43 datasets found
  1. Z

    GeoJSON files for the MCSC's Trucking Industry Decarbonization Explorer...

    • data.niaid.nih.gov
    • zenodo.org
    Updated Feb 18, 2025
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    MacDonell, Danika; Borrero, Micah; Bashir, Noman; MIT Climate & Sustainability Consortium (2025). GeoJSON files for the MCSC's Trucking Industry Decarbonization Explorer (Geo-TIDE) [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_13207715
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    Dataset updated
    Feb 18, 2025
    Dataset provided by
    Massachusetts Institute of Technology
    Authors
    MacDonell, Danika; Borrero, Micah; Bashir, Noman; MIT Climate & Sustainability Consortium
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Summary

    Geojson files used to visualize geospatial layers relevant to identifying and assessing trucking fleet decarbonization opportunities with the MIT Climate & Sustainability Consortium's Geospatial Trucking Industry Decarbonization Explorer (Geo-TIDE) tool.

    Relevant Links

    Link to the online version of the tool (requires creation of a free user account).

    Link to GitHub repo with source code to produce this dataset and deploy the Geo-TIDE tool locally.

    Funding

    This dataset was produced with support from the MIT Climate & Sustainability Consortium.

    Original Data Sources

    These geojson files draw from and synthesize a number of different datasets and tools. The original data sources and tools are described below:

    Filename(s) Description of Original Data Source(s) Link(s) to Download Original Data License and Attribution for Original Data Source(s)

    faf5_freight_flows/*.geojson

    trucking_energy_demand.geojson

    highway_assignment_links_*.geojson

    infrastructure_pooling_thought_experiment/*.geojson

    Regional and highway-level freight flow data obtained from the Freight Analysis Framework Version 5. Shapefiles for FAF5 region boundaries and highway links are obtained from the National Transportation Atlas Database. Emissions attributes are evaluated by incorporating data from the 2002 Vehicle Inventory and Use Survey and the GREET lifecycle emissions tool maintained by Argonne National Lab.

    Shapefile for FAF5 Regions

    Shapefile for FAF5 Highway Network Links

    FAF5 2022 Origin-Destination Freight Flow database

    FAF5 2022 Highway Assignment Results

    Attribution for Shapefiles: United States Department of Transportation Bureau of Transportation Statistics National Transportation Atlas Database (NTAD). Available at: https://geodata.bts.gov/search?collection=Dataset.

    License for Shapefiles: This NTAD dataset is a work of the United States government as defined in 17 U.S.C. § 101 and as such are not protected by any U.S. copyrights. This work is available for unrestricted public use.

    Attribution for Origin-Destination Freight Flow database: National Transportation Research Center in the Oak Ridge National Laboratory with funding from the Bureau of Transportation Statistics and the Federal Highway Administration. Freight Analysis Framework Version 5: Origin-Destination Data. Available from: https://faf.ornl.gov/faf5/Default.aspx. Obtained on Aug 5, 2024. In the public domain.

    Attribution for the 2022 Vehicle Inventory and Use Survey Data: United States Department of Transportation Bureau of Transportation Statistics. Vehicle Inventory and Use Survey (VIUS) 2002 [supporting datasets]. 2024. https://doi.org/10.21949/1506070

    Attribution for the GREET tool (original publication): Argonne National Laboratory Energy Systems Division Center for Transportation Research. GREET Life-cycle Model. 2014. Available from this link.

    Attribution for the GREET tool (2022 updates): Wang, Michael, et al. Summary of Expansions and Updates in GREET® 2022. United States. https://doi.org/10.2172/1891644

    grid_emission_intensity/*.geojson

    Emission intensity data is obtained from the eGRID database maintained by the United States Environmental Protection Agency.

    eGRID subregion boundaries are obtained as a shapefile from the eGRID Mapping Files database.

    eGRID database

    Shapefile with eGRID subregion boundaries

    Attribution for eGRID data: United States Environmental Protection Agency: eGRID with 2022 data. Available from https://www.epa.gov/egrid/download-data. In the public domain.

    Attribution for shapefile: United States Environmental Protection Agency: eGRID Mapping Files. Available from https://www.epa.gov/egrid/egrid-mapping-files. In the public domain.

    US_elec.geojson

    US_hy.geojson

    US_lng.geojson

    US_cng.geojson

    US_lpg.geojson

    Locations of direct current fast chargers and refueling stations for alternative fuels along U.S. highways. Obtained directly from the Station Data for Alternative Fuel Corridors in the Alternative Fuels Data Center maintained by the United States Department of Energy Office of Energy Efficiency and Renewable Energy.

    US_elec.geojson

    US_hy.geojson

    US_lng.geojson

    US_cng.geojson

    US_lpg.geojson

    Attribution: U.S. Department of Energy, Energy Efficiency and Renewable Energy. Alternative Fueling Station Corridors. 2024. Available from: https://afdc.energy.gov/corridors. In the public domain.

    These data and software code ("Data") are provided by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC ("Alliance"), for the U.S. Department of Energy ("DOE"), and may be used for any purpose whatsoever.

    daily_grid_emission_profiles/*.geojson

    Hourly emission intensity data obtained from ElectricityMaps.

    Original data can be downloaded as csv files from the ElectricityMaps United States of America database

    Shapefile with region boundaries used by ElectricityMaps

    License: Open Database License (ODbL). Details here: https://www.electricitymaps.com/data-portal

    Attribution for csv files: Electricity Maps (2024). United States of America 2022-23 Hourly Carbon Intensity Data (Version January 17, 2024). Electricity Maps Data Portal. https://www.electricitymaps.com/data-portal.

    Attribution for shapefile with region boundaries: ElectricityMaps contributors (2024). electricitymaps-contrib (Version v1.155.0) [Computer software]. https://github.com/electricitymaps/electricitymaps-contrib.

    gen_cap_2022_state_merged.geojson

    trucking_energy_demand.geojson

    Grid electricity generation and net summer power capacity data is obtained from the state-level electricity database maintained by the United States Energy Information Administration.

    U.S. state boundaries obtained from this United States Department of the Interior U.S. Geological Survey ScienceBase-Catalog.

    Annual electricity generation by state

    Net summer capacity by state

    Shapefile with U.S. state boundaries

    Attribution for electricity generation and capacity data: U.S. Energy Information Administration (Aug 2024). Available from: https://www.eia.gov/electricity/data/state/. In the public domain.

    electricity_rates_by_state_merged.geojson

    Commercial electricity prices are obtained from the Electricity database maintained by the United States Energy Information Administration.

    Electricity rate by state

    Attribution: U.S. Energy Information Administration (Aug 2024). Available from: https://www.eia.gov/electricity/data.php. In the public domain.

    demand_charges_merged.geojson

    demand_charges_by_state.geojson

    Maximum historical demand charges for each state and zip code are derived from a dataset compiled by the National Renewable Energy Laboratory in this this Data Catalog.

