2011/251, Oak Ridge National Laboratory, Oak Ridge, TN.". The computed potential hydropower energy and capacity are estimates based on non-directly measured flow and head, and hence do not represent the actual numbers for engineering design. This resource assessment is not intended to provide economic feasibility level studies at each individual site. It will be the users' sole responsibility to determine whether if any site is worthy for further development. Source: http://www1.eere.energy.gov/water/pdfs/npd_report.pdf

nvblmleasenom09 (gt_prospector:nvblmleasenom09)

NULL

NREL New York 50m Wind Resource (data_res:ny_50m_wind)

Abstract: Annual average wind resource potential for New York at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 18, datum WGS 84 projection system. Source: NREL

RE_Atlas Wind Speed - Offshore (re_atlas:offshore_windspeed)

Wind: 2008 DOE report, 20% Wind by 2030. p. 8. The nation has more than 8,000GW of available land-based wind resources” Plus 2200 GW of offshore wind class 5 and better between 0 and 50 nm from shore, based on NREL’s most recent offshore resource estimates (offshore modeled data for TX, LA, GA, New England and Great Lakes; offshore portions of onshore modeled resource datasets; and estimates by NREL’s wind resource assessment group for remaining areas). Potential capacity estimated assuming 5 MW/km2. The offshore wind data are based on 90m height above surface. Areas with annual average wind speeds of 7 meters per second (m/s) and greater at 90-m height are generally considered to have a wind resource suitable for offshore development.

NREL Ohio 50m Wind Resource (data_res:ohio_50mwind)

Abstract: Annual average wind resource potential for the state of Ohio at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 17 datum WGS 84 projection system. Source: AWS TrueWind/NREL

NREL Oklahoma 50m Wind Resource (data_res:oklahoma_50mwind)

Abstract: Annual average wind resource potential for the state of Oklahoma at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. Source: AWS TrueWind/NREL

or_wa_land_ownership (gt_prospector:or_wa_land_ownership)

This theme portrays information related to surface jurisdiction of lands located in the states of Oregon and Washington.

NREL Pacific Coast 90m Offshore Wind Resource (data_res:pacific_coast_90mwindspeed_off)

Abstract: Annual average offshore wind speed for the Pacific Coast (California, Oregon, and Washington) at a 90 meter height. Supplemental Information: The annual offshore wind speed estimates were produced by AWS Truepower for onshore wind mapping projects using their MesoMap system and historical weather data. The wind speeds data have been interpolated to a 90-m height and extrapolated to 50 nautical miles by NREL. The raster datasets had a spatial 200 m resolution for California and 400 m resolution for Oregon and Washington with a projection of UTM zone 11, datum WGS 84. The shapefile was generated from these raster datasets and then projected to Geographic Decimal Degrees, datum WGS 84. Source: AWS Truepower/NREL

NREL Pacific Northwest 50m Wind Resource (data_res:pnw_50m_wind_resource)

Abstract: Annual average wind resource potential of the northwestern United States at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 400 m resolution, in a UTM zone 11, datum WGS 84 projection system. The resource information for the Confederated Tribes of the Umatilla reservation is not being made available as part of this data set at their request. Source: TrueWind Solutions/NREL

PNW Wind -shape (wind:pnw_50m_wind_resource_shp)

potential_geothermal_area (gt_prospector:potential_geothermal_area)

This coverage shows the regions favorable for the discovery and shallow depth (less than 1000m) of thermal water of sufficient temperature for direct-heat applications. It is probable that only small areas of this region are truly underlain by such thermal water; the region represents that part of the state that deserves exploration for thermal areas. The region is defined on the basis of various geothermal and tectonic phenomena such as locations of thermal wells and springs, above-normal heat flow, youthful volcanism, mineralization, and seismicity

Power Plants Afghanistan 2006 (gst:pplant_afghanistan)

Source: digitized from Power and Gas Grid Map of South Asia (2006) Spatial resolution/Scale: Not stated. Description: Power plants.

Power Plants Bangladesh 2005 (gst:pplant_bangladesh)

Source: Bangladesh Power Development Board (Unknown, before 2005) Spatial resolution/Scale: 1:3,000,000 Description: Grid substations.

Power Plants Bhutan (gst:pplant_bhutan)

Source: Carbon Monitoring for Action (CARMA) carma.org Spatial resolution/Scale: Unknown Description: Power plants.

Power Plants Brazil 2002 (gst:pplant_brazil)

Source: ONS (National Operator of the Electric System) - Brazil (2002) Spatial resolution/Scale: Unknown Description: Power plants.

Power Plants Cambodia 2013 (gst:pplant_cambodia)

Source: Data from CARMA (www.carma.org) and OpenDevelopment Cambodia hydropower plants (2013) Spatial resolution/Scale: Not stated. Description: Power plants.

Power Plants Elsalvador 2004 (gst:pplant_elsalvador)

Source: Minesterio de Medio Ambiente y Recursos Naturales (received Jun 2004) Spatial resolution/Scale: Unknown Description: Power plants in El Salvador.

Power Plants Honduras 2003 (gst:pplant_honduras)

Source: Oficina de Electrification Social (received Aug 2003) Spatial resolution/Scale: Unknown Description: Power plants in Honduras.

Power Plants India 2010 (gst:pplant_india)

Source: Government of India, received 2010 Spatial resolution/Scale: Unknown Description: Power plant locations in India.

Power Plants Indonesia 2013 (gst:pplant_indonesia)

Source: Data from CARMA (www.carma.org) and OpenDevelopment Cambodia hydropower plants (2013) Spatial resolution/Scale: Not stated. Description: Power plants.

Power Plants Kenya (gst:pplant_kenya)

Source: Data from the Platts World Electric Power Plants Database were georeferenced using auxiliary GIS datasets, documents and maps from national utilities, regional power pools and the World Bank. Spatial resolution/Scale: Unknown Description: Data for power plants with total installed generating capacity > 10 mw.

Power Plants Malaysia 2013 (gst:pplant_malaysia)

Source: Data from CARMA (www.carma.org) and OpenDevelopment Cambodia hydropower plants (2013) Spatial resolution/Scale: Not stated. Description: Power plants.

Power Plants Nepal (gst:pplant_nepal)

Source: Nepal Alternative Energy Promostion Centre - Energy Sector Assistance Programme Spatial resolution/Scale: Unknown Description: Major power plants.

Power Plants Pakistan 2006 (gst:pplant_pakistan)

Source: digitized from Power and Gas Grid Map of South Asia (2006) Spatial resolution/Scale: Not stated. Description: Power plants.

Power Plants Philippines 2014 (gst:pplant_philippines)

Source: Data from CARMA (www.carma.org) and OpenDevelopment Cambodia hydropower plants (2014) Spatial resolution/Scale: Not stated. Description: Power plants. Color gradient of points representative of lower energy produced (light brown) to higher energy produced (dark brown) in MWh. Downloaded 6 October 2014.

Power Plants Srilanka 2003 (gst:pplant_srilanka)

Source: received from Ceylon Electricity Board, May 2003 Spatial resolution/Scale: Unknown Description: Power plants.

Power Plants Thailand 2013 (gst:pplant_thailand)

Source: Data from CARMA (www.carma.org)(2013) Spatial resolution/Scale: Not stated. Description: Power plants.

Power Plants Turkey 2009 (gst:pplant_turkey)

Source: Government of Turkey, received 2009 Spatial resolution/Scale: Unknown Description: Power plant locations in Turkey.

