GRIDCERF: Geospatial Raster Input Data for Capacity Expansion Regional Feasibility
Climate change, energy system transitions, and socioeconomic change are compounding influences affecting the growth of electricity demand. While energy efficiency initiatives and distributed resources can address a significant amount of this demand, the United States will likely still need new utili...
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| creator | Vernon, C. R. Mongird, K. Nelson, K. Rice, J. S. |
| description | Climate change, energy system transitions, and socioeconomic change are compounding influences affecting the growth of electricity demand. While energy efficiency initiatives and distributed resources can address a significant amount of this demand, the United States will likely still need new utility-scale generation resources. The energy sector uses capacity expansion planning models to determine the aggregate need for new generation, but these models are typically at the state or regional scale and are not equipped to address the wide range of location- and technology-specific issues that are increasingly a factor in power plant siting. To help address these challenges, we have developed the Geospatial Raster Input Data for Capacity Expansion Regional Feasibility (GRIDCERF) data package, a high-resolution product to evaluate siting suitability for renewable and non-renewable power plants in the conterminous United States. GRIDCERF offers 265 suitability layers for use with 56 power plant technology configurations in a harmonized format that can be easily ingested by geospatially-enabled modeling software. It also provides pre-compiled technology-specific suitability layers and allows for user customization to robustly address science objectives when evaluating varying future conditions.
Accompanying GitHub repository:
The following GitHub repository contains the code used to generate the data in this archive: https://github.com/IMMM-SFA/vernon-etal_2023_scidata
Contents:
Note:
GRIDCERF does not provide the source data directly due to some license restrictions related for direct redistribution of the unaltered source data. However, the included file "gridcerf_source_data_description.csv" details the provenance associated with each source dataset and notes their individual licenses/disclaimers.
Common Rasters:
Suitability Layer Type and Source
GRIDCERF Raster Name
Bureau of Land Management (BLM) Surface Management Agency Areas33
gridcerf_blm_surface_management_agency_areas.tif
BLM National Landscape Conservation System (NLCS) - National Monuments34
gridcerf_blm_nlcs_national_monument_conus.tif
BLM NLCS - Outstanding Natural Areas35
gridcerf_blm_nlcs_outstanding_natural_areas_conus.tif
BLM NLCS - Wilderness36
gridcerf_blm_nlcs_wilderness_conus.tif
BLM NLCS - Wilderness Study Areas37
gridcerf_blm_nlcs_wilderness_study_areas_conus.tif
National Park Service (NPS) Class 1 airsheds38
gridcerf_class1_airsheds_conus.tif
NPS Administrative Boundaries39
gridcerf_ |
| doi_str_mv | 10.5281/zenodo.6601789 |
| format | Dataset |
| fullrecord | <record><control><sourceid>datacite_PQ8</sourceid><recordid>TN_cdi_datacite_primary_10_5281_zenodo_6601789</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>10_5281_zenodo_6601789</sourcerecordid><originalsourceid>FETCH-datacite_primary_10_5281_zenodo_66017893</originalsourceid><addsrcrecordid>eNqVjr0KwjAURrM4iLo63xewNoq1uvZP1-AervZWAjUJSQTr0xuxL-B0ho_zcRhb8jTZbXK-fpM2rUmyLOX7_DBlohHnsqhEfYSGjLcYFPYg0AdycNb2GaDEgNAZBwVavKkwQPWyqL0yGgTdI6JRE3p1VX2c52zSYe9pMXLGkrq6FKdVG4-iT9I69UA3SJ7Kb5T8Rckxavu38AFyLkaL</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>dataset</recordtype></control><display><type>dataset</type><title>GRIDCERF: Geospatial Raster Input Data for Capacity Expansion Regional Feasibility</title><source>DataCite</source><creator>Vernon, C. R. ; Mongird, K. ; Nelson, K. ; Rice, J. S.</creator><creatorcontrib>Vernon, C. R. ; Mongird, K. ; Nelson, K. ; Rice, J. S.</creatorcontrib><description>Climate change, energy system transitions, and socioeconomic change are compounding influences affecting the growth of electricity demand. While energy efficiency initiatives and distributed resources can address a significant amount of this demand, the United States will likely still need new utility-scale generation resources. The energy sector uses capacity expansion planning models to determine the aggregate need for new generation, but these models are typically at the state or regional scale and are not equipped to address the wide range of location- and technology-specific issues that are increasingly a factor in power plant siting. To help address these challenges, we have developed the Geospatial Raster Input Data for Capacity Expansion Regional Feasibility (GRIDCERF) data package, a high-resolution product to evaluate siting suitability for renewable and non-renewable power plants in the conterminous United States. GRIDCERF offers 265 suitability layers for use with 56 power plant technology configurations in a harmonized format that can be easily ingested by geospatially-enabled modeling software. It also provides pre-compiled technology-specific suitability layers and allows for user customization to robustly address science objectives when evaluating varying future conditions.
Accompanying GitHub repository:
The following GitHub repository contains the code used to generate the data in this archive: https://github.com/IMMM-SFA/vernon-etal_2023_scidata
Contents:
Note:
GRIDCERF does not provide the source data directly due to some license restrictions related for direct redistribution of the unaltered source data. However, the included file "gridcerf_source_data_description.csv" details the provenance associated with each source dataset and notes their individual licenses/disclaimers.
