50 datasets found
  1. g

    United States Shapefile

    • geopostcodes.com
    shp
    Updated May 15, 2025
    + more versions
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    GeoPostcodes (2025). United States Shapefile [Dataset]. https://www.geopostcodes.com/country/united-states-shapefile
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    shpAvailable download formats
    Dataset updated
    May 15, 2025
    Dataset authored and provided by
    GeoPostcodes
    Area covered
    United States
    Description

    Download high-quality, up-to-date United States shapefile boundaries (SHP, projection system SRID 4326). Our United States Shapefile Database offers comprehensive boundary data for spatial analysis, including administrative areas and geographic boundaries. This dataset contains accurate and up-to-date information on all administrative divisions, zip codes, cities, and geographic boundaries, making it an invaluable resource for various applications such as geographic analysis, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including Shapefile, GeoJSON, KML, ASC, DAT, CSV, and GML, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.

  2. d

    TIGER/Line Shapefile, 2019, nation, U.S., Primary Roads National Shapefile

    • catalog.data.gov
    Updated Jan 15, 2021
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    (2021). TIGER/Line Shapefile, 2019, nation, U.S., Primary Roads National Shapefile [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2019-nation-u-s-primary-roads-national-shapefile
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    Dataset updated
    Jan 15, 2021
    Area covered
    United States
    Description

    The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Primary roads are generally divided, limited-access highways within the interstate highway system or under State management, and are distinguished by the presence of interchanges. These highways are accessible by ramps and may include some toll highways. The MAF/TIGER Feature Classification Code (MTFCC) is S1100 for primary roads.

  3. Large Scale International Boundaries

    • catalog.data.gov
    • geodata.state.gov
    • +1more
    Updated Jul 4, 2025
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    U.S. Department of State (Point of Contact) (2025). Large Scale International Boundaries [Dataset]. https://catalog.data.gov/dataset/large-scale-international-boundaries
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    Dataset updated
    Jul 4, 2025
    Dataset provided by
    United States Department of Statehttp://state.gov/
    Description