    Historical demand charge dataset

    The original dataset is compiled by the National Renewable Energy Laboratory (NREL), the U.S. Department of Energy (DOE), and the Alliance for Sustainable Energy, LLC ('Alliance').

    Attribution: McLaren, Joyce, Pieter Gagnon, Daniel Zimny-Schmitt, Michael DeMinco, and Eric Wilson. 2017. 'Maximum demand charge rates for commercial and industrial electricity tariffs in the United States.' NREL Data Catalog. Golden, CO: National Renewable Energy Laboratory. Last updated: July 24, 2024. DOI: 10.7799/1392982.

    eastcoast.geojson

    midwest.geojson

    la_i710.geojson

    h2la.geojson

    bayarea.geojson

    saltlake.geojson

    northeast.geojson

    Highway corridors and regions targeted for heavy duty vehicle infrastructure projects are derived from a public announcement on February 15, 2023 by the United States Department of Energy.

    The shapefile with Bay area boundaries is obtained from this Berkeley Library dataset.

    The shapefile with Utah county boundaries is obtained from this dataset from the Utah Geospatial Resource Center.

    Shapefile for Bay Area country boundaries

    Shapefile for counties in Utah

    Attribution for public announcement: United States Department of Energy. Biden-Harris Administration Announces Funding for Zero-Emission Medium- and Heavy-Duty Vehicle Corridors, Expansion of EV Charging in Underserved Communities (2023). Available from https://www.energy.gov/articles/biden-harris-administration-announces-funding-zero-emission-medium-and-heavy-duty-vehicle.

    Attribution for Bay area boundaries: San Francisco (Calif.). Department Of Telecommunications and Information Services. Bay Area Counties. 2006. In the public domain.

    Attribution for Utah boundaries: Utah Geospatial Resource Center & Lieutenant Governor's Office. Utah County Boundaries (2023). Available from https://gis.utah.gov/products/sgid/boundaries/county/.

    License for Utah boundaries: Creative Commons 4.0 International License.

    incentives_and_regulations/*.geojson

    State-level incentives and regulations targeting heavy duty vehicles are collected from the State Laws and Incentives database maintained by the United States Department of Energy's Alternative Fuels Data Center.

    Data was collected manually from the State Laws and Incentives database.

    Attribution: U.S. Department of Energy, Energy Efficiency and Renewable Energy, Alternative Fuels Data Center. State Laws and Incentives. Accessed on Aug 5, 2024 from: https://afdc.energy.gov/laws/state. In the public domain.

    These data and software code ("Data") are provided by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC ("Alliance"), for the U.S. Department of Energy ("DOE"), and may be used for any purpose whatsoever.

    costs_and_emissions/*.geojson

    diesel_price_by_state.geojson

    trucking_energy_demand.geojson

    Lifecycle costs and emissions of electric and diesel trucking are evaluated by adapting the model developed by Moreno Sader et al., and calibrated to the Run on Less dataset for the Tesla Semi collected from the 2023 PepsiCo Semi pilot by the North American Council for Freight Efficiency.

    In

  2. World Countries Generalized

    • hub.arcgis.com
    • covid19.esriuk.com
    • +2more
    Updated May 5, 2022
    + more versions
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    Esri (2022). World Countries Generalized [Dataset]. https://hub.arcgis.com/datasets/esri::world-countries-generalized/about
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    Dataset updated
    May 5, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    World,
    Description

    World Countries Generalized provides a generalized basemap layer for the countries of the world. It has fields for official names and country codes. The generalized boundaries improve draw performance and effectiveness at global and continental levels.This layer is best viewed out beyond a maximum scale (zoomed in) of 1:5,000,000.The sources of this dataset are Esri, Garmin, and U.S. Central Intelligence Agency (The World Factbook). It is updated every 12-18 months as country names or significant borders change.

  3. a

    Fuquay-Varina Utilities - Water System - Fire Department Connection (FDC)

    • data-tofv.opendata.arcgis.com
    • data-wake.opendata.arcgis.com
    • +2more
    Updated Mar 11, 2022
    + more versions
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    Town of Fuquay-Varina (2022). Fuquay-Varina Utilities - Water System - Fire Department Connection (FDC) [Dataset]. https://data-tofv.opendata.arcgis.com/items/23cc2bd80d7b4591bdb6da5cb6a51907
    Explore at:
    Dataset updated
    Mar 11, 2022
    Dataset authored and provided by
    Town of Fuquay-Varina
    Area covered
    Description

    Fire Department Connections (FDC's) points within Fuquay-Varina. These are primarily privately owned and maintained. Mapping of FDC's primarily began from 2015 and later from as-built information provided by new developments, so this should be considered a very limited dataset. Please note that ALL public utility data layers can be downloaded in a single .mpkx (ArcGIS Pro map package file), updated every Friday evening. This .mpkx file can be opened directly with ArcGIS Pro version 3+. Alternatively, you can extract the file geodatabase within it by renaming the file ending .mpkx to .zip and treating it like a zip archive file, for use in any version of ArcGIS Pro or ArcMap software. You can also use QGIS, a powerful, free, and open-source GIS software.The Town of Fuquay-Varina creates, maintains, and serves out a variety of utility information to the public, including its Potable Water System, Sanitary Sewer System, and Stormwater Collection System features. This is the same utility data displayed in our public web map. This utility data includes some features designated as 'private' that are not owned or maintained by the Town, but may be helpful for modeling and other informational purposes. Please pay particular attention to the terms of use and disclaimer associated with these data. Some data includes the use of Subtypes and Domains that may not translate well to Shapefile or GeoJSON downloads available through our Open Data site. Please beware the dangers of cartographic misrepresentation if you are unfamiliar with filtering and symbolizing data based on attributes. Water System Layers:Water LinesWater ValvesWater ManholesFire HydrantsFire Department ConnectionsWater MetersRPZ (Backflow Preventers)Water TankWater Booster StationsHarnett County Water District AreaSewer System Layers:Gravity Sewer LinesForced Sewer LinesSewer ManholesSewer ValvesSewer CleanoutsSewer Pump StationsWastewater Treatment PlantsStormwater System Layers:Stormwater Lines (Pipes)Stormwater Points (Inlets/Outlets/Manholes)Stormwater Control Measure Points (SCM's, such as Wet Ponds / Retention Basins)

  4. CA Geographic Boundaries

    • data.ca.gov
    • s.cnmilf.com
    • +1more
    shp
    Updated May 3, 2024
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    California Department of Technology (2024). CA Geographic Boundaries [Dataset]. https://data.ca.gov/dataset/ca-geographic-boundaries
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    shp(10153125), shp(136046), shp(2597712)Available download formats
    Dataset updated
    May 3, 2024
    Dataset authored and provided by
    California Department of Technologyhttp://cdt.ca.gov/
    Description

    This dataset contains shapefile boundaries for CA State, counties and places from the US Census Bureau's 2023 MAF/TIGER database. Current geography in the 2023 TIGER/Line Shapefiles generally reflects the boundaries of governmental units in effect as of January 1, 2023.