Common Rasters:
Suitability Layer Type and Source
GRIDCERF Raster Name
Bureau of Land Management (BLM) Surface Management Agency Areas33
gridcerf_blm_surface_management_agency_areas.tif
BLM National Landscape Conservation System (NLCS) - National Monuments34
gridcerf_blm_nlcs_national_monument_conus.tif
BLM NLCS - Outstanding Natural Areas35
gridcerf_blm_nlcs_outstanding_natural_areas_conus.tif
BLM NLCS - Wilderness36
gridcerf_blm_nlcs_wilderness_conus.tif
BLM NLCS - Wilderness Study Areas37
gridcerf_blm_nlcs_wilderness_study_areas_conus.tif
National Park Service (NPS) Class 1 airsheds38
gridcerf_class1_airsheds_conus.tif
NPS Administrative Boundaries39
gridcerf_nps_administrative_boundaries_conus.tif
NPS Historic Trails40
gridcerf_nps_historic_trails_conus.tif
NPS Scenic Trails41
gridcerf_nps_scenic_trails_conus.tif
U.S. Fish and Wildlife Service (USFWS) - Critical Habitat42
gridcerf_usfws_critical_habitat_conus.tif
USFWS - Special Designation43
gridcerf_usfws_special_designation_conus.tif
USFWS - Wild and Scenic River System44
gridcerf_usfws_national_wild_scenic_river_system_conus.tif
USFWS - National Realty Tracts45
gridcerf_usfws_national_realty_tracts_conus.tif
National Land Cover Dataset (NLCD) Wetlands46
gridcerf_nlcd_wetlands_conus.tif
U.S. Forest Service (USFS) Administrative Boundaries47
gridcerf_usfs_administrative_boundaries_conus.tif
USFS Wilderness Areas48
gridcerf_usfs_wilderness_areas_conus.tif
U.S. Geological Survey (USGS) National Wilderness Lands49
gridcerf_usgs_wilderness_areas_conus.tif
USGS Protected Areas of the U.S - Class 1&250
gridcerf_usgs_padus_class_1_to_2_conus.tif
U.S. State Protected Lands51
gridcerf_wdpa_state_protected_lands_conus.tif
Nature Conservancy lands52
gridcerf_wdpa_tnc_managed_lands_conus.tif
Technology-specific Rasters:
Suitability Layer Type and Source
GRIDCERF Raster Name
Bureau of Indian Affairs (BIA) Land Area Representations Dataset53
gridcerf_bia_land_area_representations_conus.tif
Slope 5% or less suitable20
gridcerf_srtm_slope_5pct_or_less.tif
Slope 10% or less suitable20
gridcerf_srtm_slope_10pct_or_less.tif
Slope 12% or less suitable20
gridcerf_srtm_slope_12pct_or_less.tif
Slope 20% or less suitable20
gridcerf_srtm_slope_20pct_or_less.tif
Airports (10-mile buffer)54
gridcerf_airports_10mi_buffer_conus.tif
Airports (3-mile buffer)54
gridcerf_airports_3mi_buffer_conus.tif
Proximity to Railroad and Navigable Waters (< 5 km) 55,56
gridcerf_usdot_railnodes_navwaters_within5km.tif
Coal Supply55–57
gridcerf_coalmines20km_railnodes5km_navwaters5km_conus.tif
United States Environmental Protection Agency (EPA) CO Non-attainment Areas58
gridcerf_epa_nonattainment_co_conus.tif
EPA NOx Non-attainment Areas58
gridcerf_epa_nonattainment_no2_conus.tif
EPA Ozone Non-attainment Areas58
gridcerf_epa_nonattainment_ozone_conus.tif
EPA Lead Non-attainment Areas58
gridcerf_epa_nonattainment_lead_conus.tif
EPA PM10 Non-attainment Areas58
gridcerf_epa_nonattainment_pm10_conus.tif
EPA PM2.5 Non-attainment Areas58
gridcerf_epa_nonattainment_pm2p5_conus.tif
EPA SOx Non-attainment Areas58
gridcerf_epa_nonattainment_so2_conus.tif
Earthquake Potential59
gridcerf_usgs_earthquake_pga_0.3_at_2pct_in_50yrs_conus.tif
Densely population areas11
gridcerf_densely_populated_ssp[2,3,5]_[year].tif
Densely population areas buffered by 25 miles11
gridcerf_densely_populated_ssp[2,3,5]_[year]_buff25mi.tif
Densely population areas – nuclear11
gridcerf_densely_populated_ssp[2,3,5]_[year]_nuclear.tif
National Hydrography Dataset (version 2; NHDv2)32
gridcerf_nhd2plus_surfaceflow_greaterthan[bin]mgd_buffer20km.tif
National Renewable Energy Laboratory (NREL) concentrating solar direct normal potential26
gridcerf_nrel_solar_csp_centralized_potential.tif
NREL photovoltaic potential26
gridcerf_nrel_solar_pv_centralized_potential.tif
NREL Wind Integration National Dataset (WIND) toolkit22
gridcerf_nrel_wind_development_potential_hubheight[080,110,140]_cf35.tif
Compiled Technology Rasters:
The list of layers that make up each compiled technology raster can be found in the "reference/compiled_layer_configuration.txt" file in this data archive.