    Overview The Office of the Geographer and Global Issues at the U.S. Department of State produces the Large Scale International Boundaries (LSIB) dataset. The current edition is version 11.4 (published 24 February 2025). The 11.4 release contains updated boundary lines and data refinements designed to extend the functionality of the dataset. These data and generalized derivatives are the only international boundary lines approved for U.S. Government use. The contents of this dataset reflect U.S. Government policy on international boundary alignment, political recognition, and dispute status. They do not necessarily reflect de facto limits of control. National Geospatial Data Asset This dataset is a National Geospatial Data Asset (NGDAID 194) managed by the Department of State. It is a part of the International Boundaries Theme created by the Federal Geographic Data Committee. Dataset Source Details Sources for these data include treaties, relevant maps, and data from boundary commissions, as well as national mapping agencies. Where available and applicable, the dataset incorporates information from courts, tribunals, and international arbitrations. The research and recovery process includes analysis of satellite imagery and elevation data. Due to the limitations of source materials and processing techniques, most lines are within 100 meters of their true position on the ground. Cartographic Visualization The LSIB is a geospatial dataset that, when used for cartographic purposes, requires additional styling. The LSIB download package contains example style files for commonly used software applications. The attribute table also contains embedded information to guide the cartographic representation. Additional discussion of these considerations can be found in the Use of Core Attributes in Cartographic Visualization section below. Additional cartographic information pertaining to the depiction and description of international boundaries or areas of special sovereignty can be found in Guidance Bulletins published by the Office of the Geographer and Global Issues: https://data.geodata.state.gov/guidance/index.html Contact Direct inquiries to internationalboundaries@state.gov. Direct download: https://data.geodata.state.gov/LSIB.zip Attribute Structure The dataset uses the following attributes divided into two categories: ATTRIBUTE NAME | ATTRIBUTE STATUS CC1 | Core CC1_GENC3 | Extension CC1_WPID | Extension COUNTRY1 | Core CC2 | Core CC2_GENC3 | Extension CC2_WPID | Extension COUNTRY2 | Core RANK | Core LABEL | Core STATUS | Core NOTES | Core LSIB_ID | Extension ANTECIDS | Extension PREVIDS | Extension PARENTID | Extension PARENTSEG | Extension These attributes have external data sources that update separately from the LSIB: ATTRIBUTE NAME | ATTRIBUTE STATUS CC1 | GENC CC1_GENC3 | GENC CC1_WPID | World Polygons COUNTRY1 | DoS Lists CC2 | GENC CC2_GENC3 | GENC CC2_WPID | World Polygons COUNTRY2 | DoS Lists LSIB_ID | BASE ANTECIDS | BASE PREVIDS | BASE PARENTID | BASE PARENTSEG | BASE The core attributes listed above describe the boundary lines contained within the LSIB dataset. Removal of core attributes from the dataset will change the meaning of the lines. An attribute status of “Extension” represents a field containing data interoperability information. Other attributes not listed above include “FID”, “Shape_length” and “Shape.” These are components of the shapefile format and do not form an intrinsic part of the LSIB. Core Attributes The eight core attributes listed above contain unique information which, when combined with the line geometry, comprise the LSIB dataset. These Core Attributes are further divided into Country Code and Name Fields and Descriptive Fields. County Code and Country Name Fields “CC1” and “CC2” fields are machine readable fields that contain political entity codes. These are two-character codes derived from the Geopolitical Entities, Names, and Codes Standard (GENC), Edition 3 Update 18. “CC1_GENC3” and “CC2_GENC3” fields contain the corresponding three-character GENC codes and are extension attributes discussed below. The codes “Q2” or “QX2” denote a line in the LSIB representing a boundary associated with areas not contained within the GENC standard. The “COUNTRY1” and “COUNTRY2” fields contain the names of corresponding political entities. These fields contain names approved by the U.S. Board on Geographic Names (BGN) as incorporated in the ‘"Independent States in the World" and "Dependencies and Areas of Special Sovereignty" lists maintained by the Department of State. To ensure maximum compatibility, names are presented without diacritics and certain names are rendered using common cartographic abbreviations. Names for lines associated with the code "Q2" are descriptive and not necessarily BGN-approved. Names rendered in all CAPITAL LETTERS denote independent states. Names rendered in normal text represent dependencies, areas of special sovereignty, or are otherwise presented for the convenience of the user. Descriptive Fields The following text fields are a part of the core attributes of the LSIB dataset and do not update from external sources. They provide additional information about each of the lines and are as follows: ATTRIBUTE NAME | CONTAINS NULLS RANK | No STATUS | No LABEL | Yes NOTES | Yes Neither the "RANK" nor "STATUS" fields contain null values; the "LABEL" and "NOTES" fields do. The "RANK" field is a numeric expression of the "STATUS" field. Combined with the line geometry, these fields encode the views of the United States Government on the political status of the boundary line. ATTRIBUTE NAME | | VALUE | RANK | 1 | 2 | 3 STATUS | International Boundary | Other Line of International Separation | Special Line A value of “1” in the “RANK” field corresponds to an "International Boundary" value in the “STATUS” field. Values of ”2” and “3” correspond to “Other Line of International Separation” and “Special Line,” respectively. The “LABEL” field contains required text to describe the line segment on all finished cartographic products, including but not limited to print and interactive maps. The “NOTES” field contains an explanation of special circumstances modifying the lines. This information can pertain to the origins of the boundary lines, limitations regarding the purpose of the lines, or the original source of the line. Use of Core Attributes in Cartographic Visualization Several of the Core Attributes provide information required for the proper cartographic representation of the LSIB dataset. The cartographic usage of the LSIB requires a visual differentiation between the three categories of boundary lines. Specifically, this differentiation must be between: International Boundaries (Rank 1); Other Lines of International Separation (Rank 2); and Special Lines (Rank 3). Rank 1 lines must be the most visually prominent. Rank 2 lines must be less visually prominent than Rank 1 lines. Rank 3 lines must be shown in a manner visually subordinate to Ranks 1 and 2. Where scale permits, Rank 2 and 3 lines must be labeled in accordance with the “Label” field. Data marked with a Rank 2 or 3 designation does not necessarily correspond to a disputed boundary. Please consult the style files in the download package for examples of this depiction. The requirement to incorporate the contents of the "LABEL" field on cartographic products is scale dependent. If a label is legible at the scale of a given static product, a proper use of this dataset would encourage the application of that label. Using the contents of the "COUNTRY1" and "COUNTRY2" fields in the generation of a line segment label is not required. The "STATUS" field contains the preferred description for the three LSIB line types when they are incorporated into a map legend but is otherwise not to be used for labeling. Use of the “CC1,” “CC1_GENC3,” “CC2,” “CC2_GENC3,” “RANK,” or “NOTES” fields for cartographic labeling purposes is prohibited. Extension Attributes Certain elements of the attributes within the LSIB dataset extend data functionality to make the data more interoperable or to provide clearer linkages to other datasets. The fields “CC1_GENC3” and “CC2_GENC” contain the corresponding three-character GENC code to the “CC1” and “CC2” attributes. The code “QX2” is the three-character counterpart of the code “Q2,” which denotes a line in the LSIB representing a boundary associated with a geographic area not contained within the GENC standard. To allow for linkage between individual lines in the LSIB and World Polygons dataset, the “CC1_WPID” and “CC2_WPID” fields contain a Universally Unique Identifier (UUID), version 4, which provides a stable description of each geographic entity in a boundary pair relationship. Each UUID corresponds to a geographic entity listed in the World Polygons dataset. These fields allow for linkage between individual lines in the LSIB and the overall World Polygons dataset. Five additional fields in the LSIB expand on the UUID concept and either describe features that have changed across space and time or indicate relationships between previous versions of the feature. The “LSIB_ID” attribute is a UUID value that defines a specific instance of a feature. Any change to the feature in a lineset requires a new “LSIB_ID.” The “ANTECIDS,” or antecedent ID, is a UUID that references line geometries from which a given line is descended in time. It is used when there is a feature that is entirely new, not when there is a new version of a previous feature. This is generally used to reference countries that have dissolved. The “PREVIDS,” or Previous ID, is a UUID field that contains old versions of a line. This is an additive field, that houses all Previous IDs. A new version of a feature is defined by any change to the