  5. b

    North American Rail Network Lines

    • geodata.bts.gov
    • geodata.colorado.gov
    • +8more
    Updated Jul 1, 1995
    + more versions
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    U.S. Department of Transportation: ArcGIS Online (1995). North American Rail Network Lines [Dataset]. https://geodata.bts.gov/datasets/usdot::north-american-rail-network-lines/about
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    Dataset updated
    Jul 1, 1995
    Dataset authored and provided by
    U.S. Department of Transportation: ArcGIS Online
    Area covered
    Description

    The North American Rail Network (NARN) Rail Lines dataset was created in 2016 and was updated on July 18, 2025 from the Federal Railroad Administration (FRA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The NARN Rail Lines dataset is a database that provides ownership, trackage rights, type, passenger, STRACNET, and geographic reference for North America's railway system at 1:24,000 or better within the United States. The data set covers all 50 States, the District of Columbia, Mexico, and Canada. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1528950

  6. Snow Plow Truck Location AVL (Iowa DOT)

    • data.iowadot.gov
    • public-iowadot.opendata.arcgis.com
    • +1more
    Updated Oct 17, 2018
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    Iowa Department of Transportation (2018). Snow Plow Truck Location AVL (Iowa DOT) [Dataset]. https://data.iowadot.gov/datasets/20a0c10c06a54240b5f2893e0187e22c
    Explore at:
    Dataset updated
    Oct 17, 2018
    Dataset authored and provided by
    Iowa Department of Transportationhttps://iowadot.gov/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This layer contains all active Iowa DOT Plow Trucks that are traveling more than 3 MPH. This data is updated every 2 minutes; 24 hours a day/7 days a week. Real-Time Data Formats: GeoJSON | JSONNotesFor Date/Time Queries: Use MODIFIEDDT as it is a valid UTC timestamp. There is a MODIFIEDDT_UTC_OFFSET that can be used if needed. LOGDT is in Local-Iowa time.When viewing in ArcGIS Online or Open Data, your local timezone offset is applied AUTOMATICALLY. This will make the UTC time appear correctly, while the local Iowa time will appear earlier than the UTC time.ArcGIS Open Data file formats will CACHE data. If you are looking to pull data to show real-time data, you will need to use the REST service. Further documentation can be found here.

  7. V

    GIS | Virginia County Boundaries

    • data.virginia.gov
    • data.dumfriesva.gov
    csv, json, rdf, xsl
    Updated May 25, 2023
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    Dumfries (2023). GIS | Virginia County Boundaries [Dataset]. https://data.virginia.gov/dataset/gis-virginia-county-boundaries1
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    xsl, json, csv, rdfAvailable download formats
    Dataset updated
    May 25, 2023
    Dataset provided by
    data.dumfriesva.gov
    Authors
    Dumfries
    Area covered
    Virginia
    Description
    1. US Census Bureau Cartographic Boundary File of county boundaries for the Commonwealth of Virginia.

    From the US Census Bureau: "The cartographic boundary files are simplified representations of selected geographic areas from the Census Bureau’s MAF/TIGER geographic database. These boundary files are specifically designed for small scale thematic mapping."

  8. w

    Fuquay-Varina Utilities - Water System - Water Valves

    • data.wake.gov
    • hub.arcgis.com
    • +2more
    Updated Mar 12, 2022
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    Town of Fuquay-Varina (2022). Fuquay-Varina Utilities - Water System - Water Valves [Dataset]. https://data.wake.gov/datasets/71e51755fc224aa3aa398c7c92d53f47
    Explore at:
    Dataset updated
    Mar 12, 2022
    Dataset authored and provided by
    Town of Fuquay-Varina
    Area covered
    Description

    Water Valves within Fuquay-Varina. Please note that some of these valves are privately owned and maintained. Pay attention to the WValve_Subtype field and OWNEDBY fields. Please note that ALL public utility data layers can be downloaded in a single .mpkx (ArcGIS Pro map package file), updated every Friday evening. This .mpkx file can be opened directly with ArcGIS Pro version 3+. Alternatively, you can extract the file geodatabase within it by renaming the file ending .mpkx to .zip and treating it like a zip archive file, for use in any version of ArcGIS Pro or ArcMap software. You can also use QGIS, a powerful, free, and open-source GIS software.The Town of Fuquay-Varina creates, maintains, and serves out a variety of utility information to the public, including its Potable Water System, Sanitary Sewer System, and Stormwater Collection System features. This is the same utility data displayed in our public web map. This utility data includes some features designated as 'private' that are not owned or maintained by the Town, but may be helpful for modeling and other informational purposes. Please pay particular attention to the terms of use and disclaimer associated with these data. Some data includes the use of Subtypes and Domains that may not translate well to Shapefile or GeoJSON downloads available through our Open Data site. Please beware the dangers of cartographic misrepresentation if you are unfamiliar with filtering and symbolizing data based on attributes. Water System Layers:Water LinesWater ValvesWater ManholesFire HydrantsFire Department ConnectionsWater MetersRPZ (Backflow Preventers)Water TankWater Booster StationsHarnett County Water District AreaSewer System Layers:Gravity Sewer LinesForced Sewer LinesSewer ManholesSewer ValvesSewer CleanoutsSewer Pump StationsWastewater Treatment PlantsStormwater System Layers:Stormwater Lines (Pipes)Stormwater Points (Inlets/Outlets/Manholes)Stormwater Control Measure Points (SCM's, such as Wet Ponds / Retention Basins)

  9. w

    Fuquay-Varina Utilities - Sewer System - Sewer Valves

    • data.wake.gov
    • data-wake.opendata.arcgis.com
    • +3more
    Updated Mar 18, 2022
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    Town of Fuquay-Varina (2022). Fuquay-Varina Utilities - Sewer System - Sewer Valves [Dataset]. https://data.wake.gov/datasets/tofv::fuquay-varina-utilities-sewer-system-sewer-valves
    Explore at:
    Dataset updated
    Mar 18, 2022
    Dataset authored and provided by
    Town of Fuquay-Varina
    Area covered
    Description