Power Plants Vietnam 2010 (gst:pplant_vietnam)

Source: Digitized from JETRO National Energy Grid Map (2010) Spatial resolution/Scale: Not Stated. Description: Power plants.

pr_vi_50mwind (data_res:pr_vi_50mwind)

Abstract: Annual average wind resource potential for Puerto Rico and the Virgin Islands at a 50 meter height. Supplemental Information: Provide information on the wind resource development potential within Puerto Rico and the Virgin Islands. Source: AWS TrueWind/NREL

protected_areas (irena:protected_areas)

public_lands_acecs (gt_prospector:public_lands_acecs)

REQUIRED: A brief narrative summary of the data set.

public_lands_blm (gt_prospector:public_lands_blm)

REQUIRED: A brief narrative summary of the data set.

public_lands_island_park (gt_prospector:public_lands_island_park)

REQUIRED: A brief narrative summary of the data set.

public_lands_trails (gt_prospector:public_lands_trails)

REQUIRED: A brief narrative summary of the data set.

public_lands_wsas (gt_prospector:public_lands_wsas)

REQUIRED: A brief narrative summary of the data set.

pvwatts_data_available (data_res:pvwatts_data_available)

pvwatts_data_available_90 (data_res:pvwatts_data_available_90)

qfelsicvents (gt_prospector:qfelsicvents)

Quaternary felsic intrusions in the Western US: 1:500K ?, Source: Nevada Bureau of Mines and Geology (NBMG) (ftp://ftp.nbmg.unr.edu/pub/geothermal/03_Geology_Data/gbQfelsicvents.zip)

Identified Hydrothermal Sites Points United States USGS 2008 (irena:reatlas_geothermalpoint)

Identified hydrothermal sites from Assessment of Moderate- and High-Temperature Geothermal Resources of the United States (2008). This document summarizes the result of the resource assessment in which the identified sites in the data set were gathered and analyzed. The methodology used to develop resource estimates for the identified hydrothermal sites is available in A Review of Methods Applied by the U.S. Geological Survey in the Assessment of Identified Geothermal Resources. Site attributes list most likely values for temperature and reservoir volume and mean estimate for resource potential, taken from a distribution of values. Sources: - Williams, Colin F., Reed, Marshall J., Mariner, Robert H., DeAngelo, Jacob, Galanis, S. Peter, Jr., 2008, Assessment of moderate- and high-temperature geothermal resources of the United States: U.S. Geological Survey Fact Sheet 2008-3082, 4 p. - Williams, C.F., Reed, M.J., and Mariner, R.H., 2008, A review of methods applied by the U.S. Geological Survey in the assessment of identified geothermal resources: U.S. Geological Survey Open-File Report 2008-1296, 27 p.

Deep Enhanced Geothermal Systems Polygons United States SMU/NREL 2009 (irena:reatlas_us_geothermal)

Map does not include shallow Deep Enhanced Geothermal Systems (EGS) resources located near hydrothermal sites or USGS assessment of undiscovered hydrothermal resources. Source data for deep EGS includes temperature at depth from 3 to 10 km provided by Southern Methodist University Geothermal Laboratory (Blackwell & Richards, 2009) and analyses (for regions with temperatures ≥150°C) performed by NREL (2009). N/A regions have temperatures less than 150°C at 10 km depth and were not assessed for deep EGS potential. Temperature at depth data for deep EGS in Alaska and Hawaii not available. Qualitative classes are based on temperature and depth ranges. Temperature values are not exclusive to any single class and may be located at different depths from one class to the next. Classes express approximate favorability for geothermal resource, with a lower number indicating the possibility of a higher potential value.

Administrative Boundaries Polygon Global ESRI 2008 (swera:ref_admin)

World Administrative Units represents the boundaries for the first-level administrative units of the world.

World Cities Points Global ESRI 2002 (swera:ref_cities)

World Cities provides a base map layer of the cities for the world. The cities include national capitals, provincial capitals, major population centers, and landmark cities.

ref_cities (test_ws:ref_cities)

Country Boundaries Polygon Global ESRI 2008 (swera:ref_countries)

World Countries (Generalized) represents generalized boundaries for the countries of the world as they existed in January 2008.

Detailed Lakes Polygon Global Natural Earth (swera:ref_detailed_lakes)

Primarily derived from World Data Bank 2 with numerous reservoir additions from other sources, primarily imagery. The diminishing areal extent of the Aral Sea and Lake Chad derives from recent satellite imagery. Ranked by relative importance, coordinating with river ranking. Includes name attributes. Natural Earth generated this data primarily using the CIA's World Databank 2 datasets which were completed in 1977.

Detailed Rivers Polyline Global Natural Earth (swera:ref_detailed_rivers)

Rivers primarily derived from World Data Bank 2. Double line rivers in WDB2 were digitized to created single line drainages. All rivers received manual smoothing and position adjustments to fit shaded relief generated from SRTM Plus elevation data, which is more recent and (presumably) more accurate. Lake centerlines obtained by manually drawing connecting segments in reservoirs. When available, Admin 0 and 1 political boundaries in reservoirs serve as the lake centerlines. Ranked by relative importance. Includes name and line width attributes for creating tapered drainages. Natural Earth generated this data primarily using the CIA's World Databank 2 datasets which were completed in 1977.

Major Lakes Polygon Global ESRI 2008 (swera:ref_lakes)

World Lakes represents the major lakes and inland seas within the world.

ref_lakes (test_ws:ref_lakes)

Major Rivers Polygon Global ESRI 2008 (swera:ref_rivers)

World Rivers represents the major rivers within the world.

ref_rivers (test_ws:ref_rivers)

Incentive Regions (workinglayers:regions)

regions_disp_1 (workinglayers:regions_disp_1)

regions_style1 (workinglayers:regions_style1)

regions_style2 (workinglayers:regions_style2)

regions_style3 (workinglayers:regions_style3)

regions_style4 (workinglayers:regions_style4)

NREL Rhode Island 50m Wind Resource (data_res:rhodeisl_50mwind)

Abstract: Annual average wind resource potential for the state of Rhode Island at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. Source: AWS TrueWind/NREL

slope_reclass (irena:slope_reclass)

slp_gt30_dis (gt_prospector:slp_gt30_dis)

NULL

Solar DNI Polygon Northern Africa SMA (irena:sma_dni)

Solar DNI resources of Northern Africa.

Solar DNI Polygon Northern Africa SMA 1991-2005 (irena:sma_match_1991-2005_dni)

Solar DNI Resource of Northern Africa.

Solar GHI Polygon Northern Africa SMA 1991-2005 (irena:sma_match_1991-2005_ghi)

Solar GHI resource for Northern Africa.

RE_Atlas Hydro (FSPS) (re_atlas:smallhydro)

Long-term hydroelectric potential is drawn directly from a GIS-based study by INL: Feasibility Assessment of the Water Energy Resources of the United States for New Low Power and Small Hydro Classes of Hydroelectric Plants, January 2006.

smu_thermal (gt_prospector:smu_thermal)

Temperature vs. depth (O&G wells): SMU thermal database, Source: Southern Methodist University (SMU) (http://smu.edu/geothermal/georesou/usa.htm)

smu_wells (gt_prospector:smu_wells)

Geochemical Data: SMU Well Data bases, Source: Southern Methodist University (SMU) (http://smu.edu/geothermal/georesou/usa.htm)

DEM GeoTIFF East Hemisphere Geomodel 2000-2006 (irena:srtm30_e_tiled)

Elevation (SRTM-30) Shuttle Radar Topography Mission version 2 © 2000-2006 SRTM Mission SRTM30 plus © 2008 Joseph J. Becker, David T. Sandwell CleanTOPO2 © 2008 Tom Patterson Post-processing and cartography by GeoModel Solar Resolution: 00:00:30 Terrain maps show the elevation above sea level on the land and depth of the ocean and sea bottom. The slope inclination and azimuth are calculated on-the-fly. The map is developed from Shuttle Radar Topography Mission (SRTM) and SRTM Water Body Dataset (SWBD). The detailed SRTM3 data with grid resolution of 3 arcsec (~90 m at the equator) are available between the latitudes 60N and 50S, which represents the most of the continental parts of the Earth. For regions north from 60N and south from 50S, only the elevation data from GTOPO30 (SRTM30) are available. The original grid resolution of the GTOPO30 dataset is 30 arcsec (~1000 m at the equator). The bathymetry has been created from two different sources: SRTM30 plus dataset and CleanTOPO2 dataset, in which a few inconsitencies of SRTM30 plus are resolved. The fusion of these datasets has been done and the new map of bathymetry has been created. Terrain shading has been derived from GTOPO30 and SRTM-3 data.