  4. U.S. EPAs Geospatial Data Access Project

    • data.cnra.ca.gov
    • data.wu.ac.at
    Updated Jul 18, 2020
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    United States Environmental Protection Agency (2020). U.S. EPAs Geospatial Data Access Project [Dataset]. https://data.cnra.ca.gov/dataset/us-epas-geospatial-data-access-project
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    Dataset updated
    Jul 18, 2020
    Dataset authored and provided by
    United States Environmental Protection Agencyhttp://www.epa.gov/
    Description

    To improve public health and the environment, the United States Environmental Protection Agency (EPA) collects information about facilities, sites, or places subject to environmental regulation or of environmental interest. Through the Geospatial Data Download Service, the public is now able to download the EPA Geodata Shapefile, Feature Class or extensible markup language (XML) file containing facility and site information from EPA's national program systems. The files are Internet accessible from the Envirofacts Web site (https://www3.epa.gov/enviro/). The data may be used with geospatial mapping applications. (Note: The files omit facilities without latitude/longitude coordinates.) The EPA Geospatial Data contains the name, location (latitude/longitude), and EPA program information about specific facilities and sites. In addition, the files contain a Uniform Resource Locator (URL), which allows mapping applications to present an option to users to access additional EPA data resources on a specific facility or site.

  5. TIGER/Line Shapefile, 2023, Nation, U.S., International Boundaries...

    • catalog.data.gov
    Updated Dec 15, 2023
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geospatial Products Branch (Point of Contact) (2023). TIGER/Line Shapefile, 2023, Nation, U.S., International Boundaries (national) [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2023-nation-u-s-international-boundaries-national
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    Dataset updated
    Dec 15, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    United States
    Description

    The international boundary data featured in this shapefile consists of the boundary between the United States and Canada and the United States and Mexico. Each country's section is administered independently. The United States and Canada border data was provided by the International Boundary Commission, United States and Canada (IBC). The International Boundary and Water Commission (IBWC) provided the United States and Mexico section of the border data. Geospatial data files provided individually by the IBC and IBWC were used to re-align the Census Bureau's MAF/TIGER System data for the agency's representation of the international boundaries of United States with Canada and Mexico. The Census Bureau's MAF/TIGER System and the IBWC source file data for the portion of the United States and Mexico border featured a gap between Cameron County, Texas and the three-mile limit in the Gulf of Mexico. The National Oceanic and Atmospheric Administration Coast Survey Office's representation of the United States and Mexico boundary used to fill this gap.