    Sewer system valve points in Fuquay-Varina. These are primarily forced sewer pipe valves. Please note that ALL public utility data layers can be downloaded in a single .mpkx (ArcGIS Pro map package file), updated every Friday evening. This .mpkx file can be opened directly with ArcGIS Pro version 3+. Alternatively, you can extract the file geodatabase within it by renaming the file ending .mpkx to .zip and treating it like a zip archive file, for use in any version of ArcGIS Pro or ArcMap software. You can also use QGIS, a powerful, free, and open-source GIS software.The Town of Fuquay-Varina creates, maintains, and serves out a variety of utility information to the public, including its Potable Water System, Sanitary Sewer System, and Stormwater Collection System features. This is the same utility data displayed in our public web map. This utility data includes some features designated as 'private' that are not owned or maintained by the Town, but may be helpful for modeling and other informational purposes. Please pay particular attention to the terms of use and disclaimer associated with these data. Some data includes the use of Subtypes and Domains that may not translate well to Shapefile or GeoJSON downloads available through our Open Data site. Please beware the dangers of cartographic misrepresentation if you are unfamiliar with filtering and symbolizing data based on attributes. Water System Layers:Water LinesWater ValvesWater ManholesFire HydrantsFire Department ConnectionsWater MetersWater Meter VaultsRPZ (Backflow Preventers)Water TankWater Booster StationsHarnett County Water District AreaSewer System Layers:Gravity Sewer LinesForced Sewer LinesSewer ManholesSewer ValvesSewer CleanoutsSewer Pump StationsWastewater Treatment PlantsStormwater System Layers:Stormwater Lines (Pipes)Stormwater Points (Inlets/Outlets/Manholes)Stormwater Control Measure Points (SCM's, such as Wet Ponds / Retention Basins)

  10. W

    California Natural Gas Service Areas

    • wifire-data.sdsc.edu
    • hub.arcgis.com
    • +1more
    csv, esri rest +4
    Updated Apr 26, 2019
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    CA Governor's Office of Emergency Services (2019). California Natural Gas Service Areas [Dataset]. https://wifire-data.sdsc.edu/dataset/california-natural-gas-service-areas
    Explore at:
    csv, kml, html, esri rest, zip, geojsonAvailable download formats
    Dataset updated
    Apr 26, 2019
    Dataset provided by
    CA Governor's Office of Emergency Services
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    California
    Description

    This data is a graphic representation of natural gas utility service territories. The file has not been certified by a Professional Surveyor. This data is not suitable for legal purposes. The purpose of this data is to provide a generalized statewide view of electric service territories. The data does not include individual or commercial releases. A release is an agreement between adjoining utilities that release customers from one utility to be served by the adjoining utility. A customer release does not change the territory boundary. The file has been compiled from numerous sources and as such contains errors. The data only contains the electric utility service territories and the name of the utility.The data was derived from ESRI zipcode boundary and utility companies.



    California Energy Commission's Open Data Portal.

  11. w

    Fuquay-Varina Utilities - Sewer System - Sewer Manholes

    • data.wake.gov
    • data-tofv.opendata.arcgis.com
    • +3more
    Updated Mar 18, 2022
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    Town of Fuquay-Varina (2022). Fuquay-Varina Utilities - Sewer System - Sewer Manholes [Dataset]. https://data.wake.gov/datasets/tofv::fuquay-varina-utilities-sewer-system-sewer-manholes
    Explore at:
    Dataset updated
    Mar 18, 2022
    Dataset authored and provided by
    Town of Fuquay-Varina
    Area covered
    Description

    Sewer System Manhole points in Fuquay-Varina. These are primarily publicly-maintained gravity sewer manhole points. However, there are also some privately-owned and privately-maintained manholes included in this dataset; they are mapped for modeling and informational purposes to provide more context for the complete Town sewer network.Please note that ALL public utility data layers can be downloaded in a single .mpkx (ArcGIS Pro map package file), updated every Friday evening. This .mpkx file can be opened directly with ArcGIS Pro version 3+. Alternatively, you can extract the file geodatabase within it by renaming the file ending .mpkx to .zip and treating it like a zip archive file, for use in any version of ArcGIS Pro or ArcMap software. You can also use QGIS, a powerful, free, and open-source GIS software.The Town of Fuquay-Varina creates, maintains, and serves out a variety of utility information to the public, including its Potable Water System, Sanitary Sewer System, and Stormwater Collection System features. This is the same utility data displayed in our public web map. This utility data includes some features designated as 'private' that are not owned or maintained by the Town, but may be helpful for modeling and other informational purposes. Please pay particular attention to the terms of use and disclaimer associated with these data. Some data includes the use of Subtypes and Domains that may not translate well to Shapefile or GeoJSON downloads available through our Open Data site. Please beware the dangers of cartographic misrepresentation if you are unfamiliar with filtering and symbolizing data based on attributes. Water System Layers:Water LinesWater ValvesWater ManholesFire HydrantsFire Department ConnectionsWater MetersRPZ (Backflow Preventers)Water TankWater Booster StationsHarnett County Water District AreaSewer System Layers:Gravity Sewer LinesForced Sewer LinesSewer ManholesSewer ValvesSewer CleanoutsSewer Pump StationsWastewater Treatment PlantsStormwater System Layers:Stormwater Lines (Pipes)Stormwater Points (Inlets/Outlets/Manholes)Stormwater Control Measure Points (SCM's, such as Wet Ponds / Retention Basins)

  12. California Counties

    • data.ca.gov
    • catalog.data.gov
    • +1more
    Updated Mar 6, 2025
    + more versions
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    California Department of Education (2025). California Counties [Dataset]. https://data.ca.gov/dataset/california-counties
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    gdb, kml, geojson, xlsx, csv, zip, html, txt, gpkg, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    Mar 6, 2025
    Dataset authored and provided by
    California Department of Educationhttps://www.cde.ca.gov/
    Area covered
    California
    Description

    This layer contains the boundaries for California’s 58 counties. County features are derived from the US Census Bureau's TIGER/Line database and have been clipped to the coastal boundary line and designed to overlay with the California Department of Education’s (CDE) educational boundary layers.