DEM GeoTIFF West Hemisphere Geomodel 2000-2006 (irena:srtm30_w_tiled)

Elevation (SRTM-30) Shuttle Radar Topography Mission version 2 © 2000-2006 SRTM Mission SRTM30 plus © 2008 Joseph J. Becker, David T. Sandwell CleanTOPO2 © 2008 Tom Patterson Post-processing and cartography by GeoModel Solar Resolution: 00:00:30 Terrain maps show the elevation above sea level on the land and depth of the ocean and sea bottom. The slope inclination and azimuth are calculated on-the-fly. The map is developed from Shuttle Radar Topography Mission (SRTM) and SRTM Water Body Dataset (SWBD). The detailed SRTM3 data with grid resolution of 3 arcsec (~90 m at the equator) are available between the latitudes 60N and 50S, which represents the most of the continental parts of the Earth. For regions north from 60N and south from 50S, only the elevation data from GTOPO30 (SRTM30) are available. The original grid resolution of the GTOPO30 dataset is 30 arcsec (~1000 m at the equator). The bathymetry has been created from two different sources: SRTM30 plus dataset and CleanTOPO2 dataset, in which a few inconsitencies of SRTM30 plus are resolved. The fusion of these datasets has been done and the new map of bathymetry has been created. Terrain shading has been derived from GTOPO30 and SRTM-3 data.

DEM GeoTIFF Eastern Africa Geomodel 2000-2006 (irena:srtm_eapp2)

Elevation (SRTM-30) Shuttle Radar Topography Mission version 2 © 2000-2006 SRTM Mission SRTM30 plus © 2008 Joseph J. Becker, David T. Sandwell CleanTOPO2 © 2008 Tom Patterson Post-processing and cartography by GeoModel Solar Includes only Eastern African countries. Resolution: 00:00:30 Terrain maps show the elevation above sea level on the land and depth of the ocean and sea bottom. The slope inclination and azimuth are calculated on-the-fly. The map is developed from Shuttle Radar Topography Mission (SRTM) and SRTM Water Body Dataset (SWBD). The detailed SRTM3 data with grid resolution of 3 arcsec (~90 m at the equator) are available between the latitudes 60N and 50S, which represents the most of the continental parts of the Earth. For regions north from 60N and south from 50S, only the elevation data from GTOPO30 (SRTM30) are available. The original grid resolution of the GTOPO30 dataset is 30 arcsec (~1000 m at the equator). The bathymetry has been created from two different sources: SRTM30 plus dataset and CleanTOPO2 dataset, in which a few inconsitencies of SRTM30 plus are resolved. The fusion of these datasets has been done and the new map of bathymetry has been created. Terrain shading has been derived from GTOPO30 and SRTM-3 data.

state_geothermal_ (gt_prospector:state_geothermal_)

This coverage shows the regions favorable for the discovery and shallow depth (less than 1000m) of thermal water of sufficient temperature for direct-heat applications. It is probable that only small areas of this region are truly underlain by such thermal water; the region represents that part of the state that deserves exploration for thermal areas. The region is defined on the basis of various geothermal and tectonic phenomena such as locations of thermal wells and springs, above-normal heat flow, youthful volcanism, mineralization, and seismicity

stateown_region_surface (gt_prospector:stateown)

This dataset represents Surface and Mineral Ownership for the state of Wyoming. This dataset is intented to represent the ownership information on Master Title Plats(MTPs). Surface ownership will be identified by the Agency of Juridiction, when the surface is Federal. All other parcels will be identified as either Private or State. Private parcels do not identify the name of the individual owner. Mineral ownership identifies only the Federal interest.

stateown_region_fed_min (gt_prospector:stateown_region_fed_min)

This dataset represents Surface and Mineral Ownership for the state of Wyoming. This dataset is intented to represent the ownership information on Master Title Plats(MTPs). Surface ownership will be identified by the Agency of Juridiction, when the surface is Federal. All other parcels will be identified as either Private or State. Private parcels do not identify the name of the individual owner. Mineral ownership identifies only the Federal interest.

stateown_region_surface (gt_prospector:stateown_region_surface)

This dataset represents Surface and Mineral Ownership for the state of Wyoming. This dataset is intented to represent the ownership information on Master Title Plats(MTPs). Surface ownership will be identified by the Agency of Juridiction, when the surface is Federal. All other parcels will be identified as either Private or State. Private parcels do not identify the name of the individual owner. Mineral ownership identifies only the Federal interest.

USA Population (topp:states)

This is some census data on the states.

surfgeol_500k (gt_prospector:surfgeol_500k)

This dataset represents surficial geology of Wyoming at 1:500,000-scale. The layer contains 577 separate surficial feature (landforms) and deposit descriptions present on the surface in the state. Compiled from aerial photography and existing maps this layer represents the first comprehensive surficial geology map of Wyoming.

Wind Grid 200m-25km United States NREL (swera:swera_us_wind_hi_res)

Wind resource of the United States. Resolution of dataset ranges from 200m up to 25km depending on location. Source: NREL

Solar TILT Polygon Turkey 10km GeoModel 2011 (swera:tilt_geomodel_high)

SRID 4326 of two available coordinate systems. TILT 10km Resolution by GeoModel for Turkey. Units: kWh/m sq. per day, Source: GeoModel

Solar TILT Polygon Turkey 10km GeoModel 2011 (swera:tilt_geomodel_high_900913)

SRID 900913 of two available coordinate systems. TILT 10km Resolution by GeoModel for Turkey. Units: kWh/m sq. per day, Source: GeoModel

Solar TILT Polygon 10km Brazil INPE 2008 (swera:tilt_inpe_high)

SRID 4326 of two available coordinate systems. Latitude tilted solar radiation in kWh/m2/day for 1 year organized into cells with 10km x 10km. (Purpose): The BRASIL-SR model and the SPRING software (both developed by INPE -National Institute for Space Research) were used to produce the dataset and SHAPE files (Supplemental Information): The assessment of reliability levels of the BRASIL-SR model were performed through the evaluation of the deviations shown by the estimated values for solar radiation flux vis-à-vis the values measured at the surface (ground truth). This evaluation was done in two phases. The first phase consisted in an inter-comparison between the core radiation transfer models adopted by the SWERA Project to map the solar energy in the various countries participating in the project. The HELIOSAT model took part in this phase like benchmark due to its employment to map solar energy resources incountries from European Union. In the second phase, the solar flux estimates providedby the BRASIL-SR model were compared with measured values acquired at several solarimetric stations spread along the Brazilian territory

Solar TILT Polygon 10km Brazil INPE 2008 (swera:tilt_inpe_high_900913)