  6. H

    United States Aquifer Database

    • hydroshare.org
    • beta.hydroshare.org
    • +1more
    zip
    Updated Apr 19, 2022
    + more versions
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    Merhawi GebreEgziabher; Scott Jasechko; Debra Perrone (2022). United States Aquifer Database [Dataset]. https://www.hydroshare.org/resource/d2260651b51044d0b5cb2d293d21af08
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    zip(3.7 MB)Available download formats
    Dataset updated
    Apr 19, 2022
    Dataset provided by
    HydroShare
    Authors
    Merhawi GebreEgziabher; Scott Jasechko; Debra Perrone
    License

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

    Area covered
    Description

    Here we present a geospatial dataset representing local- and regional-scale aquifer system boundaries, defined on the basis of an extensive literature review and published in GebreEgziabher et al. (2022). Nature Communications, 13, 2129, https://www.nature.com/articles/s41467-022-29678-7

    The database contains 440 polygons, each representing one study area analyzed in GebreEgziabher et al. (2022). The attribute table associated with the shapefile has two fields (column headings): (1) aquifer system title (Ocala Uplift sub-area of the broader Floridan Aquifer System), and (2) broader aquifer system title (e.g., the Floridan Aquifer System).

  7. o

    US State Boundaries

    • public.opendatasoft.com
    • data.wu.ac.at
    csv, excel, geojson +1
    Updated Jun 27, 2017
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    (2017). US State Boundaries [Dataset]. https://public.opendatasoft.com/explore/dataset/us-state-boundaries/
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    json, csv, geojson, excelAvailable download formats
    Dataset updated
    Jun 27, 2017
    License

    https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain

    Area covered
    United States
    Description

    This dataset represents States and equivalent entities, which are the primary governmental divisions of the United States. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. In addition to the fifty States, the Census Bureau treats the District of Columbia, Puerto Rico, and each of the Island Areas (American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the U.S. Virgin Islands) as the statistical equivalents of States for the purpose of data presentation.

  8. U

    A national dataset of rasterized building footprints for the U.S.

    • data.usgs.gov
    • catalog.data.gov
    Updated Feb 28, 2020
    + more versions
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    Mehdi Heris; Nathan Foks; Kenneth Bagstad; Austin Troy (2020). A national dataset of rasterized building footprints for the U.S. [Dataset]. http://doi.org/10.5066/P9J2Y1WG
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    Dataset updated
    Feb 28, 2020
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Mehdi Heris; Nathan Foks; Kenneth Bagstad; Austin Troy
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Time period covered
    2020
    Area covered
    United States
    Description

    The Bing Maps team at Microsoft released a U.S.-wide vector building dataset in 2018, which includes over 125 million building footprints for all 50 states in GeoJSON format. This dataset is extracted from aerial images using deep learning object classification methods. Large-extent modelling (e.g., urban morphological analysis or ecosystem assessment models) or accuracy assessment with vector layers is highly challenging in practice. Although vector layers provide accurate geometries, their use in large-extent geospatial analysis comes at a high computational cost. We used High Performance Computing (HPC) to develop an algorithm that calculates six summary values for each cell in a raster representation of each U.S. state: (1) total footprint coverage, (2) number of unique buildings intersecting each cell, (3) number of building centroids falling inside each cell, and area of the (4) average, (5) smallest, and (6) largest area of buildings that intersect each cell. These values a ...

  9. 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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    Borrero, Micah (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
    Borrero, Micah
    Bashir, Noman
    MacDonell, Danika
    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

  10. K

    US Cities and Towns (Local)

    • koordinates.com
    csv, dwg, geodatabase +6
    + more versions
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    US Department of Agriculture (USDA), US Cities and Towns (Local) [Dataset]. https://koordinates.com/layer/12229-us-cities-and-towns-local/
    Explore at:
    geopackage / sqlite, kml, mapinfo tab, pdf, dwg, geodatabase, csv, shapefile, mapinfo mifAvailable download formats
    Dataset authored and provided by
    US Department of Agriculture (USDA)
    Area covered
    United States,
    Description

    Geospatial data about US Cities and Towns (Local). Export to CAD, GIS, PDF, CSV and access via API.

  11. d

    Federal Communications Commission (FCC) Geospatial Data, United States.

    • datadiscoverystudio.org
    • data.wu.ac.at
    htm
    Updated Apr 9, 2015
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    (2015). Federal Communications Commission (FCC) Geospatial Data, United States. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/59734f3475214d7a8684054fbfca562f/html
    Explore at:
    htmAvailable download formats
    Dataset updated
    Apr 9, 2015
    Description

    description: Various telecommunication datasets such as cellphone towers and service areas, land mobile station locations, AM, FM, and TV communication, extracted from the FCC Licensing Database, can be individually downloaded from the FCC GIS data site. Addiitonally, a full dataset download of all GIS files is packaged with an ArcExplorer(R) viewing capability for users who do not have full GIS capability.; abstract: Various telecommunication datasets such as cellphone towers and service areas, land mobile station locations, AM, FM, and TV communication, extracted from the FCC Licensing Database, can be individually downloaded from the FCC GIS data site. Addiitonally, a full dataset download of all GIS files is packaged with an ArcExplorer(R) viewing capability for users who do not have full GIS capability.