  13. HIFLD Open - Transportation Air Datasets (Feature Layer)

    • data.amerigeoss.org
    esri rest, html
    Updated Jul 9, 2020
    + more versions
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    ESRI (2020). HIFLD Open - Transportation Air Datasets (Feature Layer) [Dataset]. https://data.amerigeoss.org/nl/dataset/hifld-open-transportation-air-datasets-feature-layer
    Explore at:
    esri rest, htmlAvailable download formats
    Dataset updated
    Jul 9, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Description

    Included HIFLD Open Layers:

    • aircraft_landing_facilities
    • faa_regions
    • runways

    Downloaded from the HILFD archives May 2019. Unveiled in February 2016, the Homeland Infrastructure Foundation-Level Data (HIFLD) Open data portal contains national foundation-level geospatial critical infrastructure data within the public domain that can be useful to support community preparedness, response and recovery, resiliency, research, and more. HIFLD Open represents a new approach to meeting the changing needs of our stakeholders and consumers. Once referred to as Homeland Security Infrastructure Program (HSIP) Freedom, HIFLD Open contains 320 public datasets— consisting of re-hosted public data and direct pointers to live data services. These layers are accessible in a variety of formats including: CSV, KML, Shapefiles, and File Geodatabases. Developers can access GeoJSON and GeoService APIs to harness this data. HIFLD Open is accessible via the following link: https://hifldgeoplatform.opendata.arcgis.com/. As part of the HIFLD mission to build a more transparent and collaborative ecosystem for information sharing, the HIFLD Open Portal is integrated with the Geospatial Platform (www.geoplatform.gov) through Data.gov and other data providers.

    What’s in HIFLD Open? HIFLD Open is a diverse set of data layers which have been categorized to better enable discovery based on a user’s interests and data needs. Data can also be easily found using the search functionality and other features on the site. HIFLD contains data on a wide range of topics and is accessed through the following categorical folders: • Agriculture • Borders • Boundaries • Chemicals • Commercial • Communications • Education • Emergency Services • Energy • Finance • Food Industry • Geonames • Government • Law Enforcement • Mail Shipping • Mining • National Flood Hazard • Natural Hazards • Public Health • Public Venues • Transportation Air • Transportation Ground • Transportation Water • Water Supply

  14. b

    North American Roads

    • geodata.bts.gov
    • hub.arcgis.com
    • +2more
    Updated Oct 27, 2020
    + more versions
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    U.S. Department of Transportation: ArcGIS Online (2020). North American Roads [Dataset]. https://geodata.bts.gov/datasets/usdot::north-american-roads/about
    Explore at:
    Dataset updated
    Oct 27, 2020
    Dataset authored and provided by
    U.S. Department of Transportation: ArcGIS Online
    Area covered
    Description

    The North American Roads dataset was compiled on October 27, 2020 from the Bureau of Transportation Statistics (BTS) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). This dataset contains geospatial information regarding major roadways in North America. On March 31, 2025, the errant records with a value of 2 in the "NHS" field were corrected to have a value of 7 (Other NHS). The data set covers the 48 contiguous United States plus the District of Columbia, Alaska, Hawaii, Canada and Mexico. The nominal scale of the data set is 1:100,000. The data within the North American Roads layer is a compilation of data from Natural Resources Canada, USDOT’s Federal Highway Administration, and the Mexican Transportation Institute. North American Roads is a digital single-line representation of major roads and highways for Canada, the United States, and Mexico with consistent definitions by road class, jurisdiction, lane counts, speed limits and surface type.

  15. Data from: National Highway System

    • data.ca.gov
    • gis.data.ca.gov
    • +1more
    Updated Jul 18, 2023
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    Caltrans (2023). National Highway System [Dataset]. https://data.ca.gov/dataset/national-highway-system
    Explore at:
    kml, html, zip, csv, arcgis geoservices rest api, geojsonAvailable download formats
    Dataset updated
    Jul 18, 2023
    Dataset authored and provided by
    Caltranshttp://dot.ca.gov/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The National Highway System consists of a network of roads important to the economy, defense and mobility. On October 1, 2012 the existing National Highway System (NHS) was expanded to include all existing Principal Arterials (i.e. Functional Classifications 1, 2 and 3) to the new Enhanced NHS.

    Under MAP-21, the Enhanced NHS is composed of rural and urban roads nationwide serving major population centers, international border crossings, intermodal transportation facilities, and major travel destinations.The NHS includes:

    The Interstate System.

    • Other Principal arterials and border crossings on those routes (including other urban and rural principal arterial routes, and border crossings on those routes, that were not included on the NHS before the date of enactment of the MAP-21).
    • Intermodal connectors -- highways that provide motor vehicle access between the NHS and major intermodal transportation facilities.
    • STRAHNET -- the network of highways important to U.S. strategic defense.
    • STRAHNET connectors to major military installations.

  16. FSTopo PBS Reference Quadrangle (Feature Layer)

    • agdatacommons.nal.usda.gov
    • datadiscoverystudio.org
    • +6more
    bin
    Updated Nov 24, 2025
    + more versions
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    U.S. Forest Service (2025). FSTopo PBS Reference Quadrangle (Feature Layer) [Dataset]. https://agdatacommons.nal.usda.gov/articles/dataset/FSTopo_PBS_Reference_Quadrangle_Feature_Layer_/28710629
    Explore at:
    binAvailable download formats
    Dataset updated
    Nov 24, 2025
    Dataset provided by
    U.S. Department of Agriculture Forest Servicehttp://fs.fed.us/
    Authors
    U.S. Forest Service
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This data portrays the FSTopo quad footprint. Quadrangles with a Vintage (greater than zero) make up the FSTopo area of interest.Within the FSTopo database, features are represented as lines, points, or polygons, with descriptive subtype attribute codes attached to describe the cartographic symbology characteristics of features. Annotation features are represented as stand-alone map text collected relative to the scale of the topographic quadrangle. The FSTopo database was originally populated with Cartographic Feature File (CFF) data which was digitized from either the Primary Base Series (PBS) quadrangles or U.S. Geological Survey (USGS) topographic map series quadrangles. Over time, the legacy CFF data is being replaced (at least partially) with data from nationally standardized sources. Data completeness reflects the content of the original source graphic, digital correction guide information, stereoscopic source, monoscopic source, supplemented with cadastral source information. Forests and Quadrangles may have undergone revision at varying dates. The update revision uses a variety of sources, including Digital Orthophoto Quad (DOQ) imagery, NAIP imagery, cadastral information, other vector data sources, and field-prepared correction guides in hardcopy or digital format.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService OGC WMS CSV Shapefile GeoJSON KML For complete information, please visit https://data.gov.