The following technology raster file names are self-descriptive in the format "gridcerf____.tif". Some technologies do not have a carbon capture or cooling type designation and will simply have technology specific considerations listed.
gridcerf_biomass_conventional_ccs_dry.tif
gridcerf_biomass_conventional_ccs_oncethrough.tif
gridcerf_biomass_conventional_ccs_recirculating.tif
gridcerf_biomass_conventional_no-ccs_dry.tif
gridcerf_biomass_conventional_no-ccs_oncethrough.tif
gridcerf_biomass_conventional_no-ccs_pond.tif
gridcerf_biomass_conventional_no-ccs_recirculating.tif
gridcerf_biomass_igcc_no-ccs_dry.tif
gridcerf_biomass_igcc_no-ccs_oncethrough.tif
gridcerf_biomass_igcc_no-ccs_recirculating.tif
gridcerf_biomass_igcc_with-ccs_dry.tif
gridcerf_biomass_igcc_with-ccs_oncethrough.tif
gridcerf_biomass_igcc_with-ccs_recirculating.tif
gridcerf_coal_conventional_ccs_dry.tif
gridcerf_coal_conventional_ccs_oncethrough.tif
gridcerf_coal_conventional_ccs_recirculating.tif
gridcerf_coal_conventional_no-ccs_dry.tif
gridcerf_coal_conventional_no-ccs_oncethrough.tif
gridcerf_coal_conventional_no-ccs_pond.tif
gridcerf_coal_conventional_no-ccs_recirculating.tif
gridcerf_coal_igcc_no-ccs_dry.tif
gridcerf_coal_igcc_no-ccs_oncethrough.tif
gridcerf_coal_igcc_no-ccs_recirculating.tif
gridcerf_coal_igcc_with-ccs_dry.tif
gridcerf_coal_igcc_with-ccs_oncethrough.tif
gridcerf_coal_igcc_with-ccs_recirculating.tif
gridcerf_gas_cc_ccs_dry.tif
gridcerf_gas_cc_ccs_oncethrough.tif
gridcerf_gas_cc_ccs_recirculating.tif
gridcerf_gas_cc_no-ccs_dry.tif
gridcerf_gas_cc_no-ccs_oncethrough.tif
gridcerf_gas_cc_no-ccs_pond.tif
gridcerf_gas_cc_no-ccs_recirculating.tif
gridcerf_gas_turbine_dry.tif
gridcerf_gas_turbine_oncethrough.tif
gridcerf_gas_turbine_pond.tif
gridcerf_gas_turbine_recirculating.tif
gridcerf_nuclear_gen3_oncethrough.tif
gridcerf_nuclear_gen3_pond.tif
gridcerf_nuclear_gen3_recirculating.tif
gridcerf_refinedliquids_cc_ccs_dry.tif
gridcerf_refinedliquids_cc_ccs_oncethrough.tif
gridcerf_refinedliquids_cc_ccs_recirculating.tif
gridcerf_refinedliquids_cc_no-ccs_dry.tif
gridcerf_refinedliquids_cc_no-ccs_oncethrough.tif
gridcerf_refinedliquids_cc_no-ccs_recirculating.tif
gridcerf_refinedliquids_ct_dry.tif
gridcerf_refinedliquids_ct_oncethrough.tif
gridcerf_refinedliquids_ct_pond.tif
gridcerf_refinedliquids_ct_recirculating.tif
gridcerf_solar_csp_centralized_dry-hybrid.tif
gridcerf_solar_csp_centralized_recirculating.tif
gridcerf_solar_pv_centralized.tif
gridcerf_wind_onshore_hubheight080m.tif
gridcerf_wind_onshore_hubheight110m.tif
gridcerf_wind_onshore_hubheight140m.tif
Reference Data: Contains land mask and other useful boundary data. Also contains additional literature review resource and the layers used to build the compiled suitability.
References:
1. Bureau of Land Management. BLM National Surface Management Agency Area Polygons - National Geospatial Data Asset (NGDA). Landscape Approach Data Portal https://gbp-blm-egis.hub.arcgis.com/datasets/blm-national-sma-surface-management-agency-area-polygons/about (2023).
2. Bureau of Land Management. BLM National NLCS National Monuments, National Conservation Areas and Similar Designations Polygons. U.S.Department of Interior Bureau of Land Management Geospatial Business Plaform https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-natl-nlcs-national-monuments-national-conservation-areas-polygons/about (2023).
3. Hartger, P. NLCS Outstanding Natural Areas. ArcGIS Hub https://hub.arcgis.com/datasets/Wilderness::nlcs-outstanding-natural-areas/about (2017).
4. Bureau of Land Management. BLM National NLCS Wilderness Areas Polygons. U.S.Department of Interior Bureau of Land Management Geospatial Business Plaform https://arcg.is/a01uC (2023).
5. Bureau of Land Management. BLM National NLCS Wilderness Study Areas Polygons. U.S.Department of Interior https://arcg.is/14XPiC (2023).