  12. U

    Watershed Boundary Dataset (WBD) - USGS National Map Downloadable Data...

    • data.usgs.gov
    • catalog.data.gov
    Updated Jan 3, 2025
    + more versions
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    U.S. Geological Survey, National Geospatial Technical Operations Center (2025). Watershed Boundary Dataset (WBD) - USGS National Map Downloadable Data Collection [Dataset]. https://data.usgs.gov/datacatalog/data/USGS:0101bc32-916e-481d-8654-db7f8509fd0c
    Explore at:
    Dataset updated
    Jan 3, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey, National Geospatial Technical Operations Center
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    The Watershed Boundary Dataset (WBD) is a comprehensive aggregated collection of hydrologic unit data consistent with the national criteria for delineation and resolution. It defines the areal extent of surface water drainage to a point except in coastal or lake front areas where there could be multiple outlets as stated by the "Federal Standards and Procedures for the National Watershed Boundary Dataset (WBD)" "Standard" (https://pubs.usgs.gov/tm/11/a3/). Watershed boundaries are determined solely upon science-based hydrologic principles, not favoring any administrative boundaries or special projects, nor particular program or agency. This dataset represents the hydrologic unit boundaries to the 12-digit for the entire United States. Some areas may also include additional subdivisions representing the 14- and 16-digit hydrologic unit (HU). At a minimum, the HUs are delineated at 1:24,000-scale in the conterminous United States, 1:25,000-scale in Hawaii, Pacific basin and the Cari ...

  13. d

    2019 Cartographic Boundary Shapefile, Current Census Tract for United...

    • catalog.data.gov
    Updated Nov 12, 2020
    + more versions
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    (2020). 2019 Cartographic Boundary Shapefile, Current Census Tract for United States, 1:500,000 [Dataset]. https://catalog.data.gov/dataset/2019-cartographic-boundary-shapefile-current-census-tract-for-united-states-1-500000
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    Dataset updated
    Nov 12, 2020
    Area covered
    United States
    Description

    The 2019 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some states and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

  14. 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(136046), shp(2597712), shp(10153125)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.

  15. K

    US Communities

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Sep 3, 2018
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    US Federal Emergency Management Agency (FEMA) (2018). US Communities [Dataset]. https://koordinates.com/layer/25566-us-communities/
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    mapinfo mif, csv, mapinfo tab, pdf, shapefile, dwg, kml, geopackage / sqlite, geodatabaseAvailable download formats
    Dataset updated
    Sep 3, 2018
    Dataset authored and provided by
    US Federal Emergency Management Agency (FEMA)
    Area covered
    Description

    The Census data utilized for developing the Community Layer used 2010 TIGER/Line shapefile datasets (TIGER = Topologically Integrated Geographic Encoding and Referencing). TIGER/Line shapefiles are available for free download from the US Census Bureau and include various legal and statistical geographic areas for which the Census tabulates data. The shapefiles are designed to be used in a GIS environment, with the ability to directly link the geographic areas to Census data via a unique GEOID number.The following TIGER/Line datasets should be used: - Counties and Equivalent Entities –primary legal divisions within each state (counties, parishes, etc)- County Subdivisions –includes both legal areas (Minor Civil Divisions or MCDs) and various statistical areas- Places –includes both legal areas (Incorporated Places) and statistical areas (Census Designated Places or CDPs)- Blocks –the smallest geographical area for which Census population counts are recorded; blocks never cross boundaries of any entity for which the Census Bureau tabulates data, including counties, county subdivisions, places, and American Indian, Alaska Native, and Native Hawaiian (AIANNH) areas- American Indian, Alaska Native, and Native Hawaiian (AIANNH) AreasExtracting and Formatting CIS DataA key component of the community layer is the ability to link CIS information spatially. Data from CIS cannot directly be joined with Census data. The two datasets have community name discrepancies which impede an exact match. Therefore, CIS data needs to be formatted to match Census community names. A custom report can be obtained from CIS to include a CID number, Community Name, County, State, Community Status, and Tribal status for all CIS records. Make sure all CID numbers are six digits and you follow the CIS community naming convention outlined in Table 4.2.1.1 in the Community Layer Update Technical Guide 20131206. Converting the CIS name“ADDISON, VILLAGE OF” to “ADDISON TOWN”involves removing unneeded spaces, comma, and preposition to make the join successful to the Census data. Using a comprehensive report at a national level gains efficiencies as bulk edits can be made. Data for each state should be extracted as needed by separating the CIS data into each type of community corresponding to the Census geography layers used, and a new JoinID column (e.g. ADDISON TOWN) can be created for each dataset allowing the CIS data to be joined to the Census data.