  17. Data from: public health departments

    • data.amerigeoss.org
    csv, esri rest +4
    Updated Jul 9, 2020
    + more versions
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    ESRI (2020). public health departments [Dataset]. https://data.amerigeoss.org/ca/dataset/public-health-departments1
    Explore at:
    geojson, zip, html, kml, csv, esri restAvailable download formats
    Dataset updated
    Jul 9, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Description

    Included HIFLD Open Layers:

    • hospitals
    • nursing_homes
    • pharmacies
    • public_health_departments
    • urgent_care_facilities
    • vha_medical_facilities

    Downloaded from the HILFD archives May 2019. Unveiled in February 2016, the Homeland Infrastructure Foundation-Level Data (HIFLD) Open data portal contains national foundation-level geospatial critical infrastructure data within the public domain that can be useful to support community preparedness, response and recovery, resiliency, research, and more. HIFLD Open represents a new approach to meeting the changing needs of our stakeholders and consumers. Once referred to as Homeland Security Infrastructure Program (HSIP) Freedom, HIFLD Open contains 320 public datasets— consisting of re-hosted public data and direct pointers to live data services. These layers are accessible in a variety of formats including: CSV, KML, Shapefiles, and File Geodatabases. Developers can access GeoJSON and GeoService APIs to harness this data. HIFLD Open is accessible via the following link: https://hifldgeoplatform.opendata.arcgis.com/. As part of the HIFLD mission to build a more transparent and collaborative ecosystem for information sharing, the HIFLD Open Portal is integrated with the Geospatial Platform (www.geoplatform.gov) through Data.gov and other data providers.

    What’s in HIFLD Open? HIFLD Open is a diverse set of data layers which have been categorized to better enable discovery based on a user’s interests and data needs. Data can also be easily found using the search functionality and other features on the site. HIFLD contains data on a wide range of topics and is accessed through the following categorical folders: • Agriculture • Borders • Boundaries • Chemicals • Commercial • Communications • Education • Emergency Services • Energy • Finance • Food Industry • Geonames • Government • Law Enforcement • Mail Shipping • Mining • National Flood Hazard • Natural Hazards • Public Health • Public Venues • Transportation Air • Transportation Ground • Transportation Water • Water Supply

  18. Z

    Green Roofs Footprints for New York City, Assembled from Available Data and...

    • data.niaid.nih.gov
    • data-staging.niaid.nih.gov
    • +1more
    Updated Jan 24, 2020
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    Treglia, Michael L.; McPhearson, Timon; Sanderson, Eric W.; Yetman, Greg; Maxwell, Emily Nobel (2020). Green Roofs Footprints for New York City, Assembled from Available Data and Remote Sensing [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_1469673
    Explore at:
    Dataset updated
    Jan 24, 2020
    Dataset provided by
    Center for International Earth Science Information Network, Columbia University
    Wildlife Conservation Society
    New York City Program, The Nature Conservancy
    Urban Systems Lab, The New School
    Authors
    Treglia, Michael L.; McPhearson, Timon; Sanderson, Eric W.; Yetman, Greg; Maxwell, Emily Nobel
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Area covered
    New York
    Description

    Summary:

    The files contained herein represent green roof footprints in NYC visible in 2016 high-resolution orthoimagery of NYC (described at https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_AerialImagery.md). Previously documented green roofs were aggregated in 2016 from multiple data sources including from NYC Department of Parks and Recreation and the NYC Department of Environmental Protection, greenroofs.com, and greenhomenyc.org. Footprints of the green roof surfaces were manually digitized based on the 2016 imagery, and a sample of other roof types were digitized to create a set of training data for classification of the imagery. A Mahalanobis distance classifier was employed in Google Earth Engine, and results were manually corrected, removing non-green roofs that were classified and adjusting shape/outlines of the classified green roofs to remove significant errors based on visual inspection with imagery across multiple time points. Ultimately, these initial data represent an estimate of where green roofs existed as of the imagery used, in 2016.

    These data are associated with an existing GitHub Repository, https://github.com/tnc-ny-science/NYC_GreenRoofMapping, and as needed and appropriate pending future work, versioned updates will be released here.

    Terms of Use:

    The Nature Conservancy and co-authors of this work shall not be held liable for improper or incorrect use of the data described and/or contained herein. Any sale, distribution, loan, or offering for use of these digital data, in whole or in part, is prohibited without the approval of The Nature Conservancy and co-authors. The use of these data to produce other GIS products and services with the intent to sell for a profit is prohibited without the written consent of The Nature Conservancy and co-authors. All parties receiving these data must be informed of these restrictions. Authors of this work shall be acknowledged as data contributors to any reports or other products derived from these data.

    Associated Files:

    As of this release, the specific files included here are:

    GreenRoofData2016_20180917.geojson is in the human-readable, GeoJSON format, in geographic coordinates (Lat/Long, WGS84; EPSG 4263).

    GreenRoofData2016_20180917.gpkg is in the GeoPackage format, which is an Open Standard readable by most GIS software including Esri products (tested on ArcMap 10.3.1 and multiple versions of QGIS). This dataset is in the New York State Plan Coordinate System (units in feet) for the Long Island Zone, North American Datum 1983, EPSG 2263.

    GreenRoofData2016_20180917_Shapefile.zip is a zipped folder containing a Shapefile and associated files. Please note that some field names were truncated due to limitations of Shapefiles, but columns are in the same order as for other files and in the same order as listed below. This dataset is in the New York State Plan Coordinate System (units in feet) for the Long Island Zone, North American Datum 1983, EPSG 2263.

    GreenRoofData2016_20180917.csv is a comma-separated values file (CSV) with coordinates for centroids for the green roofs stored in the table itself. This allows for easily opening the data in a tool like spreadsheet software (e.g., Microsoft Excel) or a text editor.

    Column Information for the datasets:

    Some, but not all fields were joined to the green roof footprint data based on building footprint and tax lot data; those datasets are embedded as hyperlinks below.

    fid - Unique identifier

    bin - NYC Building ID Number based on overlap between green roof areas and a building footprint dataset for NYC from August, 2017. (Newer building footprint datasets do not have linkages to the tax lot identifier (bbl), thus this older dataset was used). The most current building footprint dataset should be available at: https://data.cityofnewyork.us/Housing-Development/Building-Footprints/nqwf-w8eh. Associated metadata for fields from that dataset are available at https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_BuildingFootprints.md.

    bbl - Boro Block and Lot number as a single string. This field is a tax lot identifier for NYC, which can be tied to the Digital Tax Map (http://gis.nyc.gov/taxmap/map.htm) and PLUTO/MapPLUTO (https://www1.nyc.gov/site/planning/data-maps/open-data/dwn-pluto-mappluto.page). Metadata for fields pulled from PLUTO/MapPLUTO can be found in the PLUTO Data Dictionary found on the aforementioned page. All joins to this bbl were based on MapPLUTO version 18v1.

    gr_area - Total area of the footprint of the green roof as per this data layer, in square feet, calculated using the projected coordinate system (EPSG 2263).

    bldg_area - Total area of the footprint of the associated building, in square feet, calculated using the projected coordinate system (EPSG 2263).

    prop_gr - Proportion of the building covered by green roof according to this layer (gr_area/bldg_area).

    cnstrct_yr - Year the building was constructed, pulled from the Building Footprint data.

    doitt_id - An identifier for the building assigned by the NYC Dept. of Information Technology and Telecommunications, pulled from the Building Footprint Data.