6. United States Environmental Protection Agency. Mandatory Class 1 Federal Areas Web Service. Mandatory Class 1 Federal Areas Web</description><identifier>DOI: 10.5281/zenodo.6601789</identifier><language>eng</language><publisher>Zenodo</publisher><subject>Capacity Expansion ; Geospatial ; MultiSector Dynamics</subject><creationdate>2023</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-3406-6214 ; 0000-0003-2807-7088 ; 0000-0002-6745-167X ; 0000-0002-7833-9456</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>776,1888</link.rule.ids><linktorsrc>$$Uhttps://commons.datacite.org/doi.org/10.5281/zenodo.6601789$$EView_record_in_DataCite.org$$FView_record_in_$$GDataCite.org$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Vernon, C. R.</creatorcontrib><creatorcontrib>Mongird, K.</creatorcontrib><creatorcontrib>Nelson, K.</creatorcontrib><creatorcontrib>Rice, J. S.</creatorcontrib><title>GRIDCERF: Geospatial Raster Input Data for Capacity Expansion Regional Feasibility</title><description>Climate change, energy system transitions, and socioeconomic change are compounding influences affecting the growth of electricity demand. While energy efficiency initiatives and distributed resources can address a significant amount of this demand, the United States will likely still need new utility-scale generation resources. The energy sector uses capacity expansion planning models to determine the aggregate need for new generation, but these models are typically at the state or regional scale and are not equipped to address the wide range of location- and technology-specific issues that are increasingly a factor in power plant siting. To help address these challenges, we have developed the Geospatial Raster Input Data for Capacity Expansion Regional Feasibility (GRIDCERF) data package, a high-resolution product to evaluate siting suitability for renewable and non-renewable power plants in the conterminous United States. GRIDCERF offers 265 suitability layers for use with 56 power plant technology configurations in a harmonized format that can be easily ingested by geospatially-enabled modeling software. It also provides pre-compiled technology-specific suitability layers and allows for user customization to robustly address science objectives when evaluating varying future conditions.
Accompanying GitHub repository:
The following GitHub repository contains the code used to generate the data in this archive: https://github.com/IMMM-SFA/vernon-etal_2023_scidata
Contents:
Note:
GRIDCERF does not provide the source data directly due to some license restrictions related for direct redistribution of the unaltered source data. However, the included file "gridcerf_source_data_description.csv" details the provenance associated with each source dataset and notes their individual licenses/disclaimers.
Common Rasters:
Suitability Layer Type and Source
GRIDCERF Raster Name
Bureau of Land Management (BLM) Surface Management Agency Areas33
gridcerf_blm_surface_management_agency_areas.tif
BLM National Landscape Conservation System (NLCS) - National Monuments34
gridcerf_blm_nlcs_national_monument_conus.tif
BLM NLCS - Outstanding Natural Areas35
gridcerf_blm_nlcs_outstanding_natural_areas_conus.tif
BLM NLCS - Wilderness36
gridcerf_blm_nlcs_wilderness_conus.tif
BLM NLCS - Wilderness Study Areas37
gridcerf_blm_nlcs_wilderness_study_areas_conus.tif
National Park Service (NPS) Class 1 airsheds38
gridcerf_class1_airsheds_conus.tif
NPS Administrative Boundaries39
gridcerf_nps_administrative_boundaries_conus.tif
NPS Historic Trails40
gridcerf_nps_historic_trails_conus.tif
NPS Scenic Trails41
gridcerf_nps_scenic_trails_conus.tif
U.S. Fish and Wildlife Service (USFWS) - Critical Habitat42
gridcerf_usfws_critical_habitat_conus.tif
USFWS - Special Designation43
gridcerf_usfws_special_designation_conus.tif
USFWS - Wild and Scenic River System44
gridcerf_usfws_national_wild_scenic_river_system_conus.tif
USFWS - National Realty Tracts45
gridcerf_usfws_national_realty_tracts_conus.tif
National Land Cover Dataset (NLCD) Wetlands46
gridcerf_nlcd_wetlands_conus.tif
U.S. Forest Service (USFS) Administrative Boundaries47
gridcerf_usfs_administrative_boundaries_conus.tif
USFS Wilderness Areas48
gridcerf_usfs_wilderness_areas_conus.tif
U.S. Geological Survey (USGS) National Wilderness Lands49
gridcerf_usgs_wilderness_areas_conus.tif
USGS Protected Areas of the U.S - Class 1&250
gridcerf_usgs_padus_class_1_to_2_conus.tif
U.S. State Protected Lands51
gridcerf_wdpa_state_protected_lands_conus.tif
Nature Conservancy lands52
gridcerf_wdpa_tnc_managed_lands_conus.tif
Technology-specific Rasters:
Suitability Layer Type and Source
GRIDCERF Raster Name
Bureau of Indian Affairs (BIA) Land Area Representations Dataset53
gridcerf_bia_land_area_representations_conus.tif
Slope 5% or less suitable20
gridcerf_srtm_slope_5pct_or_less.tif
Slope 10% or less suitable20
gridcerf_srtm_slope_10pct_or_less.tif
Slope 12% or less suitable20
gridcerf_srtm_slope_12pct_or_less.tif
Slope 20% or less suitable20
gridcerf_srtm_slope_20pct_or_less.tif
Airports (10-mile buffer)54
gridcerf_airports_10mi_buffer_conus.tif
Airports (3-mile buffer)54
gridcerf_airports_3mi_buffer_conus.tif
Proximity to Railroad and Navigable Waters (< 5 km) 55,56
gridcerf_usdot_railnodes_navwaters_within5km.tif
Coal Supply55–57
gridcerf_coalmines20km_railnodes5km_navwaters5km_conus.tif
United States Environmental Protection Agency (EPA) CO Non-attainment Areas58
gridcerf_epa_nonattainment_co_conus.tif
EPA NOx Non-attainment Areas58
gridcerf_epa_nonattainment_no2_conus.tif
EPA Ozone Non-attainment Areas58
gridcerf_epa_nonattainment_ozone_conus.tif
EPA Lead Non-attainment Areas58
gridcerf_epa_nonattainment_lead_conus.tif
EPA PM10 Non-attainment Areas58
gridcerf_epa_nonattainment_pm10_conus.tif
EPA PM2.5 Non-attainment Areas58
gridcerf_epa_nonattainment_pm2p5_conus.tif
EPA SOx Non-attainment Areas58
gridcerf_epa_nonattainment_so2_conus.tif
Earthquake Potential59
gridcerf_usgs_earthquake_pga_0.3_at_2pct_in_50yrs_conus.tif
Densely population areas11
gridcerf_densely_populated_ssp[2,3,5]_[year].tif
Densely population areas buffered by 25 miles11
gridcerf_densely_populated_ssp[2,3,5]_[year]_buff25mi.tif
Densely population areas – nuclear11
gridcerf_densely_populated_ssp[2,3,5]_[year]_nuclear.tif
National Hydrography Dataset (version 2; NHDv2)32
gridcerf_nhd2plus_surfaceflow_greaterthan[bin]mgd_buffer20km.tif
National Renewable Energy Laboratory (NREL) concentrating solar direct normal potential26
gridcerf_nrel_solar_csp_centralized_potential.tif
NREL photovoltaic potential26
gridcerf_nrel_solar_pv_centralized_potential.tif
NREL Wind Integration National Dataset (WIND) toolkit22
gridcerf_nrel_wind_development_potential_hubheight[080,110,140]_cf35.tif
Compiled Technology Rasters:
The list of layers that make up each compiled technology raster can be found in the "reference/compiled_layer_configuration.txt" file in this data archive.