  16. n

    North Carolina State and County Boundary Polygons

    • nconemap.gov
    • hub.arcgis.com
    • +1more
    Updated Jun 11, 2020
    + more versions
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    State of North Carolina - Emergency Management (2020). North Carolina State and County Boundary Polygons [Dataset]. https://www.nconemap.gov/datasets/NCEM-GIS::north-carolina-state-and-county-boundary-polygons
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    Dataset updated
    Jun 11, 2020
    Dataset authored and provided by
    State of North Carolina - Emergency Management
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    The North Carolina State and County Boundary vector polygon data provides location information for North Carolina State and County Boundary lines derived from the best available survey and/or Geographic Information System (GIS) data. Sources for information are the North Carolina Geodetic Survey (NCGS), NC Department of Transportation (NCDOT), United States Geological Survey (USGS), and field surveys conducted by licensed surveyors in North Carolina and neighboring states that have been approved and recorded in their respective counties. North Carolina Geodetic Survey assists counties on a cooperative basis (NC General Statute 153A-18) in defining and monumenting the location of uncertain or disputed boundaries as established by law. Some counties have completed boundary surveys for at least a portion of their county boundary. However, the majority of county boundaries have not been surveyed and are represented by the best currently available data from GIS sources, including NCDOT county maps (which originally came from the USGS) and updated county parcel maps.

  17. M

    Federal Communications Commission (FCC) Geospatial Data, United States

    • gisdata.mn.gov
    • geo.btaa.org
    • +1more
    fgdb, gpkg, html +2
    Updated Nov 22, 2024
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    Geospatial Information Office (2024). Federal Communications Commission (FCC) Geospatial Data, United States [Dataset]. https://gisdata.mn.gov/dataset/util-fcc
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    shp, fgdb, html, gpkg, jpegAvailable download formats
    Dataset updated
    Nov 22, 2024
    Dataset provided by
    Geospatial Information Office
    Area covered
    United States
    Description

    Various telecommunication datasets such as cellphone towers and service areas, land mobile station locations, AM, FM, and TV communication can be downloaded on an FCC page. Additionally, data files can be individually downloaded from the FCC Universal Licensing System data site. This data resource is intended to guide users toward the authoritative data source and to demonstrate at least one translation of that data into a spatial format.

    The metadata for this translated dataset is here:

    Antenna Structure Registration: antenna_structure_registration_mn.html

    In addition, the Department of Homeland Security's Homeland Infrastructure Foundation - Level Data (HIFLD) program has an "Open Data" site, which includes a nationwide dataset on Cellular Towers derived from the FCC Universal Licensing System Database: https://hifld-geoplatform.opendata.arcgis.com/datasets/cellular-towers

  18. K

    US Major Cities

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Aug 30, 2018
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    US Department of Agriculture (USDA) (2018). US Major Cities [Dataset]. https://koordinates.com/layer/11897-us-major-cities/
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    csv, mapinfo tab, geodatabase, pdf, geopackage / sqlite, mapinfo mif, kml, shapefile, dwgAvailable download formats
    Dataset updated
    Aug 30, 2018
    Dataset authored and provided by
    US Department of Agriculture (USDA)
    Area covered
    Description

    This layer is a component of 2007_NAIP_COVERAGE_3.mxd.