    heightroof - Height of the roof of the associated building, pulled from the Building Footprint Data.

    feat_code - Code describing the type of building, pulled from the Building Footprint Data.

    groundelev - Lowest elevation at the building level, pulled from the Building Footprint Data.

    qa - Flag indicating a positive QA/QC check (using multiple types of imagery); all data in this dataset should have 'Good'

    notes - Any notes about the green roof taken during visual inspection of imagery; for example, it was noted if the green roof appeared to be missing in newer imagery, or if there were parts of the roof for which it was unclear whether there was green roof area or potted plants.

    classified - Flag indicating whether the green roof was detected image classification. (1 for yes, 0 for no)

    digitized - Flag indicating whether the green roof was digitized prior to image classification and used as training data. (1 for yes, 0 for no)

    newlyadded - Flag indicating whether the green roof was detected solely by visual inspection after the image classification and added. (1 for yes, 0 for no)

    original_source - Indication of what the original data source was, whether a specific website, agency such as NYC Dept. of Parks and Recreation (DPR), or NYC Dept. of Environmental Protection (DEP). Multiple sources are separated by a slash.

    address - Address based on MapPLUTO, joined to the dataset based on bbl.

    borough - Borough abbreviation pulled from MapPLUTO.

    ownertype - Owner type field pulled from MapPLUTO.

    zonedist1 - Zoning District 1 type pulled from MapPLUTO.

    spdist1 - Special District 1 pulled from MapPLUTO.

    bbl_fixed - Flag to indicate whether bbl was manually fixed. Since tax lot data may have changed slightly since the release of the building footprint data used in this work, a small percentage of bbl codes had to be manually updated based on overlay between the green roof footprint and the MapPLUTO data, when no join was feasible based on the bbl code from the building footprint data. (1 for yes, 0 for no)

    For GreenRoofData2016_20180917.csv there are two additional columns, representing the coordinates of centroids in geographic coordinates (Lat/Long, WGS84; EPSG 4263):

    xcoord - Longitude in decimal degrees.

    ycoord - Latitude in decimal degrees.

    Acknowledgements:

    This work was primarily supported through funding from the J.M. Kaplan Fund, awarded to the New York City Program of The Nature Conservancy, with additional support from the New York Community Trust, through New York City Audubon and the Green Roof Researchers Alliance.

  19. d

    500 Cities: City Boundaries

    • catalog.data.gov
    • healthdata.gov
    • +5more
    Updated Feb 3, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). 500 Cities: City Boundaries [Dataset]. https://catalog.data.gov/dataset/500-cities-city-boundaries
    Explore at:
    Dataset updated
    Feb 3, 2025
    Dataset provided by
    Centers for Disease Control and Prevention
    Description

    This city boundary shapefile was extracted from Esri Data and Maps for ArcGIS 2014 - U.S. Populated Place Areas. This shapefile can be joined to 500 Cities city-level Data (GIS Friendly Format) in a geographic information system (GIS) to make city-level maps.

  20. m

    Maryland Physical Boundaries - County Boundaries (Detailed)

    • data.imap.maryland.gov
    • dev-maryland.opendata.arcgis.com
    Updated Feb 9, 2016
    + more versions
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    ArcGIS Online for Maryland (2016). Maryland Physical Boundaries - County Boundaries (Detailed) [Dataset]. https://data.imap.maryland.gov/datasets/2315ef0b071a4ec59420e3d342dbcfe2
    Explore at:
    Dataset updated
    Feb 9, 2016
    Dataset authored and provided by
    ArcGIS Online for Maryland
    Area covered
    Description

    This layer contains detailed outlines of Maryland counties. The Maryland land county boundaries were built using political county boundaries and the National Hydrology Data (NHD). Land boundaries are a key geographic featue in our mapping process.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Last Updated: UnknownFeature Service Link:https://mdgeodata.md.gov/imap/rest/services/Boundaries/MD_PhysicalBoundaries/FeatureServer/0

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MacDonell, Danika; Borrero, Micah; Bashir, Noman; MIT Climate & Sustainability Consortium (2025). GeoJSON files for the MCSC's Trucking Industry Decarbonization Explorer (Geo-TIDE) [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_13207715

GeoJSON files for the MCSC's Trucking Industry Decarbonization Explorer (Geo-TIDE)

Explore at:
Dataset updated
Feb 18, 2025
Dataset provided by
Massachusetts Institute of Technology
Authors
MacDonell, Danika; Borrero, Micah; Bashir, Noman; MIT Climate & Sustainability Consortium
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Summary

Geojson files used to visualize geospatial layers relevant to identifying and assessing trucking fleet decarbonization opportunities with the MIT Climate & Sustainability Consortium's Geospatial Trucking Industry Decarbonization Explorer (Geo-TIDE) tool.

Relevant Links

Link to the online version of the tool (requires creation of a free user account).

Link to GitHub repo with source code to produce this dataset and deploy the Geo-TIDE tool locally.

Funding

This dataset was produced with support from the MIT Climate & Sustainability Consortium.

Original Data Sources

These geojson files draw from and synthesize a number of different datasets and tools. The original data sources and tools are described below:

Filename(s) Description of Original Data Source(s) Link(s) to Download Original Data License and Attribution for Original Data Source(s)

faf5_freight_flows/*.geojson

trucking_energy_demand.geojson

highway_assignment_links_*.geojson

infrastructure_pooling_thought_experiment/*.geojson

Regional and highway-level freight flow data obtained from the Freight Analysis Framework Version 5. Shapefiles for FAF5 region boundaries and highway links are obtained from the National Transportation Atlas Database. Emissions attributes are evaluated by incorporating data from the 2002 Vehicle Inventory and Use Survey and the GREET lifecycle emissions tool maintained by Argonne National Lab.

Shapefile for FAF5 Regions

Shapefile for FAF5 Highway Network Links

FAF5 2022 Origin-Destination Freight Flow database

FAF5 2022 Highway Assignment Results

Attribution for Shapefiles: United States Department of Transportation Bureau of Transportation Statistics National Transportation Atlas Database (NTAD). Available at: https://geodata.bts.gov/search?collection=Dataset.

License for Shapefiles: This NTAD dataset is a work of the United States government as defined in 17 U.S.C. § 101 and as such are not protected by any U.S. copyrights. This work is available for unrestricted public use.

Attribution for Origin-Destination Freight Flow database: National Transportation Research Center in the Oak Ridge National Laboratory with funding from the Bureau of Transportation Statistics and the Federal Highway Administration. Freight Analysis Framework Version 5: Origin-Destination Data. Available from: https://faf.ornl.gov/faf5/Default.aspx. Obtained on Aug 5, 2024. In the public domain.