The following technology raster file names are self-descriptive in the format "gridcerf____.tif". Some technologies do not have a carbon capture or cooling type designation and will simply have technology specific considerations listed.
gridcerf_biomass_conventional_ccs_dry.tif
gridcerf_biomass_conventional_ccs_oncethrough.tif
gridcerf_biomass_conventional_ccs_recirculating.tif
gridcerf_biomass_conventional_no-ccs_dry.tif
gridcerf_biomass_conventional_no-ccs_oncethrough.tif
gridcerf_biomass_conventional_no-ccs_pond.tif
gridcerf_biomass_conventional_no-ccs_recirculating.tif
gridcerf_biomass_igcc_no-ccs_dry.tif
gridcerf_biomass_igcc_no-ccs_oncethrough.tif
gridcerf_biomass_igcc_no-ccs_recirculating.tif
gridcerf_biomass_igcc_with-ccs_dry.tif
gridcerf_biomass_igcc_with-ccs_oncethrough.tif
gridcerf_biomass_igcc_with-ccs_recirculating.tif
gridcerf_coal_conventional_ccs_dry.tif
gridcerf_coal_conventional_ccs_oncethrough.tif
gridcerf_coal_conventional_ccs_recirculating.tif
gridcerf_coal_conventional_no-ccs_dry.tif
gridcerf_coal_conventional_no-ccs_oncethrough.tif
gridcerf_coal_conventional_no-ccs_pond.tif
gridcerf_coal_conventional_no-ccs_recirculating.tif
gridcerf_coal_igcc_no-ccs_dry.tif
gridcerf_coal_igcc_no-ccs_oncethrough.tif
gridcerf_coal_igcc_no-ccs_recirculating.tif
gridcerf_coal_igcc_with-ccs_dry.tif
gridcerf_coal_igcc_with-ccs_oncethrough.tif
gridcerf_coal_igcc_with-ccs_recirculating.tif
gridcerf_gas_cc_ccs_dry.tif
gridcerf_gas_cc_ccs_oncethrough.tif
gridcerf_gas_cc_ccs_recirculating.tif
gridcerf_gas_cc_no-ccs_dry.tif
gridcerf_gas_cc_no-ccs_oncethrough.tif
gridcerf_gas_cc_no-ccs_pond.tif
gridcerf_gas_cc_no-ccs_recirculating.tif
gridcerf_gas_turbine_dry.tif
gridcerf_gas_turbine_oncethrough.tif
gridcerf_gas_turbine_pond.tif
gridcerf_gas_turbine_recirculating.tif
gridcerf_nuclear_gen3_oncethrough.tif
gridcerf_nuclear_gen3_pond.tif
gridcerf_nuclear_gen3_recirculating.tif
gridcerf_refinedliquids_cc_ccs_dry.tif
gridcerf_refinedliquids_cc_ccs_oncethrough.tif
gridcerf_refinedliquids_cc_ccs_recirculating.tif
gridcerf_refinedliquids_cc_no-ccs_dry.tif
gridcerf_refinedliquids_cc_no-ccs_oncethrough.tif
gridcerf_refinedliquids_cc_no-ccs_recirculating.tif
gridcerf_refinedliquids_ct_dry.tif
gridcerf_refinedliquids_ct_oncethrough.tif
gridcerf_refinedliquids_ct_pond.tif
gridcerf_refinedliquids_ct_recirculating.tif
gridcerf_solar_csp_centralized_dry-hybrid.tif
gridcerf_solar_csp_centralized_recirculating.tif
gridcerf_solar_pv_centralized.tif
gridcerf_wind_onshore_hubheight080m.tif
gridcerf_wind_onshore_hubheight110m.tif
gridcerf_wind_onshore_hubheight140m.tif
Reference Data: Contains land mask and other useful boundary data. Also contains additional literature review resource and the layers used to build the compiled suitability.
References:
1. Bureau of Land Management. BLM National Surface Management Agency Area Polygons - National Geospatial Data Asset (NGDA). Landscape Approach Data Portal https://gbp-blm-egis.hub.arcgis.com/datasets/blm-national-sma-surface-management-agency-area-polygons/about (2023).