  19. BOEM BSEE Marine Cadastre Layers National Scale - OCS Oil & Gas Pipelines

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Nov 16, 2016
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    US Bureau of Ocean Energy Management (BOEM) (2016). BOEM BSEE Marine Cadastre Layers National Scale - OCS Oil & Gas Pipelines [Dataset]. https://koordinates.com/layer/15435-boem-bsee-marine-cadastre-layers-national-scale-ocs-oil-gas-pipelines/
    Explore at:
    dwg, kml, mapinfo tab, geopackage / sqlite, mapinfo mif, geodatabase, shapefile, csv, pdfAvailable download formats
    Dataset updated
    Nov 16, 2016
    Dataset provided by
    Bureau of Ocean Energy Managementhttp://www.boem.gov/
    Federal government of the United Stateshttp://www.usa.gov/
    Authors
    US Bureau of Ocean Energy Management (BOEM)
    Area covered
    Description

    This dataset is a compilation of available oil and gas pipeline data and is maintained by BSEE. Pipelines are used to transport and monitor oil and/or gas from wells within the outer continental shelf (OCS) to resource collection locations. Currently, pipelines managed by BSEE are found in Gulf of Mexico and southern California waters.

    © MarineCadastre.gov This layer is a component of BOEMRE Layers.

    This Map Service contains many of the primary data types created by both the Bureau of Ocean Energy Management (BOEM) and the Bureau of Safety and Environmental Enforcement (BSEE) within the Department of Interior (DOI) for the purpose of managing offshore federal real estate leases for oil, gas, minerals, renewable energy, sand and gravel. These data layers are being made available as REST mapping services for the purpose of web viewing and map overlay viewing in GIS systems. Due to re-projection issues which occur when converting multiple UTM zone data to a single national or regional projected space, and line type changes that occur when converting from UTM to geographic projections, these data layers should not be used for official or legal purposes. Only the original data found within BOEM/BSEE’s official internal database, federal register notices or official paper or pdf map products may be considered as the official information or mapping products used by BOEM or BSEE. A variety of data layers are represented within this REST service are described further below. These and other cadastre information the BOEM and BSEE produces are generated in accordance with 30 Code of Federal Regulations (CFR) 256.8 to support Federal land ownership and mineral resource management.

    For more information – Contact: Branch Chief, Mapping and Boundary Branch, BOEM, 381 Elden Street, Herndon, VA 20170. Telephone (703) 787-1312; Email: mapping.boundary.branch@boem.gov

    The REST services for National Level Data can be found here: http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE/MMC_Layers/MapServer

    REST services for regional level data can be found by clicking on the region of interest from the following URL: http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE

    Individual Regional Data or in depth metadata for download can be obtained in ESRI Shape file format by clicking on the region of interest from the following URL: http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx

    Currently the following layers are available from this REST location:

    OCS Drilling Platforms -Locations of structures at and beneath the water surface used for the purpose of exploration and resource extraction. Only platforms in federal Outer Continental Shelf (OCS) waters are included. A database of platforms and rigs is maintained by BSEE.

    OCS Oil and Natural Gas Wells -Existing wells drilled for exploration or extraction of oil and/or gas products. Additional information includes the lease number, well name, spud date, the well class, surface area/block number, and statistics on well status summary. Only wells found in federal Outer Continental Shelf (OCS) waters are included. Wells information is updated daily. Additional files are available on well completions and well tests. A database of wells is maintained by BSEE.

    OCS Oil & Gas Pipelines -This dataset is a compilation of available oil and gas pipeline data and is maintained by BSEE. Pipelines are used to transport and monitor oil and/or gas from wells within the outer continental shelf (OCS) to resource collection locations. Currently, pipelines managed by BSEE are found in Gulf of Mexico and southern California waters.

    Unofficial State Lateral Boundaries - The approximate location of the boundary between two states seaward of the coastline and terminating at the Submerged Lands Act Boundary. Because most State boundary locations have not been officially described beyond the coast, are disputed between states or in some cases the coastal land boundary description is not available, these lines serve as an approximation that was used to determine a starting point for creation of BOEM’s OCS Administrative Boundaries. GIS files are not available for this layer due to its unofficial status.

    BOEM OCS Administrative Boundaries - Outer Continental Shelf (OCS) Administrative Boundaries Extending from the Submerged Lands Act Boundary seaward to the Limit of the United States OCS (The U.S. 200 nautical mile Limit, or other marine boundary)For additional details please see the January 3, 2006 Federal Register Notice.

    BOEM Limit of OCSLA ‘8(g)’ zone - The Outer Continental Shelf Lands Act '8(g) Zone' lies between the Submerged Lands Act (SLA) boundary line and a line projected 3 nautical miles seaward of the SLA boundary line. Within this zone, oil and gas revenues are shared with the coastal state(s). The official version of the ‘8(g)’ Boundaries can only be found on the BOEM Official Protraction Diagrams (OPDs) or Supplemental Official Protraction described below.