Attribution for the 2022 Vehicle Inventory and Use Survey Data: United States Department of Transportation Bureau of Transportation Statistics. Vehicle Inventory and Use Survey (VIUS) 2002 [supporting datasets]. 2024. https://doi.org/10.21949/1506070

Attribution for the GREET tool (original publication): Argonne National Laboratory Energy Systems Division Center for Transportation Research. GREET Life-cycle Model. 2014. Available from this link.

Attribution for the GREET tool (2022 updates): Wang, Michael, et al. Summary of Expansions and Updates in GREET® 2022. United States. https://doi.org/10.2172/1891644

grid_emission_intensity/*.geojson

Emission intensity data is obtained from the eGRID database maintained by the United States Environmental Protection Agency.

eGRID subregion boundaries are obtained as a shapefile from the eGRID Mapping Files database.

eGRID database

Shapefile with eGRID subregion boundaries

Attribution for eGRID data: United States Environmental Protection Agency: eGRID with 2022 data. Available from https://www.epa.gov/egrid/download-data. In the public domain.

Attribution for shapefile: United States Environmental Protection Agency: eGRID Mapping Files. Available from https://www.epa.gov/egrid/egrid-mapping-files. In the public domain.

US_elec.geojson

US_hy.geojson

US_lng.geojson

US_cng.geojson

US_lpg.geojson

Locations of direct current fast chargers and refueling stations for alternative fuels along U.S. highways. Obtained directly from the Station Data for Alternative Fuel Corridors in the Alternative Fuels Data Center maintained by the United States Department of Energy Office of Energy Efficiency and Renewable Energy.

US_elec.geojson

US_hy.geojson

US_lng.geojson

US_cng.geojson

US_lpg.geojson

Attribution: U.S. Department of Energy, Energy Efficiency and Renewable Energy. Alternative Fueling Station Corridors. 2024. Available from: https://afdc.energy.gov/corridors. In the public domain.

These data and software code ("Data") are provided by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC ("Alliance"), for the U.S. Department of Energy ("DOE"), and may be used for any purpose whatsoever.

daily_grid_emission_profiles/*.geojson

Hourly emission intensity data obtained from ElectricityMaps.

Original data can be downloaded as csv files from the ElectricityMaps United States of America database

Shapefile with region boundaries used by ElectricityMaps

License: Open Database License (ODbL). Details here: https://www.electricitymaps.com/data-portal

Attribution for csv files: Electricity Maps (2024). United States of America 2022-23 Hourly Carbon Intensity Data (Version January 17, 2024). Electricity Maps Data Portal. https://www.electricitymaps.com/data-portal.

Attribution for shapefile with region boundaries: ElectricityMaps contributors (2024). electricitymaps-contrib (Version v1.155.0) [Computer software]. https://github.com/electricitymaps/electricitymaps-contrib.

gen_cap_2022_state_merged.geojson

trucking_energy_demand.geojson

Grid electricity generation and net summer power capacity data is obtained from the state-level electricity database maintained by the United States Energy Information Administration.

U.S. state boundaries obtained from this United States Department of the Interior U.S. Geological Survey ScienceBase-Catalog.

Annual electricity generation by state

Net summer capacity by state

Shapefile with U.S. state boundaries

Attribution for electricity generation and capacity data: U.S. Energy Information Administration (Aug 2024). Available from: https://www.eia.gov/electricity/data/state/. In the public domain.

electricity_rates_by_state_merged.geojson

Commercial electricity prices are obtained from the Electricity database maintained by the United States Energy Information Administration.

Electricity rate by state

Attribution: U.S. Energy Information Administration (Aug 2024). Available from: https://www.eia.gov/electricity/data.php. In the public domain.

demand_charges_merged.geojson

demand_charges_by_state.geojson

Maximum historical demand charges for each state and zip code are derived from a dataset compiled by the National Renewable Energy Laboratory in this this Data Catalog.

Historical demand charge dataset

The original dataset is compiled by the National Renewable Energy Laboratory (NREL), the U.S. Department of Energy (DOE), and the Alliance for Sustainable Energy, LLC ('Alliance').

Attribution: McLaren, Joyce, Pieter Gagnon, Daniel Zimny-Schmitt, Michael DeMinco, and Eric Wilson. 2017. 'Maximum demand charge rates for commercial and industrial electricity tariffs in the United States.' NREL Data Catalog. Golden, CO: National Renewable Energy Laboratory. Last updated: July 24, 2024. DOI: 10.7799/1392982.

eastcoast.geojson

midwest.geojson

la_i710.geojson

h2la.geojson

bayarea.geojson

saltlake.geojson

northeast.geojson

Highway corridors and regions targeted for heavy duty vehicle infrastructure projects are derived from a public announcement on February 15, 2023 by the United States Department of Energy.

The shapefile with Bay area boundaries is obtained from this Berkeley Library dataset.

The shapefile with Utah county boundaries is obtained from this dataset from the Utah Geospatial Resource Center.

Shapefile for Bay Area country boundaries

Shapefile for counties in Utah

Attribution for public announcement: United States Department of Energy. Biden-Harris Administration Announces Funding for Zero-Emission Medium- and Heavy-Duty Vehicle Corridors, Expansion of EV Charging in Underserved Communities (2023). Available from https://www.energy.gov/articles/biden-harris-administration-announces-funding-zero-emission-medium-and-heavy-duty-vehicle.

Attribution for Bay area boundaries: San Francisco (Calif.). Department Of Telecommunications and Information Services. Bay Area Counties. 2006. In the public domain.

Attribution for Utah boundaries: Utah Geospatial Resource Center & Lieutenant Governor's Office. Utah County Boundaries (2023). Available from https://gis.utah.gov/products/sgid/boundaries/county/.

License for Utah boundaries: Creative Commons 4.0 International License.

incentives_and_regulations/*.geojson

State-level incentives and regulations targeting heavy duty vehicles are collected from the State Laws and Incentives database maintained by the United States Department of Energy's Alternative Fuels Data Center.

Data was collected manually from the State Laws and Incentives database.

Attribution: U.S. Department of Energy, Energy Efficiency and Renewable Energy, Alternative Fuels Data Center. State Laws and Incentives. Accessed on Aug 5, 2024 from: https://afdc.energy.gov/laws/state. In the public domain.

These data and software code ("Data") are provided by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC ("Alliance"), for the U.S. Department of Energy ("DOE"), and may be used for any purpose whatsoever.

costs_and_emissions/*.geojson

diesel_price_by_state.geojson

trucking_energy_demand.geojson

Lifecycle costs and emissions of electric and diesel trucking are evaluated by adapting the model developed by Moreno Sader et al., and calibrated to the Run on Less dataset for the Tesla Semi collected from the 2023 PepsiCo Semi pilot by the North American Council for Freight Efficiency.

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