2. Bureau of Land Management. BLM National NLCS National Monuments, National Conservation Areas and Similar Designations Polygons. U.S.Department of Interior Bureau of Land Management Geospatial Business Plaform https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-natl-nlcs-national-monuments-national-conservation-areas-polygons/about (2023).
3. Hartger, P. NLCS Outstanding Natural Areas. ArcGIS Hub https://hub.arcgis.com/datasets/Wilderness::nlcs-outstanding-natural-areas/about (2017).
4. Bureau of Land Management. BLM National NLCS Wilderness Areas Polygons. U.S.Department of Interior Bureau of Land Management Geospatial Business Plaform https://arcg.is/a01uC (2023).
5. Bureau of Land Management. BLM National NLCS Wilderness Study Areas Polygons. U.S.Department of Interior https://arcg.is/14XPiC (2023).
6. United States Environmental Protection Agency. Mandatory Class 1 Federal Areas Web Service. Mandatory Class 1 Federal Areas Web</description><subject>Capacity Expansion</subject><subject>Geospatial</subject><subject>MultiSector Dynamics</subject><fulltext>true</fulltext><rsrctype>dataset</rsrctype><creationdate>2023</creationdate><recordtype>dataset</recordtype><sourceid>PQ8</sourceid><recordid>eNqVjr0KwjAURrM4iLo63xewNoq1uvZP1-AervZWAjUJSQTr0xuxL-B0ho_zcRhb8jTZbXK-fpM2rUmyLOX7_DBlohHnsqhEfYSGjLcYFPYg0AdycNb2GaDEgNAZBwVavKkwQPWyqL0yGgTdI6JRE3p1VX2c52zSYe9pMXLGkrq6FKdVG4-iT9I69UA3SJ7Kb5T8Rckxavu38AFyLkaL</recordid><startdate>20231025</startdate><enddate>20231025</enddate><creator>Vernon, C. R.</creator><creator>Mongird, K.</creator><creator>Nelson, K.</creator><creator>Rice, J. S.</creator><general>Zenodo</general><scope>DYCCY</scope><scope>PQ8</scope><orcidid>https://orcid.org/0000-0002-3406-6214</orcidid><orcidid>https://orcid.org/0000-0003-2807-7088</orcidid><orcidid>https://orcid.org/0000-0002-6745-167X</orcidid><orcidid>https://orcid.org/0000-0002-7833-9456</orcidid></search><sort><creationdate>20231025</creationdate><title>GRIDCERF: Geospatial Raster Input Data for Capacity Expansion Regional Feasibility</title><author>Vernon, C. R. ; Mongird, K. ; Nelson, K. ; Rice, J. S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-datacite_primary_10_5281_zenodo_66017893</frbrgroupid><rsrctype>datasets</rsrctype><prefilter>datasets</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Capacity Expansion</topic><topic>Geospatial</topic><topic>MultiSector Dynamics</topic><toplevel>online_resources</toplevel><creatorcontrib>Vernon, C. R.</creatorcontrib><creatorcontrib>Mongird, K.</creatorcontrib><creatorcontrib>Nelson, K.</creatorcontrib><creatorcontrib>Rice, J. S.</creatorcontrib><collection>DataCite (Open Access)</collection><collection>DataCite</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Vernon, C. R.</au><au>Mongird, K.</au><au>Nelson, K.</au><au>Rice, J. S.</au><format>book</format><genre>unknown</genre><ristype>DATA</ristype><title>GRIDCERF: Geospatial Raster Input Data for Capacity Expansion Regional Feasibility</title><date>2023-10-25</date><risdate>2023</risdate><abstract>Climate change, energy system transitions, and socioeconomic change are compounding influences affecting the growth of electricity demand. While energy efficiency initiatives and distributed resources can address a significant amount of this demand, the United States will likely still need new utility-scale generation resources. The energy sector uses capacity expansion planning models to determine the aggregate need for new generation, but these models are typically at the state or regional scale and are not equipped to address the wide range of location- and technology-specific issues that are increasingly a factor in power plant siting. To help address these challenges, we have developed the Geospatial Raster Input Data for Capacity Expansion Regional Feasibility (GRIDCERF) data package, a high-resolution product to evaluate siting suitability for renewable and non-renewable power plants in the conterminous United States. GRIDCERF offers 265 suitability layers for use with 56 power plant technology configurations in a harmonized format that can be easily ingested by geospatially-enabled modeling software. It also provides pre-compiled technology-specific suitability layers and allows for user customization to robustly address science objectives when evaluating varying future conditions.
Accompanying GitHub repository:
The following GitHub repository contains the code used to generate the data in this archive: https://github.com/IMMM-SFA/vernon-etal_2023_scidata
Contents:
Note:
GRIDCERF does not provide the source data directly due to some license restrictions related for direct redistribution of the unaltered source data. However, the included file "gridcerf_source_data_description.csv" details the provenance associated with each source dataset and notes their individual licenses/disclaimers.