    Submerged Lands Act Boundary - The SLA boundary defines the seaward limit of a state's submerged lands and the landward boundary of federally managed OCS lands. The official version of the SLA Boundaries can only be found on the BOEM Official Protraction Diagrams (OPDs) or Supplemental Official Protraction Diagrams described below.

    Atlantic Wildlife Survey Tracklines(2005-2012) - These data depict tracklines of wildlife surveys conducted in the Mid-Atlantic region since 2005. The tracklines are comprised of aerial and shipboard surveys. These data are intended to be used as a working compendium to inform the diverse number of groups that conduct surveys in the Mid-Atlantic region.The tracklines as depicted in this dataset have been derived from source tracklines and transects. The tracklines have been simplified (modified from their original form) due to the large size of the Mid-Atlantic region and the limited ability to map all areas simultaneously.The tracklines are to be used as a general reference and should not be considered definitive or authoritative. This data can be downloaded from http://www.boem.gov/uploadedFiles/BOEM/Renewable_Energy_Program/Mapping_and_Data/ATL_WILDLIFE_SURVEYS.zip

    BOEM OCS Protraction Diagrams & Leasing Maps - This data set contains a national scale spatial footprint of the outer boundaries of the Bureau of Ocean Energy Management’s (BOEM’s) Official Protraction Diagrams (OPDs) and Leasing Maps (LMs). It is updated as needed. OPDs and LMs are mapping products produced and used by the BOEM to delimit areas available for potential offshore mineral leases, determine the State/Federal offshore boundaries, and determine the limits of revenue sharing and other boundaries to be considered for leasing offshore waters. This dataset shows only the outline of the maps that are available from BOEM.Only the most recently published paper or pdf versions of the OPDs or LMs should be used for official or legal purposes. The pdf maps can be found by going to the following link and selecting the appropriate region of interest. http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx Both OPDs and LMs are further subdivided into individual Outer Continental Shelf(OCS) blocks which are available as a separate layer. Some OCS blocks that also contain other boundary information are known as Supplemental Official Block Diagrams (SOBDs.) Further information on the historic development of OPD's can be found in OCS Report MMS 99-0006: Boundary Development on the Outer Continental Shelf: http://www.boemre.gov/itd/pubs/1999/99-0006.PDF Also see the metadata for each of the individual GIS data layers available for download. The Official Protraction Diagrams (OPDs) and Supplemental Official Block Diagrams (SOBDs), serve as the legal definition for BOEM offshore boundary coordinates and area descriptions.

    BOEM OCS Lease Blocks - Outer Continental Shelf (OCS) lease blocks serve as the legal definition for BOEM offshore boundary coordinates used to define small geographic areas within an Official Protraction Diagram (OPD) for leasing and administrative purposes. OCS blocks relate back to individual Official Protraction Diagrams and are not uniquely numbered. Only the most recently published paper or pdf

  20. USA Airports

    • hub.arcgis.com
    • prep-response-portal.napsgfoundation.org
    • +4more
    Updated Dec 9, 2014
    + more versions
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    Esri (2014). USA Airports [Dataset]. https://hub.arcgis.com/maps/5d93352406744d658d9c1f43f12b560c
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    Dataset updated
    Dec 9, 2014
    Dataset authored and provided by
    Esrihttp://esri.com/
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    The Airports database is a geographic point database of aircraft landing facilities in the United States and U.S. Territories. Attribute data is provided on the physical and operational characteristics of the landing facility, current usage including enplanements and aircraft operations, congestion levels and usage categories. This geospatial data is derived from the FAA's National Airspace System Resource Aeronautical Data Product.

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GeoPostcodes (2025). United States Shapefile [Dataset]. https://www.geopostcodes.com/country/united-states-shapefile

United States Shapefile

United States Shapefile - Data Download

Explore at:
33 scholarly articles cite this dataset (View in Google Scholar)
shpAvailable download formats
Dataset updated
May 15, 2025
Dataset authored and provided by
GeoPostcodes
Area covered
United States
Description

Download high-quality, up-to-date United States shapefile boundaries (SHP, projection system SRID 4326). Our United States Shapefile Database offers comprehensive boundary data for spatial analysis, including administrative areas and geographic boundaries. This dataset contains accurate and up-to-date information on all administrative divisions, zip codes, cities, and geographic boundaries, making it an invaluable resource for various applications such as geographic analysis, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including Shapefile, GeoJSON, KML, ASC, DAT, CSV, and GML, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.

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