SRID 900913 of two available coordinate systems. Latitude tilted solar radiation in kWh/m2/day for 1 year organized into cells with 10km x 10km. (Purpose): The BRASIL-SR model and the SPRING software (both developed by INPE -National Institute for Space Research) were used to produce the dataset and SHAPE files (Supplemental Information): The assessment of reliability levels of the BRASIL-SR model were performed through the evaluation of the deviations shown by the estimated values for solar radiation flux vis-à-vis the values measured at the surface (ground truth). This evaluation was done in two phases. The first phase consisted in an inter-comparison between the core radiation transfer models adopted by the SWERA Project to map the solar energy in the various countries participating in the project. The HELIOSAT model took part in this phase like benchmark due to its employment to map solar energy resources incountries from European Union. In the second phase, the solar flux estimates providedby the BRASIL-SR model were compared with measured values acquired at several solarimetric stations spread along the Brazilian territory

Solar TILT Polygon 40km Brazil and South America INPE 1995-2005 (swera:tilt_inpe_mod)

SRID 4326 of two available coordinate systems. Photosynthetically active radiation in kWh/m2/day for 1 year organized into cells with 40km x 40km. (Purpose): The BRASIL-SR model and the SPRING software (both developed by INPE - National Institute for Space Research) were used to produce the dataset and SHAPE files (Supplemental Information): The assessment of reliability levels of the BRASIL-SR model were performed through the evaluation of the deviations shown by the estimated values for solar radiation flux vis-à-vis the values measured at the surface (ground truth). This evaluation was done in two phases. The first phase consisted in an inter-comparison between the core radiation transfer models adopted by the SWERA Project to map the solar energy in the various countries participating in the project. The HELIOSAT model took part in this phase like benchmark due to its employment to map solar energy resources in countries from European Union. In the second phase, the solar flux estimates provided by the BRASIL-SR model were compared with measured values acquired at several solarimetric stations spread along the Brazilian territory.

Solar TILT Polygon 40km Brazil and South America INPE 1995-2005 (swera:tilt_inpe_mod_900913)

SRID 900913 of two available coordinate systems. Photosynthetically active radiation in kWh/m2/day for 1 year organized into cells with 40km x 40km. (Purpose): The BRASIL-SR model and the SPRING software (both developed by INPE - National Institute for Space Research) were used to produce the dataset and SHAPE files (Supplemental Information): The assessment of reliability levels of the BRASIL-SR model were performed through the evaluation of the deviations shown by the estimated values for solar radiation flux vis-à-vis the values measured at the surface (ground truth). This evaluation was done in two phases. The first phase consisted in an inter-comparison between the core radiation transfer models adopted by the SWERA Project to map the solar energy in the various countries participating in the project. The HELIOSAT model took part in this phase like benchmark due to its employment to map solar energy resources in countries from European Union. In the second phase, the solar flux estimates provided by the BRASIL-SR model were compared with measured values acquired at several solarimetric stations spread along the Brazilian territory.

Solar TILT Polygon Global NASA 2008 (swera:tilt_nasa_low)

SRID 4326 of two available coordinate systems. Latitude Tilt Irradiance NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Jan 2008) 22-year Monthly & Annual Average (July 1983 - June 2005). Parameter: Latitude Tilt Radiation (kWh/m2/day) Internet: http://eosweb.larc.nasa.gov/sse/ Note 1: SSE Methodology & Accuracy sections online Note 2: Lat/Lon values indicate the lower left corner of a 1x1 degree region. Negative values are south and west; positive values are north and east. Boundaries of the -90/-180 region are -90 to -89 (south) and -180 to -179 (west). The last region, 89/180, is bounded by 89 to 90 (north) and 179 to 180 (east). The mid-point of the region is +0.5 added to the the Lat/Lon value. These data are regional averages; not point data. Created: March 17, 2008 See the NASA Surface meteorology and Solar Energy (SSE) web site at http://eosweb.larc.nasa.gov/sse/. The source data was downloaded from the SSE website at Data Retrieval: Meteorology and Solar Energy > Global data sets as text files. The tabular data was then converted to the shapefile format.

Solar TILT Polygon Multiple Countries 40km NREL 1985-1991 (swera:tilt_nrel_mod)

SRID 4326 of two available coordinate systems. These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. Existing ground measurement stations are used to validate the data where possible. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties associated with meteorological input to the model. The local cloud cover can vary significantly even within a single grid cell as a result of terrain effects and other microclimate influences. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain.

Solar TILT Polygon Multiple Countries 40km NREL 1985-1991 (swera:tilt_nrel_mod_900913)

SRID 900913 of two available coordinate systems. These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. Existing ground measurement stations are used to validate the data where possible. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties associated with meteorological input to the model. The local cloud cover can vary significantly even within a single grid cell as a result of terrain effects and other microclimate influences. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain.

Solar TILT Polygon Multiple Countries 10km SUNY 1998-2005 (swera:tilt_suny_high)

SRID 4326 of two available coordinate systems. These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 10 km by 10 km in size. The solar resource value is represented as kilowatt-hours per square meter per day for each month. The data were developed from the State University of New York's (SUNY) GOES satellite solar model. This model uses information on hourly satellite observed visible irradiance, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total of the normal or beam insolation falling on a tracking concentrator pointed directly at the sun. Existing ground measurement stations are used to validate the data where possible. The modeled values are accurate to approximately 12% of a true measured value within the grid cell due to the uncertainties associated with meteorological input to the model. The local cloud cover can vary significantly even within a single grid cell as a result of terrain effects and other microclimate influences. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain.

Solar TILT Polygon Multiple Countries 10km SUNY 1998-2005 (swera:tilt_suny_high_900913)

SRID 900913 of two available coordinate systems. These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 10 km by 10 km in size. The solar resource value is represented as kilowatt-hours per square meter per day for each month. The data were developed from the State University of New York's (SUNY) GOES satellite solar model. This model uses information on hourly satellite observed visible irradiance, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total of the normal or beam insolation falling on a tracking concentrator pointed directly at the sun. Existing ground measurement stations are used to validate the data where possible. The modeled values are accurate to approximately 12% of a true measured value within the grid cell due to the uncertainties associated with meteorological input to the model. The local cloud cover can vary significantly even within a single grid cell as a result of terrain effects and other microclimate influences. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain.

Transmission Lines Afghanistan 2006 kV (gst:tline_afghanistan)

Source: digitized from Power and Gas Grid Map of South Asia (2006) Spatial resolution/Scale: Not stated. Description: Utility electric transmission lines.

Transmission Line Buffers Afghanistan 2km - 20km (gst:tline_afghanistan_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: digitized from Power and Gas Grid Map of South Asia (2006)

Transmission Lines Bangladesh 1996 kV (gst:tline_bangladesh)

Source: Power Transmission Lines, Bangladesh Power Development Board (1996-1997)) Spatial resolution/Scale: 1:3,000,000 Description: Electric power transmission lines of Bangladesh.

Transmission Line Buffers Bangladesh 2km - 20km (gst:tline_bangladesh_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: Power Transmission Lines, Bangladesh Power Development Board

Transmission Lines Bhutan kV (gst:tline_bhutan)

Source: Bhutan Department of Energy (Date Unknown) Spatial resolution/Scale: Unknown Description: Electric power transmission lines of Bhutan.

Transmission Line Buffers Bhutan 2km - 20km (gst:tline_bhutan_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: Bhutan Department of Energy (Date Unknown)

tline_brazil (gst:tline_brazil)

Source: ELETROBRAS (Brazilian Electric Central Inc.), Ministry of Mines and Energy (2004) Spatial resolution/Scale: Unknown Description: Electric power transmission lines 69 - 750 kV.