Common Rasters:
Suitability Layer Type and Source
GRIDCERF Raster Name
Bureau of Land Management (BLM) Surface Management Agency Areas33
gridcerf_blm_surface_management_agency_areas.tif
BLM National Landscape Conservation System (NLCS) - National Monuments34
gridcerf_blm_nlcs_national_monument_conus.tif
BLM NLCS - Outstanding Natural Areas35
gridcerf_blm_nlcs_outstanding_natural_areas_conus.tif
BLM NLCS - Wilderness36
gridcerf_blm_nlcs_wilderness_conus.tif
BLM NLCS - Wilderness Study Areas37
gridcerf_blm_nlcs_wilderness_study_areas_conus.tif
National Park Service (NPS) Class 1 airsheds38
gridcerf_class1_airsheds_conus.tif
NPS Administrative Boundaries39
gridcerf_nps_administrative_boundaries_conus.tif
NPS Historic Trails40
gridcerf_nps_historic_trails_conus.tif
NPS Scenic Trails41
gridcerf_nps_scenic_trails_conus.tif
U.S. Fish and Wildlife Service (USFWS) - Critical Habitat42
gridcerf_usfws_critical_habitat_conus.tif
USFWS - Special Designation43
gridcerf_usfws_special_designation_conus.tif
USFWS - Wild and Scenic River System44
gridcerf_usfws_national_wild_scenic_river_system_conus.tif
USFWS - National Realty Tracts45
gridcerf_usfws_national_realty_tracts_conus.tif
National Land Cover Dataset (NLCD) Wetlands46
gridcerf_nlcd_wetlands_conus.tif
U.S. Forest Service (USFS) Administrative Boundaries47
gridcerf_usfs_administrative_boundaries_conus.tif
USFS Wilderness Areas48
gridcerf_usfs_wilderness_areas_conus.tif
U.S. Geological Survey (USGS) National Wilderness Lands49
gridcerf_usgs_wilderness_areas_conus.tif
USGS Protected Areas of the U.S - Class 1&250
gridcerf_usgs_padus_class_1_to_2_conus.tif
U.S. State Protected Lands51
gridcerf_wdpa_state_protected_lands_conus.tif
Nature Conservancy lands52
gridcerf_wdpa_tnc_managed_lands_conus.tif
Technology-specific Rasters:
Suitability Layer Type and Source
GRIDCERF Raster Name
Bureau of Indian Affairs (BIA) Land Area Representations Dataset53
gridcerf_bia_land_area_representations_conus.tif
Slope 5% or less suitable20
gridcerf_srtm_slope_5pct_or_less.tif
Slope 10% or less suitable20
gridcerf_srtm_slope_10pct_or_less.tif
Slope 12% or less suitable20
gridcerf_srtm_slope_12pct_or_less.tif
Slope 20% or less suitable20
gridcerf_srtm_slope_20pct_or_less.tif
Airports (10-mile buffer)54
gridcerf_airports_10mi_buffer_conus.tif
Airports (3-mile buffer)54
gridcerf_airports_3mi_buffer_conus.tif
Proximity to Railroad and Navigable Waters (< 5 km) 55,56
gridcerf_usdot_railnodes_navwaters_within5km.tif
Coal Supply55–57
gridcerf_coalmines20km_railnodes5km_navwaters5km_conus.tif
United States Environmental Protection Agency (EPA) CO Non-attainment Areas58
gridcerf_epa_nonattainment_co_conus.tif
EPA NOx Non-attainment Areas58
gridcerf_epa_nonattainment_no2_conus.tif
EPA Ozone Non-attainment Areas58
gridcerf_epa_nonattainment_ozone_conus.tif
EPA Lead Non-attainment Areas58
gridcerf_epa_nonattainment_lead_conus.tif
EPA PM10 Non-attainment Areas58
gridcerf_epa_nonattainment_pm10_conus.tif
EPA PM2.5 Non-attainment Areas58
gridcerf_epa_nonattainment_pm2p5_conus.tif
EPA SOx Non-attainment Areas58
gridcerf_epa_nonattainment_so2_conus.tif
Earthquake Potential59
gridcerf_usgs_earthquake_pga_0.3_at_2pct_in_50yrs_conus.tif
Densely population areas11
gridcerf_densely_populated_ssp[2,3,5]_[year].tif
Densely population areas buffered by 25 miles11
gridcerf_densely_populated_ssp[2,3,5]_[year]_buff25mi.tif
Densely population areas – nuclear11
gridcerf_densely_populated_ssp[2,3,5]_[year]_nuclear.tif
National Hydrography Dataset (version 2; NHDv2)32
gridcerf_nhd2plus_surfaceflow_greaterthan[bin]mgd_buffer20km.tif
National Renewable Energy Laboratory (NREL) concentrating solar direct normal potential26
gridcerf_nrel_solar_csp_centralized_potential.tif
NREL photovoltaic potential26
gridcerf_nrel_solar_pv_centralized_potential.tif
NREL Wind Integration National Dataset (WIND) toolkit22
gridcerf_nrel_wind_development_potential_hubheight[080,110,140]_cf35.tif
Compiled Technology Rasters:
The list of layers that make up each compiled technology raster can be found in the "reference/compiled_layer_configuration.txt" file in this data archive.