Transmission Line Buffers Brazil 2km - 20km (gst:tline_brazil_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: ELETROBRAS (Brazilian Electric Central Inc.), Ministry of Mines and

Transmission Lines Cambodia 2013 kV (gst:tline_cambodia)

Source: OpenDevelopment Cambodia hydropower transmission dataset (2013) Spatial resolution/Scale: Not stated. Description: Utility electric transmission lines.

Transmission Line Buffers Cambodia 2km - 20km (gst:tline_cambodia_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: OpenDevelopment Cambodia hydropower transmission dataset (2013)

Transmission Lines Elsalvador 2004 kV (gst:tline_elsalvador)

Source: Minesterio de Medio Ambiente y Recursos Naturales (received Jun 2004) Spatial resolution/Scale: Unknown Description: Electric power transmission lines of El Salvador.

Transmission Line Buffers Elsalvador 2km - 20km (gst:tline_elsalvador_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: Minesterio de Medio Ambiente y Recursos Naturales (received Jun 2004)

Transmission Lines Ghana 2005 kV (gst:tline_ghana)

Source: Data collected for NREL by the Ghana Energy Commission - original source not stated (received Nov. 2005) Spatial resolution/Scale: Unknown Description: Electric power transmission lines.

Transmission Line Buffers Ghana 2km - 20km (gst:tline_ghana_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: Data collected for NREL by the Ghana Energy Commission - original source

Transmission Lines Guatemala 2001 kV (gst:tline_guatemala)

Source: Ministerio de Agricultura, Ganaderia y Alimentacion (Jun 2001) Spatial resolution/Scale: 1:250,000 Description: Electric power transmission lines of Guatemala.

Transmission Line Buffers Guatemala 2km - 20km (gst:tline_guatemala_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: Ministerio de Agricultura, Ganaderia y Alimentacion (Jun 2001)

Transmission Lines Hebei (gst:tline_hebei)

Source: Unknown Spatial resolution/Scale: Unknown Description: Electric power transmission lines of Hebei.

Transmission Line Buffers Hebei 2km - 20km (gst:tline_hebei_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets.

Transmission Lines Honduras 2003 kV (gst:tline_honduras)

Source: Oficina de Electrification Social (received Aug 2003) Spatial resolution/Scale: Unknown Description: Electric power transmission lines of Honduras.

Transmission Line Buffers Honduras 2km - 20km (gst:tline_honduras_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: Oficina de Electrification Social (received Aug 2003)

Transmission Lines India 2006 (gst:tline_india)

Source: Power and Gas Grid Map of South Asia (2006) prepared for USAID under SARI/Energy program. Spatial resolution/Scale: Unknown Description: Electric power transmission lines of India.

Transmission Line Buffers India 2km - 20km (gst:tline_india_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: Power and Gas Grid Map of South Asia (2006) prepared for USAID

Transmission Lines Kenya kV (gst:tline_kenya)

Source: A variety of sources were consulted, including documents and maps from national utilities, regional power pools and the World Bank. Spatial resolution/Scale: Unknown Description: Data for medium and high voltage transmission lines were compiled for the AICD study led by the World Bank. A variety of sources were consulted, including regional power pool documents and maps from World Bank project documents. Locations are approximate, intended to reflect main connections, and are not representative of actual "path on the ground". The following attributes were collected: VOLTAGE_KV: Transmission line capacity in kilovolts, FROM_NM: Name of the locality where the link starts, TO_NM: Name of the locality where the link ends, STATUS: Status of link (Existing, Planned, Proposed, Under Study), SOURCES: Source of location or attribute information, PROJECT_NM: Name of project (planned links). Transmission line thickness relates to capacity kV capacity of the line.

Transmission Line Buffers Kenya 2km - 20km (gst:tline_kenya_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: A variety of sources were consulted, including documents and maps from national utilities,

Transmission Lines Nepal kV (gst:tline_nepal)

Source: Nepal Alternative Energy Promostion Centre - Energy Sector Assistance Programme Spatial resolution/Scale: Unknown Description: Electric transmission lines in Nepal.

Transmission Line Buffers Nepal 2km - 20km (gst:tline_nepal_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: Nepal Alternative Energy Promostion Centre - Energy Sector

Transmission Lines Nicaragua 2004 kV (gst:tline_nicaragua)

Source: Comision Nacional de Energia (received Mar 2004) Spatial resolution/Scale: Unknown Description: Electric power transmission lines of Nicaragua.

Transmission Line Buffers Nicaragua 2km - 20km (gst:tline_nicaragua_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: Comision Nacional de Energia (received Mar 2004)

Transmission Lines Oaxaca 2003 (gst:tline_oaxaca)

Source: Instituto de Investigaciones Electricas (received April 2003) Spatial resolution/Scale: Unknown Description: Electric power transmission lines of Oaxaca.

Transmission Line Buffers Oaxaca 2km - 20km (gst:tline_oaxaca_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: Instituto de Investigaciones Electricas (received April 2003)

Transmission Lines Pakistan 2006 kV (gst:tline_pakistan)

Source: digitized from Power and Gas Grid Map of South Asia (2006) Spatial resolution/Scale: Not stated. Description: Utility electric transmission lines.

Transmission Line Buffers Pakistan 2km - 20km (gst:tline_pakistan_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: digitized from Power and Gas Grid Map of South Asia (2006)

Transmission Lines Philippines 2006 kV (gst:tline_philippines)

Source: Digitized from GENI Philippine Power Grid Map 2006 Spatial resolution/Scale: Not stated. Description: Utility electric transmission lines. Line size is representative of lower kV capacity (thin line) to higher kV capacity (wide line).

Transmission Line Buffers Philippines 2km - 20km (gst:tline_philippines_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: Digitized from GENI Philippine Power Grid Map 2006

Transmission Lines Srilanka 2003 kV (gst:tline_srilanka)

Source: received from Ceylon Electricity Board, May 2003 Spatial resolution/Scale: Unknown Description: Electric power transmission lines of Bhutan.

Transmission Line Buffers Srilanka 2km - 20km (gst:tline_srilanka_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: received from Ceylon Electricity Board, May 2003

Transmission Lines Turkey 2009 kV (gst:tline_turkey)

Source: Government of Turkey, received 2009 Spatial resolution/Scale: Unknown Description: Electric power transmission lines of Turkey.

Transmission Line Buffers Turkey 2km - 20km (gst:tline_turkey_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: Government of Turkey, received 2009

Transmission Lines Vietnam 2010 kV (gst:tline_vietnam)

Source: Digitized from JETRO National Energy Grid Map (2010) Spatial resolution/Scale: Not Stated. Description: Utility electric transmission lines.

Transmission Line Buffers Vietnam 2km - 20km (gst:tline_vietnam_buffers)

Transmission Line buffers. Distances include 2km, 5km, 10km, 15km, and 20km from nearest transmission lines. Buffers generated using transmission lines datasets from the following source: Digitized from JETRO National Energy Grid Map (2010)

NREL Tennessee 50m Wind Resource (data_res:tn_50mwind)

Abstract: Annual average wind resource potential for the state of Tennessee at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. Source: AWS TrueWind/NREL

NREL Texas 50m Wind Resource (data_res:tx_50m_wind)

NREL Lower 48 DNI 10km Resolution 1998 to 2005 (data_res:us9805_dni)

Abstract: Monthly and annual average direct normal irradiance for Hawaii and the contiguous United States. Supplemental Information: 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. Source: SUNY Albany and NREL

NREL Lower 48 GHI 10km Resolution 1998 to 2005 (data_res:us9805_ghi)

Abstract: Monthly and annual average global horizontal irradiance for Hawaii and the contiguous United States. Supplemental Information: 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. Atmospheric water vapor, trace gases, and aerosols are derived from a variety of sources. 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 available 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. Source: SUNY Albany and NREL

NREL Lower 48 LATILT 10km Resolution 1998 to 2005 (data_res:us9805_latilt)

Abstract: Monthly and annual average latitude equals tilt irradiance for Hawaii and the contiguous United States. Supplemental Information: 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. Source: SUNY Albany and NREL

NREL Lower 48 and Hawaii DNI 10km Resolution 1998 to 2009 (data_res:us9809_dni_updated)

Abstract: Monthly and annual average solar resource potential for 48 Contiguous United States. Supplemental Information: 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. Source: NREL

NREL Lower 48 and Hawaii GHI 10km Resolution 1998 to 2009 (data_res:us9809_ghi_updated)

Abstract: Monthly and annual average solar resource potential for 48 Contiguous United States. Supplemental Information: 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. 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 available at a 10 km resolution. As a result, it is believed that the modeled values are accurate to approximately 9% 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. Source: NREL

NREL Lower 48 and Hawaii LATILT 10km Resolution 1998 to 2009 (data_res:us9809_latilt_updated)

Abstract: Monthly and annual average solar resource potential for 48 Contiguous United States. Supplemental Information: 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. The procedures for converting the collector at latitude tilt are described in Marion and Wilcox (1994). 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 10% of a true measured value within the grid cell. Due to terrain effects and other micoclimate 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. Source: NREL

RE_Atlas Concentrated Solar Power (re_atlas:us_csp_national)

This data provides monthly average and annual average daily total solar resource (DNI) averaged over surface cells of 0.1 degrees in both latitude and longitude, or about 10 km in size. The insolation values represent the resource available to concentrating systems that track the sun throughout the day. The data are created using the SUNY Satellite Solar Radiation model (Perez, et.al., 2002). The data are averaged from hourly model output over 8 years (1998-2009). 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. The direct beam radiation is then calculated using the atmospheric water vapor, trace gases, and aerosols, which are derived from a variety of sources. Where possible, existing ground measurement stations are used to validate the data. Source: Perez-SUNY/NREL, 2007 Link: http://www.nrel.gov/gis

Re_Atlas Geothermal (EGS) (re_atlas:us_geothermal)

Map does not include shallow Deep Enhanced Geothermal Systems (EGS) resources located near hydrothermal sites or USGS assessment of undiscovered hydrothermal resources. Source data for deep EGS includes temperature at depth from 3 to 10 km provided by Southern Methodist University Geothermal Laboratory (Blackwell & Richards, 2009) and analyses (for regions with temperatures ≥150°C) performed by NREL (2009). N/A regions have temperatures less than 150°C at 10 km depth and were not assessed for deep EGS potential. Temperature at depth data for deep EGS in Alaska and Hawaii not available. Qualitative classes are based on temperature and depth ranges. Temperature values are not exclusive to any single class and may be located at different depths from one class to the next. Classes express approximate favorability for geothermal resource, with a lower number indicating the possibility of a higher potential value.

RE_Atlas Solar Photovoltaic (re_atlas:us_solar_all_120512)

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. The insolation values represent the resource available to fixed flat plate system tilted towards the equator at an angle equal to the latitude. The data are created using the SUNY Satellite Solar Radiation model (Perez, et.al., 2002). The data are averaged from hourly model output over 8 years (1998-2009). 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. The direct beam radiation is then calculated using the atmospheric water vapor, trace gases, and aerosols, which are derived from a variety of sources. Where possible, existing ground measurement stations are used to validate the data. Source: Perez-SUNY/NREL, 2007 The data for Alaska was created using the Climatological Solar Radiation Model (Maxwell, George and Wilcox, 1998; George and Maxwell, 1999). This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere, to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. The cloud cover data used as input to the CSR model are an 8-year histogram (1985 - 1992) of monthly average cloud fraction provided for grid cells of approximately 40km x 40km in size. Thus, the spatial resolution of the CSR model output is defined by this database. The data were obtained from the National Climatic Data Center in Asheville, North Carolina, and were developed from the U.S. Air Force Real Time Nephanalysis (RTNEPH) program. Atmospheric water vapor, trace gases, and aerosols are derived from a variety of sources, as summarized in the references. The procedures for converting the modeled global horizontal insolation into the insolation received by a flat plate collector at latitude tilt are described in Marion and Wilcox (1994).

RE_Atlas Solar Photovoltaic (irena:us_solar_all_120512)

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. The insolation values represent the resource available to fixed flat plate system tilted towards the equator at an angle equal to the latitude. The data are created using the SUNY Satellite Solar Radiation model (Perez, et.al., 2002). The data are averaged from hourly model output over 8 years (1998-2009). 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. The direct beam radiation is then calculated using the atmospheric water vapor, trace gases, and aerosols, which are derived from a variety of sources. Where possible, existing ground measurement stations are used to validate the data. Source: Perez-SUNY/NREL, 2007 The data for Alaska was created using the Climatological Solar Radiation Model (Maxwell, George and Wilcox, 1998; George and Maxwell, 1999). This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere, to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. The cloud cover data used as input to the CSR model are an 8-year histogram (1985 - 1992) of monthly average cloud fraction provided for grid cells of approximately 40km x 40km in size. Thus, the spatial resolution of the CSR model output is defined by this database. The data were obtained from the National Climatic Data Center in Asheville, North Carolina, and were developed from the U.S. Air Force Real Time Nephanalysis (RTNEPH) program. Atmospheric water vapor, trace gases, and aerosols are derived from a variety of sources, as summarized in the references. The procedures for converting the modeled global horizontal insolation into the insolation received by a flat plate collector at latitude tilt are described in Marion and Wilcox (1994).

us_solar_simple (re_atlas:us_solar_simple)

simplestates (workinglayers:us_states_simple)

Wind Power Class 50m Alaska NREL (swera:us_wpc_2_8bit21)

GeoTIFF of Wind Power Class values for the state of Alaska. This map shows the annual average wind power estimates at a height of 50 meters. It is a combination of high resolution and low resolution datasets produced by NREL and other organizations. The data was screened to eliminate areas unlikely to be developed onshore due to land use or environmental issues. In many states, the wind resource on this map is visually enhanced to better show distribution on ridge crests and other features.

Wind Power Class 50m Hawaii NREL (swera:us_wpc_2_8bit_HI)

GeoTIFF of Wind Power Class values for Hawaii. This map shows the annual average wind power estimates at a height of 50 meters. It is a combination of high resolution and low resolution datasets produced by NREL and other organizations. The data was screened to eliminate areas unlikely to be developed onshore due to land use or environmental issues. In many states, the wind resource on this map is visually enhanced to better show distribution on ridge crests and other features.

Wind Power Class 50m Continental US NREL (swera:us_wpc_2_8bit_l48)

GeoTIFF of the Wind Power Class values for the continental United States. This map shows the annual average wind power estimates at a height of 50 meters. It is a combination of high resolution and low resolution datasets produced by NREL and other organizations. The data was screened to eliminate areas unlikely to be developed onshore due to land use or environmental issues. In many states, the wind resource on this map is visually enhanced to better show distribution on ridge crests and other features.

NREL Utah 50m Wind Resource (data_res:utah_50mwind)

Abstract: Annual average wind resource potential for the state of Utah, United States at a 50 meter height. This dataset will be replaced when the southwest region has been completed, and the data may change when this region has been completed. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 17, datum WGS 84 projection system. Source: AWS TrueWind/NREL

Biomass Scenario Model WFS (BSM_KDF_v0:v0_2_for_wfs)

Pathway-Diversity-Focused Incentives scenario (BSM_KDF_v0:v0_diversity)

Biomass Scenario Model, Study 29; Feedstock Production [ton/yr] & Biofuel Production [gal/yr] for each year 2015,2020, 2025, 2030; National Renewable Energy Laboratory, 2013; Pathway-diversity-focused incentives scenario utilizes incentives that lead to multiple biomass-to-hydrocarbon fuel pathways gaining market share in addition to the ethanol industry retaining some market share without exceeding 10 billion USD in annual spending . The incentives are triggered to promote as many pathways as reasonably possible.

Ethanol-Focused Incentives scenario (BSM_KDF_v0:v0_ethanol)

Biomass Scenario Model, Study 29; Feedstock Production [ton/yr] & Biofuel Production [gal/yr] for each year 2015,2020, 2025, 2030; National Renewable Energy Laboratory, 2013; Ethanol-focused incentives scenario provides moderate support to the starch and cellulosic ethanol industries. Focus is on accelerating industrial learning at an early stage through FCI and government loan guarantees for pioneer-scale cellulosic ethanol biorefineries. The starch industry receives a 0.45 USD/gallon point-of-production incentive until 2012. The cellulosic ethanol industry receives a point-of-production incentive of 2.65 USD/gallon for the first one billion gallons of ethanol production, after which the level drops to 0.15 USD/gallon. The point-of-use incentive and the distribution and storage incentive are applied equally to both the starch and cellulosic ethanol industries.

Biomass Scenario Model WFS (BSM_KDF_v0:v0_for_wfs)

Biomass Scenario Model, Study 29; National Renewable Energy Laboratory, 2013; Minimal Incentives scenario, Equal Access to Incentives scenario, Ethanol-Focused Incentives scenario, Output-Focused Incentives scenario, Pathway-Diversity-Focused Incentives scenario, Point-of-Production-Focused Incentives scenario; Feedstock Production [ton/yr] & Biofuel Production [gal/yr] for each year 2015, 2020, 2025, 2030;

v0_for_wfs_limited (BSM_KDF_v0:v0_for_wfs_limited)

Minimal Incentives scenario (BSM_KDF_v0:v0_minimal)

Biomass Scenario Model, Study 29; Feedstock Production [ton/yr] & Biofuel Production [gal/yr] for each year 2015,2020, 2025, 2030; National Renewable Energy Laboratory, 2013; Minimal incentives scenario presents a case in which there are no substantive production incentives for biofuels. The point-of-production incentive is 0.45 USD/gallon until 2012, after which there is no economic support.

Output-Focused Incentives scenario (BSM_KDF_v0:v0_outputfocus)

Biomass Scenario Model, Study 29; Feedstock Production [ton/yr] & Biofuel Production [gal/yr] for each year 2015,2020, 2025, 2030; National Renewable Energy Laboratory, 2013; Output-focused incentives scenario maximizes biofuel production without exceeding 10 billion USD in annual costs. Support is directed toward the construction of pioneer- and commercial-scale refineries by providing high levels of FCI and loan guarantee support. This scenario incentivizes one biomass-to-hydrocarbon biofuel production technology in an effort to maximize its fuel production targeting the most technologically attractive biofuel pathway.

v0 Output Focus 2030 (BSM_KDF_v0:v0_outputfocus_2030)

Test data for WMS without time=?

Point-of-Production-Focused Incentives scenario (BSM_KDF_v0:v0_pps)

Biomass Scenario Model, Study 29; Feedstock Production [ton/yr] & Biofuel Production [gal/yr] for each year 2015,2020, 2025, 2030; National Renewable Energy Laboratory, 2013; Point-of-production-focused incentives scenario is a case where a low level of production incentives is available. Point-of-production incentive of 0.45 USD/gallon is applied across all biofuels. Starch-based ethanol is subsidized for one simulation year (2011). All other renewable fuels are subsidized for the duration of the simulation.

Biomass Production Over Time (BSM_KDF_v0:v0_production_sum_by_run)

Equal-Access-to-Incentives scenario (BSM_KDF_v0:v0_rfs2)

Biomass Scenario Model, Study 29; Feedstock Production [ton/yr] & Biofuel Production [gal/yr] for each year 2015, 2020, 2025, 2030; National Renewable Energy Laboratory, 2013; Equal-access-to-incentives scenario is constructed so that all cellulosic biofuel production technologies have access to the same incentives at the same levels. Qualifying biofuel technologies have access to incentives regardless of their economic viability and attractiveness to investors. Incentives are set to very high levels for the first decade after which all but the point-of-production incentive is turned off.

NREL Vermont 50m Wind Resource (data_res:vermont_50mwind)

Abstract: Annual average wind resource potential for the state of Vermont at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. Source: AWS TrueWind/NREL

volcanx020 (gt_prospector:volcanx020)

US volcanoes: Volcano dataset, Source: U.S. Geological Survey - Central Region (http://dds.cr.usgs.gov/pub/data/nationalatlas/volcanx020.tar.gz)

wa_geologic_map (gt_prospector:wa_geologic_map)

These data contain 1:100,000-scale polygons defining the extent and label of each geologic unit. The label is an abbreviation that represents the age, lithology, and name of a geologic unit. This feature class is part of a geodatabase that contains statewide 1:100,000-scale geology data for Washington State. Other feature classes are age_date_100k, contact_100k, dike_100k, dike_swarm_line_100k, dike_swarm_poly_100k, fault_100k, fold_100k, geologic_unit_point_100k, line_100k, structure_100k, and volcanic_vent_100k.

RE_Atlas Wave Power Density (re_atlas:wave_power_density)

Wave power density is the calculated kilowatts per meter of wave crest width at any given water depth. Equation A-6 of Appendix A in the full report. Source: The Wave Energy Resource Assessment project is a joint venture between NREL, EPRI, and Virginia Tech. EPRI is the prime contractor, Virginia Tech is responsible for development of the models and estimating the wave resource, and NREL serves as an independent validator and also develops the final GIS-based display of the data. For complete details regarding this study please read the full report, available here: http://en.openei.org/datasets/node/884

RE_Atlas Wind Power Class - Onshore (re_atlas:wind_class_100_dissolve)

Wind: 2008 DOE report, 20% Wind by 2030. p. 8. The nation has more than 8,000GW of available land-based wind resources. Potential capacity estimated assuming 5 MW/km2. The onshore wind data are based on 50m height above surface. The data only applies to areas of low surface roughness (i.e. grassy plains), and excludes areas with slopes greater than 20%. For areas of high surface roughness (i.e. forests), the values shown may need to be reduced by one or more power classes.

RE_Atlas Wind Power Class - Onshore (re_atlas:wind_class_100km_grid)

Wind: 2008 DOE report, 20% Wind by 2030. p. 8. The nation has more than 8,000GW of available land-based wind resources. Potential capacity estimated assuming 5 MW/km2. The onshore wind data are based on 50m height above surface. The data only applies to areas of low surface roughness (i.e. grassy plains), and excludes areas with slopes greater than 20%. For areas of high surface roughness (i.e. forests), the values shown may need to be reduced by one or more power classes.

Wind Polygon Brazil 10km INPE 2008 (swera:wind_inpe_high)

SRID 4326 of two available coordinate systems. Annual average of the aeolic potential at 50m. Content: wind speed in m/s, power class (7 classes), power density in W/m2 and Weibull k value organized into cells with 10km x 10km (Purpose): The thematic map by code of colors permits quick viewing of all the Brazilian territory dataset. That map indicates, for the height of 50m, the annual average, in W/m2, of wind speed, power class, power density and Weibull k value (Supplemental Information): The information is organized into cells measuring 10 x 10km. The wind potential maps were calculated from simulations produced by the MesoMap(*) for 360 days, extracted of a period of 15 years of data. The days were chosen by means of random sampling at several heights, so that each month and season be considered in a representative way. MesoMap(*) for 360 days, extracted of a period of 15 years of data. The days were chosen by means of random sampling at several heights, so that each month and season be considered in a representative way. (*) MesoMap is an integrated group of atmospheric simulation models, geographical and meteorological databases, nets of computers and storage systems. The MesoMap has been checked by high quality anemometric measurements in a large wind regimens range.

Wind Polygon Brazil 10km INPE 2008 (swera:wind_inpe_high_900913)

SRID 900913 of two available coordinate systems. Annual average of the aeolic potential at 50m. Content: wind speed in m/s, power class (7 classes), power density in W/m2 and Weibull k value organized into cells with 10km x 10km (Purpose): The thematic map by code of colors permits quick viewing of all the Brazilian territory dataset. That map indicates, for the height of 50m, the annual average, in W/m2, of wind speed, power class, power density and Weibull k value (Supplemental Information): The information is organized into cells measuring 10 x 10km. The wind potential maps were calculated from simulations produced by the MesoMap(*) for 360 days, extracted of a period of 15 years of data. The days were chosen by means of random sampling at several heights, so that each month and season be considered in a representative way. MesoMap(*) for 360 days, extracted of a period of 15 years of data. The days were chosen by means of random sampling at several heights, so that each month and season be considered in a representative way. (*) MesoMap is an integrated group of atmospheric simulation models, geographical and meteorological databases, nets of computers and storage systems. The MesoMap has been checked by high quality anemometric measurements in a large wind regimens range.

Wind Polygon Brazil 40km CEPAL INPE 2009 (swera:wind_inpe_mod)

SRID 4326 of two available coordinate systems. Annual average of the aeolic potential at 50m. Content: wind speed in m/s, power class (7 classes), power density in W/m2 and Weibull k value organized into cells with 40km x 40km Source: CEPEL (Electric Energy Research Center/Federal University of Rio de Janeiro) - Brazil and INPE (National Institute for Space Research)

Wind Polygon Brazil 40km CEPAL INPE 2009 (swera:wind_inpe_mod_900913)

SRID 900913 of two available coordinate systems. Annual average of the aeolic potential at 50m. Content: wind speed in m/s, power class (7 classes), power density in W/m2 and Weibull k value organized into cells with 40km x 40km Source: CEPEL (Electric Energy Research Center/Federal University of Rio de Janeiro) - Brazil and INPE (National Institute for Space Research)

Wind Polygon 1 Degree Global NASA 2005 (swera:wind_nasa_low)

SRID 4326. Wind Speed At 50 m Above The Surface Of The Earth (m/s)NASA Surface meteorology and Solar Energy (SSE) Release 5 Data Set (Jan. 2005)10-year Monthly & Annual Average (July 1983 - June 1993) Source: U.S. National Aeronautics and Space Administration (NASA), Surface meteorology and Solar Energy (SSE) Name or title (Title): Wind: monthly and annual average wind GIS data at one-degree resolution of the World from NASA/SSE

Wind Polygon 50m United States NREL (swera:wind_nrel_high)

SRID 4326 of two available coordinate systems. Geographic shapefiles generated from the original raster data. The original raster data varied in resolution from 200-meter to 1000-meter cell sizes. The data provide an estimate of annual average wind resource for specific states or regions. The data are separated into two distinct groups: NREL produced, and AWS Truepower produced/NREL validated. The NREL-produced map data only applies to areas of low surface roughness (i.e. grassy plains), and excludes areas with slopes greater than 20%. For areas of high surface roughness (i.e. forests), the values shown may need to be reduced by one or more power classes. The TrueWind-produced resource estimates factor in surface roughness in their calculations, and do not exclude areas with slopes greater than 20%. These data were produced in cooperation with U.S. Department of Energy's Wind Powering America program, and have been validated by NREL and other wind energy meteorological consultants. Source: NREL

Wind Polygon 50m United States NREL (swera:wind_nrel_high_900913)

SRID 900913 of two available coordinate systems. Geographic shapefiles generated from the original raster data. The original raster data varied in resolution from 200-meter to 1000-meter cell sizes. The data provide an estimate of annual average wind resource for specific states or regions. The data are separated into two distinct groups: NREL produced, and AWS Truepower produced/NREL validated. The NREL-produced map data only applies to areas of low surface roughness (i.e. grassy plains), and excludes areas with slopes greater than 20%. For areas of high surface roughness (i.e. forests), the values shown may need to be reduced by one or more power classes. The TrueWind-produced resource estimates factor in surface roughness in their calculations, and do not exclude areas with slopes greater than 20%. These data were produced in cooperation with U.S. Department of Energy's Wind Powering America program, and have been validated by NREL and other wind energy meteorological consultants. Source: NREL

Wind Polygon Multiple Countries 50m Riso-DTU 2008 (swera:wind_riso_high)

SRID 4326 of two available coordinate systems. These data are results from the KAMM/WASP studies. Version 2 is an updated version of the earlier release and includes an adjustment to Weibull A and k to bring the Atlas values into better agreement with observations. The KAMM/WAsP methodology uses a set of wind classes to represent wind conditions for the mapped region. A mesoscale simulation for each wind class, using KAMM (Karlsruhe Mesoscale Model), is performed and statistics performed on the model output. The result is i. a wind resource map, a summary of the simulated wind climate, and ii. a wind atlas, a summary of the wind climate standardized to flat, uniform roughness terrain. (Purpose): The product is intended to be used to estimate the wind resource potential in the country including the the spatial variability. This map covers regions where long term measurements are not available. In a sense this is the point of the mapping exercise, but it also means that verification of results has not been as complete would be ideal. There is some concern that the results may underestimate the resource. However, new measurement data is coming and revisions to the map may be made if necessary as verification is carried out.

Wind Polygon Multiple Countries 50m Riso-DTU 2008 (swera:wind_riso_high_900913)

SRID 900913 of two available coordinate systems. These data are results from the KAMM/WASP studies. Version 2 is an updated version of the earlier release and includes an adjustment to Weibull A and k to bring the Atlas values into better agreement with observations. The KAMM/WAsP methodology uses a set of wind classes to represent wind conditions for the mapped region. A mesoscale simulation for each wind class, using KAMM (Karlsruhe Mesoscale Model), is performed and statistics performed on the model output. The result is i. a wind resource map, a summary of the simulated wind climate, and ii. a wind atlas, a summary of the wind climate standardized to flat, uniform roughness terrain. (Purpose): The product is intended to be used to estimate the wind resource potential in the country including the the spatial variability. This map covers regions where long term measurements are not available. In a sense this is the point of the mapping exercise, but it also means that verification of results has not been as complete would be ideal. There is some concern that the results may underestimate the resource. However, new measurement data is coming and revisions to the map may be made if necessary as verification is carried out.

NREL Wisconsin 50m Wind Resource (data_res:wisconsin_50m_wind)

Abstract: Annual average wind resource potential for Wisconsin at a 50 meter height Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. Source:

NREL South Carolina 50m Wind Resource (data_res:wpc50gdd)

Abstract: Annual average wind resource potential for the state of South Carolina at a 50 meter height. Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a WGS 84 projection system. Source: AWS TrueWind/NREL

tasmania (tasmania)

Layer-Group type layer: tasmania

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