The following technology raster file names are self-descriptive in the format "gridcerf____.tif". Some technologies do not have a carbon capture or cooling type designation and will simply have technology specific considerations listed.
gridcerf_biomass_conventional_ccs_dry.tif
gridcerf_biomass_conventional_ccs_oncethrough.tif
gridcerf_biomass_conventional_ccs_recirculating.tif
gridcerf_biomass_conventional_no-ccs_dry.tif
gridcerf_biomass_conventional_no-ccs_oncethrough.tif
gridcerf_biomass_conventional_no-ccs_pond.tif
gridcerf_biomass_conventional_no-ccs_recirculating.tif
gridcerf_biomass_igcc_no-ccs_dry.tif
gridcerf_biomass_igcc_no-ccs_oncethrough.tif
gridcerf_biomass_igcc_no-ccs_recirculating.tif
gridcerf_biomass_igcc_with-ccs_dry.tif
gridcerf_biomass_igcc_with-ccs_oncethrough.tif
gridcerf_biomass_igcc_with-ccs_recirculating.tif
gridcerf_coal_conventional_ccs_dry.tif
gridcerf_coal_conventional_ccs_oncethrough.tif
gridcerf_coal_conventional_ccs_recirculating.tif
gridcerf_coal_conventional_no-ccs_dry.tif
gridcerf_coal_conventional_no-ccs_oncethrough.tif
gridcerf_coal_conventional_no-ccs_pond.tif
gridcerf_coal_conventional_no-ccs_recirculating.tif
gridcerf_coal_igcc_no-ccs_dry.tif
gridcerf_coal_igcc_no-ccs_oncethrough.tif
gridcerf_coal_igcc_no-ccs_recirculating.tif
gridcerf_coal_igcc_with-ccs_dry.tif
gridcerf_coal_igcc_with-ccs_oncethrough.tif
gridcerf_coal_igcc_with-ccs_recirculating.tif
gridcerf_gas_cc_ccs_dry.tif
gridcerf_gas_cc_ccs_oncethrough.tif
gridcerf_gas_cc_ccs_recirculating.tif
gridcerf_gas_cc_no-ccs_dry.tif
gridcerf_gas_cc_no-ccs_oncethrough.tif
gridcerf_gas_cc_no-ccs_pond.tif
gridcerf_gas_cc_no-ccs_recirculating.tif
gridcerf_gas_turbine_dry.tif
gridcerf_gas_turbine_oncethrough.tif
gridcerf_gas_turbine_pond.tif
gridcerf_gas_turbine_recirculating.tif
gridcerf_nuclear_gen3_oncethrough.tif
gridcerf_nuclear_gen3_pond.tif
gridcerf_nuclear_gen3_recirculating.tif
gridcerf_refinedliquids_cc_ccs_dry.tif
gridcerf_refinedliquids_cc_ccs_oncethrough.tif
gridcerf_refinedliquids_cc_ccs_recirculating.tif
gridcerf_refinedliquids_cc_no-ccs_dry.tif
gridcerf_refinedliquids_cc_no-ccs_oncethrough.tif
gridcerf_refinedliquids_cc_no-ccs_recirculating.tif
gridcerf_refinedliquids_ct_dry.tif
gridcerf_refinedliquids_ct_oncethrough.tif
gridcerf_refinedliquids_ct_pond.tif
gridcerf_refinedliquids_ct_recirculating.tif
gridcerf_solar_csp_centralized_dry-hybrid.tif
gridcerf_solar_csp_centralized_recirculating.tif
gridcerf_solar_pv_centralized.tif
gridcerf_wind_onshore_hubheight080m.tif
gridcerf_wind_onshore_hubheight110m.tif
gridcerf_wind_onshore_hubheight140m.tif
Reference Data: Contains land mask and other useful boundary data. Also contains additional literature review resource and the layers used to build the compiled suitability.
References:
1. Bureau of Land Management. BLM National Surface Management Agency Area Polygons - National Geospatial Data Asset (NGDA). Landscape Approach Data Portal https://gbp-blm-egis.hub.arcgis.com/datasets/blm-national-sma-surface-management-agency-area-polygons/about (2023).
2. Bureau of Land Management. BLM National NLCS National Monuments, National Conservation Areas and Similar Designations Polygons. U.S.Department of Interior Bureau of Land Management Geospatial Business Plaform https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-natl-nlcs-national-monuments-national-conservation-areas-polygons/about (2023).
3. Hartger, P. NLCS Outstanding Natural Areas. ArcGIS Hub https://hub.arcgis.com/datasets/Wilderness::nlcs-outstanding-natural-areas/about (2017).
4. Bureau of Land Management. BLM National NLCS Wilderness Areas Polygons. U.S.Department of Interior Bureau of Land Management Geospatial Business Plaform https://arcg.is/a01uC (2023).
5. Bureau of Land Management. BLM National NLCS Wilderness Study Areas Polygons. U.S.Department of Interior https://arcg.is/14XPiC (2023).
6. United States Environmental Protection Agency. Mandatory Class 1 Federal Areas Web Service. Mandatory Class 1 Federal Areas Web</abstract><pub>Zenodo</pub><doi>10.5281/zenodo.6601789</doi><orcidid>https://orcid.org/0000-0002-3406-6214</orcidid><orcidid>https://orcid.org/0000-0003-2807-7088</orcidid><orcidid>https://orcid.org/0000-0002-6745-167X</orcidid><orcidid>https://orcid.org/0000-0002-7833-9456</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | DOI: 10.5281/zenodo.6601789 |
| ispartof | |
| issn | |
| language | eng |
| recordid | cdi_datacite_primary_10_5281_zenodo_6601789 |
| source | DataCite |
| subjects | Capacity Expansion Geospatial MultiSector Dynamics |
| title | GRIDCERF: Geospatial Raster Input Data for Capacity Expansion Regional Feasibility |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-01T21%3A02%3A43IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-datacite_PQ8&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=unknown&rft.au=Vernon,%20C.%20R.&rft.date=2023-10-25&rft_id=info:doi/10.5281/zenodo.6601789&rft_dat=%3Cdatacite_PQ8%3E10_5281_zenodo_6601789%3C/datacite_PQ8%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |