100+ datasets found
  1. 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.

  2. U

    USGS National Boundary Dataset (NBD) Downloadable Data Collection

    • data.usgs.gov
    • catalog.data.gov
    + more versions
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    U.S. Geological Survey, National Geospatial Technical Operations Center, USGS National Boundary Dataset (NBD) Downloadable Data Collection [Dataset]. https://data.usgs.gov/datacatalog/data/USGS:6dcde538-1684-48a0-a8d6-cb671ca0a43e
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    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 USGS Governmental Unit Boundaries dataset from The National Map (TNM) represents major civil areas for the Nation, including States or Territories, counties (or equivalents), Federal and Native American areas, congressional districts, minor civil divisions, incorporated places (such as cities and towns), and unincorporated places. Boundaries data are useful for understanding the extent of jurisdictional or administrative areas for a wide range of applications, including mapping or managing resources, and responding to natural disasters. Boundaries data also include extents of forest, grassland, park, wilderness, wildlife, and other reserve areas useful for recreational activities, such as hiking and backpacking. Boundaries data are acquired from a variety of government sources. The data represents the source data with minimal editing or review by USGS. Please refer to the feature-level metadata ...

  3. Geolocet | Administrative boundaries map data | Europe | Countries, Regions,...

    • datarade.ai
    Updated Nov 3, 2023
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    Geolocet (2023). Geolocet | Administrative boundaries map data | Europe | Countries, Regions, Provinces, Municipalities, and more | Fully customizable format [Dataset]. https://datarade.ai/data-products/geolocet-administrative-boundaries-map-data-europe-coun-geolocet
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    .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Nov 3, 2023
    Dataset provided by
    Authors
    Geolocet
    Area covered
    Germany, Belgium, Latvia, Estonia, Hungary, Finland, Bulgaria, Luxembourg, Italy, United Kingdom
    Description

    Geolocet's Administrative Boundaries Spatial Data serves as the gateway to visualizing geographic distributions and patterns with precision. The comprehensive dataset covers all European countries, encompassing the boundaries of each country, as well as its political and statistical divisions. Tailoring data purchases to exact needs is possible, allowing for the selection of individual levels of geography or bundling all levels for a country with a discount. The seamless integration of administrative boundaries onto digital maps transforms raw data into actionable insights.

    🌐 Coverage Across European Countries

    Geolocet's Administrative Boundaries Data offers coverage across all European countries, ensuring access to the most up-to-date and accurate geographic information. From national borders to the finest-grained administrative units, this data enables informed choices based on verified and official sources.

    🔍 Geographic Context for Strategic Decisions

    Understanding the geographical context is crucial for strategic decision-making. Geolocet's Administrative Boundaries Spatial Data empowers exploration of geo patterns, planning expansions, analysis of regional demographics, and optimization of operations with precision. Whether it is for establishing new business locations, efficient resource allocation, or policy impact analysis, this data provides the essential geographic context for success.

    🌍 Integration with Geolocet’s Demographic Data

    The integration of Geolocet's Administrative Boundaries Spatial Data with Geolocet's Demographic Data creates a synergy that enriches insights. The combination of administrative boundaries and demographic information offers a comprehensive understanding of regions and their unique characteristics. This integration enables tailoring of strategies, marketing campaigns, and resource allocation to specific areas with confidence.

    🌍 Integration with Geolocet’s POI Data

    Combining Geolocet's Administrative Boundaries Spatial Data with our POI (Points of Interest) Data unveils not only the administrative divisions but also insights into the local characteristics of these areas. Overlaying POI data on administrative boundaries reveals details about the number and types of businesses, services, and amenities within specific regions. Whether conducting market research, identifying prime locations for retail outlets, or analyzing the accessibility of essential services, this combined data empowers a holistic view of target areas.

    🔍 Customized Data Solutions with DaaS

    Geolocet's Data as a Service (DaaS) model offers flexibility tailored to specific needs. The transparent pricing model ensures cost-efficiency, allowing payment solely for the required data. Whether nationwide administrative boundary data or specific regional details are needed, Geolocet provides a solution to match individual objectives. Contact us today to explore how Geolocet's Administrative Boundaries Spatial Data can elevate decision-making processes and provide the essential geographic data for success.

  4. 2022 Cartographic Boundary File (SHP), United States, 1:20,000,000

    • catalog.data.gov
    • gimi9.com
    • +1more
    Updated Dec 14, 2023
    + more versions
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch (Point of Contact) (2023). 2022 Cartographic Boundary File (SHP), United States, 1:20,000,000 [Dataset]. https://catalog.data.gov/dataset/2022-cartographic-boundary-file-shp-united-states-1-20000000
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    Dataset updated
    Dec 14, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    United States
    Description

    The 2022 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. This file depicts the shape of the United States clipped back to a generalized coastline. This nation layer covers the extent of the fifty states, 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) when scale appropriate.

  5. GADM Data for UK

    • kaggle.com
    zip
    Updated May 3, 2018
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    Gabriel Preda (2018). GADM Data for UK [Dataset]. https://www.kaggle.com/gpreda/gadm-data-for-uk
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    zip(4811802 bytes)Available download formats
    Dataset updated
    May 3, 2018
    Authors
    Gabriel Preda
    Area covered
    United Kingdom
    Description

    Context

    GADM provides maps and spatial data for all countries and their sub-divisions. This dataset contains the boundary data for United Kingdom (UK) at three resolutions:

    • United Kingdom level (GBM_adm0);
    • Countries level - England, Northern Ireland, Scotland, Wales - (GBM_adm1);
    • Administrative division level - i.e. counties level (GBM_adm2);

    Content

    The dataset contains boundary data for UK.

    Acknowledgements

    The data is published with the permission of GADM. The source is www.gadm.org. The conditions for using the data are specified in the license. Redistribution, or commercial use of these data, is not allowed without prior permission.

  6. Large Scale International Boundaries

    • geodata.state.gov
    • s.cnmilf.com
    • +1more
    Updated Feb 24, 2025
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    U.S. Department of State (2025). Large Scale International Boundaries [Dataset]. https://geodata.state.gov/geonetwork/srv/api/records/3bdb81a0-c1b9-439a-a0b1-85dac30c59b2
    Explore at:
    www:link-1.0-http--link, www:link-1.0-http--related, www:download:gpkg, www:download:zip, ogc:wms-1.3.0-http-get-capabilitiesAvailable download formats
    Dataset updated
    Feb 24, 2025
    Dataset provided by
    United States Department of Statehttp://state.gov/
    Authors
    U.S. Department of State
    Area covered
    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

  7. d

    Boundaries: US Zip Codes

    • catalog.data.gov
    • data.austintexas.gov
    • +1more
    Updated Oct 25, 2025
    + more versions
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    data.austintexas.gov (2025). Boundaries: US Zip Codes [Dataset]. https://catalog.data.gov/dataset/boundaries-us-zip-codes
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    Dataset updated
    Oct 25, 2025
    Dataset provided by
    data.austintexas.gov
    Description

    The City of Austin provides this zip code dataset for general use, designed to support a variety of research and analysis needs. Please note that while we facilitate access to this data, the dataset is owned and produced by the United States Postal Service (USPS). Users are encouraged to acknowledge USPS as the source when utilizing this dataset in their work. U.S. ZIP Code Areas (Five-Digit) represents five-digit ZIP Code areas used by the U.S. Postal Service to deliver mail more effectively. The first digit of a five-digit ZIP Code divides the United States into 10 large groups of states numbered from 0 in the Northeast to 9 in the far West. Within these areas, each state is divided into an average of 10 smaller geographical areas, identified by the second and third digits. These digits, in conjunction with the first digit, represent a sectional center facility or a mail processing facility area. The fourth and fifth digits identify a post office, station, branch or local delivery area. This product is for informational purposes and may not have been prepared for or be suitable for legal, engineering, or surveying purposes. It does not represent an on-the-ground survey and represents only the approximate relative location of property boundaries. This product has been produced by the City of Austin for the sole purpose of geographic reference. No warranty is made by the City of Austin regarding specific accuracy or completeness. City of Austin Open Data Terms of Use: https://datahub.austintexas.gov/stories/s/ranj-cccq

  8. Province of Ontario, Canada, Boundary WGS84

    • kaggle.com
    zip
    Updated Sep 27, 2024
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    Kyle Scissons (2024). Province of Ontario, Canada, Boundary WGS84 [Dataset]. https://www.kaggle.com/datasets/kylescissons/province-of-ontario-canada-boundary-wgs84/data
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    zip(45050226 bytes)Available download formats
    Dataset updated
    Sep 27, 2024
    Authors
    Kyle Scissons
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    Canada, Ontario
    Description

    Boundary Data For The Province of Ontario, Canada in EPSG:4236 (WGS84) Coordinate Reference System. A detailed multipolygon that represents the political boundaries of the Province of Ontario, Canada.

  9. ONS Geography Boundary Releases (2020) - Dataset - data.gov.uk

    • ckan.publishing.service.gov.uk
    Updated Sep 20, 2023
    + more versions
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    ckan.publishing.service.gov.uk (2023). ONS Geography Boundary Releases (2020) - Dataset - data.gov.uk [Dataset]. https://ckan.publishing.service.gov.uk/dataset/ons-geography-boundary-releases-2020
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    Dataset updated
    Sep 20, 2023
    Dataset provided by
    CKANhttps://ckan.org/
    Description

    A GeoPackage (see https://www.geopackage.org/) that contains the spatial data for all the boundaries that have changed over the last year.

  10. ACS Geographical Mobility Variables - Boundaries

    • hub.arcgis.com
    • city-albanyny-gis.hub.arcgis.com
    • +1more
    Updated Feb 26, 2019
    + more versions
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    Esri (2019). ACS Geographical Mobility Variables - Boundaries [Dataset]. https://hub.arcgis.com/maps/5fbaf18418ee4dde927318ea208a8aa9
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    Dataset updated
    Feb 26, 2019
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows residence one year ago for those 1 year and older. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percent of people one year and over who lived in a different state one year ago. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B07204 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  11. c

    Environmental Justice 2022 Set

    • geodata.ct.gov
    • data.ct.gov
    • +4more
    Updated May 23, 2023
    + more versions
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    Department of Energy & Environmental Protection (2023). Environmental Justice 2022 Set [Dataset]. https://geodata.ct.gov/maps/5ee667d1ac304fb3830f193a8179ffe0
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    Dataset updated
    May 23, 2023
    Dataset authored and provided by
    Department of Energy & Environmental Protection
    License

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

    Area covered
    Description

    Environmental Justice Block Groups 2022 was created from Connecticut block group boundary data located in the Census Bureau's 2020 TIGER/Line Shapefiles. The poverty data used to determine which block groups qualified as EJ communities (see CT State statute 22a-20a) was based on the Census Bureau's 2020 ACS 5-year estimate. This poverty data was joined with the block group boundaries in ArcPro. Block groups in which the percent of the population below 200% of the federal poverty level was greater than or equal to 30.0 were selected and the resulting selection was exported as a new shapefile. The block groups were then clipped so that only those block groups outside of distressed municipalities were displayed. Maintenance – This layer will be updated annually and will coincide with the annual distressed municipalities update (around August/September). The latest ACS 5-year estimate data should be used to update this layer. Environmental Justice Distressed Municipalities 2020 was created from Connecticut town boundary data located in the Census Bureau's 2020 TIGER/Line Shapefiles (County Subdivisions).

    From this shapefile, "select by attribute" was used to select the distressed municipalities by town name (note: the list of 2022 distressed municipalities was provided by the CT Department of Economic and Community Development). The selection was then exported a new shapefile. The “Union” tool was used to unite the new shapefile with tribal lands (American Indian Area Geography) boundary data from the 2020 TIGER/Line files. In the resulting layer, the tribal lands were deleted so only the distressed municipalities remained. Maintenance – This layer will be updated annually when the DECD produces its new list of distressed municipalities (around August/September).

    Note: A distressed municipality, as designated by the Connecticut Department of Economic and Community Development, includes municipalities that no longer meet the threshold requirements but are still in a 5-year grace period. (See definition at CGS Sec. 32-9p(b).) Fitting into that grace period, eight towns continue to be eligible for distressed municipality benefits because they dropped off the list within the last five years. Those are Enfield, Killingly, Naugatuck, Plymouth, New Haven, Preston, Stratford, and Voluntown.

  12. Census 2020: Blocks for San Francisco Clipped to the Shoreline

    • data.sfgov.org
    • catalog.data.gov
    Updated Jul 25, 2022
    + more versions
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    United States Census Bureau (2022). Census 2020: Blocks for San Francisco Clipped to the Shoreline [Dataset]. https://data.sfgov.org/Geographic-Locations-and-Boundaries/Census-2020-Blocks-for-San-Francisco-Clipped-to-th/e2st-aufe
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    kmz, kml, xlsx, application/geo+json, csv, xmlAvailable download formats
    Dataset updated
    Jul 25, 2022
    Dataset authored and provided by
    United States Census Bureauhttp://census.gov/
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Area covered
    San Francisco
    Description

    A. SUMMARY Census blocks with Pacific Ocean and San Francisco Bay water clipped out. Census blocks are the smallest geographic area for which the Bureau of the Census collects and tabulates decennial census data, are formed by streets, roads, railroads, streams and other bodies of water, other visible physical and cultural features, and the legal boundaries shown on Census Bureau maps. More information on the census tracts can be found here.

    B. HOW THE DATASET IS CREATED The boundaries are uploaded from TIGER/Line shapefiles provided by the U.S. Census Bureau and clipped using the water boundaries provided by the U.S. Census Bureau.

    C. UPDATE PROCESS This dataset is static. Changes to the census blocks are tracked in multiple datasets. See here for 2000 and 2010 census tract boundaries.

    D. HOW TO USE THIS DATASET This boundary file can be joined to other census datasets on GEOID. Column descriptions can be found on in the technical documentation included on the census.gov website

    E. RELATED DATASETS Census 2020: Census Tracts for San Francisco Analysis Neighborhoods - 2020 census tracts assigned to neighborhoods Census 2020: Blocks for San Francisco Census 2020: Blocks Groups for San Francisco Census 2020: Blocks Groups for San Francisco Clipped to SF Shoreline

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

    • catalog.data.gov
    • s.cnmilf.com
    Updated Aug 9, 2025
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geospatial Products Branch (Point of Contact) (2025). 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
    Aug 9, 2025
    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.

  14. School Attendance Boundary Survey 2015-2016

    • catalog.data.gov
    • s.cnmilf.com
    • +1more
    Updated Oct 21, 2024
    + more versions
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    National Center for Education Statistics (NCES) (2024). School Attendance Boundary Survey 2015-2016 [Dataset]. https://catalog.data.gov/dataset/school-attendance-boundary-survey-2015-2016-3b310
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    Dataset updated
    Oct 21, 2024
    Dataset provided by
    National Center for Education Statisticshttps://nces.ed.gov/
    Description

    This polygon files contains 2015-2016 school-year data delineating school attendance boundaries. These data were collected and processed as part of the School Attendance Boundary Survey (SABS) project which was funded by NCES to create geography delineating school attendance boundaries. Original source information that was used to create these boundary files were collected were collected over a web-based self-reporting system, through e-mail, and mailed paper maps. The web application provided instructions and assistance to users via a user guide, a frequently asked questions document, and instructional videos. Boundaries supplied outside of the online reporting system typically fell into one of six categories: a digital geographic file, such as a shapefile or KML file; digital image files, such as jpegs and pdfs; narrative descriptions; an interactive web map; Excel or pdf address lists; and paper maps. 2015 TIGER/line features (that consist of streets, hydrography, railways, etc.) were used to digitize school attendance boundaries and was the primary source of information used to digitize analog information. This practice works well as most school attendance boundaries align with streets, railways, water bodies and similar line features included in the 2015 TIGER/line "edges" files. In those few cases in which a portion of a school attendance boundary serves both sides of a street contractor staff used Esri’s Imagery base map to estimate the property lines of parcels. The data digitized from analog maps and verbal descriptions do not conform to cadastral data (and many of the original GIS files created by school districts do not conform with cadastral or parcel data).The SABS 2015-2016 file uses the WGS 1984 Web Mercator Auxiliary Sphere coordinate system.Additional information about SABS can be found on the EDGE website.The SABS dataset is intended for research purposes only and reflects a single snapshot in time. School boundaries frequently change from year to year. To verify legal descriptions of boundaries, users must contact the school district directly.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

  15. India 2020 GisData

    • kaggle.com
    zip
    Updated Jul 26, 2020
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    Durgesh Samariya (2020). India 2020 GisData [Dataset]. https://www.kaggle.com/themlphdstudent/india-2020-gisdata
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    zip(3747906 bytes)Available download formats
    Dataset updated
    Jul 26, 2020
    Authors
    Durgesh Samariya
    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
    India
    Description

    Content

    The shape files provides state level boundary data of India. Data is downloaded from igismap.

    Acknowledgements

    Data set : https://map.igismap.com/share-map/export-layer/Indian_States/06409663226af2f3114485aa4e0a23b4 Cover Image :

    Inspiration

    To be abled to plot state wise data.

  16. a

    World: Political Boundaries

    • hub.arcgis.com
    • edu.hub.arcgis.com
    Updated Sep 8, 2023
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    Education and Research (2023). World: Political Boundaries [Dataset]. https://hub.arcgis.com/maps/edu::world-political-boundaries/about
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    Dataset updated
    Sep 8, 2023
    Dataset authored and provided by
    Education and Research
    Area covered
    Description

    Explore a full description of the map.This 2020 political boundary data is from Garmin International and the United States Central Intelligence Agency The World Factbook and compiled by Esri. One layer includes the boundary lines for countries and another for states and provinces. These layers do not include contested boundaries and any you see are likely on the basemap you have chosen.CreditsEsri; Global Mapping International; U.S. Central Intelligence Agency (The World Factbook). From National Geographic MapMaker.Terms of Use This work is licensed under the Esri Master License Agreement.View Summary | View Terms of Use

  17. U

    2011 Census Geography boundaries (UK)

    • statistics.ukdataservice.ac.uk
    zip
    Updated Sep 20, 2022
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    Boundary (2022). 2011 Census Geography boundaries (UK) [Dataset]. https://statistics.ukdataservice.ac.uk/dataset/2011-census-geography-boundaries-uk
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    zipAvailable download formats
    Dataset updated
    Sep 20, 2022
    Dataset authored and provided by
    Boundary
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    United Kingdom
    Description

    A single area with complete coverage of the United Kingdom (England, Northern Ireland, Scotland and Wales combined).

    Please visit ONS Beginner's Guide to UK Geography for more info.

  18. P

    Broward County Cities

    • data.pompanobeachfl.gov
    Updated Aug 6, 2023
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    External Datasets (2023). Broward County Cities [Dataset]. https://data.pompanobeachfl.gov/dataset/broward-county-cities
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    zip, geojson, csv, kml, html, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    Aug 6, 2023
    Dataset provided by
    BC GIS
    Authors
    External Datasets
    Area covered
    Broward County
    Description

    A geographic depiction of city boundaries in Broward County, Florida.

    City boundary data was last updated April 13th, 2021 and previously on February 22, 2021. A small edit was made between Tamarac and Fort Lauderdale just SW of the Executive Airport. In February adjustments were made between Pembroke Pines, Southwest Ranches and Cooper City where their geographies are coincidence and are meant to follow the northern boundaries of STR geography. Prior to this edit, the City of Coral Springs had annexed four parcels of land from unincorporated Broward County; Ordinances 2018-014 (1 parcel) and 2018-036 (3 parcels), effective Sept 15, 2019. Previously in May 2019, a correction was made to the boundaries of Southwest Ranches and Pembroke Pines at Dykes Road and Sheraton, just north of Sheraton, on the west side of Dykes. Prior to this change, a correction was made to the Lauderhill boundary at the Florida Turnpike interchange located at the Sunrise Blvd entrance on the east side of the turnpike in April 2019; the 1959 Lauderhill incorporation legal description, (Laws of Florida 59-1478) left this thirteen acre area as unincorporated. A 1994 boundary change between Plantation and Lauderhill, (Laws of Florida 94-427) de-annexed five parcels from Plantation and annexed them to Lauderhill in this area. However in 1996, Broward County's Strategic Planning and Growth Management Department made available data sets provided by Broward County’s Planning and Information Technology Division via a CD. This data set depicted this unincorporated area as being part of Lauderhill. This depiction remained such until a boundary adjustment in 2006-2007 incorrectly depicted this as being part of Plantation. In 2009 Broward County was made aware of this error and adjusted it partially using the CD boundary as a template. This resulted in the area being incorrectly assigned to Lauderhill. In September of 2018, Lauderhill revisited this boundary depiction by the County and in 2019 it was concluded this area is unincorporated following the 1959 and the 1994 boundary adjustment legal descriptions.

    Prior to April 2019 there were other edits. The previous update of the data was Nov 7th, 2018, adusting the boundaries between Weston and Town of Davie to agree with House Bill 0871 which redefined a small area of their adjoining boundaries in the area of Weston Road and I-75. In July 2018, adjustments were made to the City of Margate to align with a city boundary shape file and written legal description as provided by John Shelton, GIS, City of Margate. The previous update was January 17th, 2018, correcting an unincorporated boundary line of the Triple H Ranch plat area within Parkland. This also reflects an adjustment made to Pembroke Pines southwest boundary between the Turnpike and SR 27 and the Sept 15th 2016 annexations of County unincorporated lands by Parkland. (City Ord 2016-06) and Coconut Creek (City Ord. 2015-027).Also a correction to the Hollywood/Davie boundary in the vicinity of Davie Blvd Ext and N 66 Ave and Oak St, per the City of Hollywood. Recent past boundary changes include annexations of county land to Pembroke Pines and Cooper City in 2015. And a Weston-Davie boundary adjustment in 2015; HB 871. And a July 2015 official resurvey of the City of Fort Lauderdale's boundaries which thus included adjustments to Oakland Park and Pompano Beach boundaries, (F. Gulliano, BC Engineering, M. Donaldson PSM, Fort Lauderdale). Also in 2015, a boundary adjustment was made to the eastern most boundary of Pompano Beach to match it to a more accurate depiction of the coastal erosion line by Broward County; (requested by the city to match their legal description). Further back, the were annexations for Parkland (2013) and Sunrise (Nov 2012) and updates to Lauderdale Lakes (per J. Petrov - BC Engineering 2012) and Plantation (I Reyes, GIS - Plantation 2012).


    Source: BCGIS

    Effective Date:

    Last Update: 04/15/2021

    Update Cycle: As needed.

  19. E

    Data from: ONS UACNTY09 coding frame geography

    • dtechtive.com
    • find.data.gov.scot
    xml, zip
    Updated Feb 21, 2017
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    EDINA (2017). ONS UACNTY09 coding frame geography [Dataset]. http://doi.org/10.7488/ds/1893
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    zip(16.08 MB), xml(0.0041 MB)Available download formats
    Dataset updated
    Feb 21, 2017
    Dataset provided by
    EDINA
    License

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

    Description

    UK boundary dataset corresponding to the geography of the ONS UACNTY09 coding frame. The dataset consists of 143 features corresponding to a standard GB county/unitary authority geography with the following exceptions. Orkney, Shetland and the Western Isles are included as a single feature; The Isles of Scilly are not included; Greater London is split into 2 Inner and Outer features corresponding to the super geographies within which the Inner and Outer London boroughs fall; Northern Ireland is provided as a single feature and is shown alongside the rest of GB in British National Grid. The GB portions of this dataset was derived from Ordnance Survey Boundary-Line data available as part of the Ordnance Survey OpenData initiative. The full terms and conditions of use of Ordnance Survey OpenData which apply to this dataset may be viewed at the following location: http://www.ordnancesurvey.co.uk/opendata/docs/os-opendata-licence.pdf. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2012-10-15 and migrated to Edinburgh DataShare on 2017-02-21.

  20. m

    MassGIS Data: New England Boundaries

    • mass.gov
    Updated Sep 15, 2007
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    MassGIS (Bureau of Geographic Information) (2007). MassGIS Data: New England Boundaries [Dataset]. https://www.mass.gov/info-details/massgis-data-new-england-boundaries
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    Dataset updated
    Sep 15, 2007
    Dataset authored and provided by
    MassGIS (Bureau of Geographic Information)
    Area covered
    Massachusetts
    Description

    September 2007

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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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CA Geographic Boundaries

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50 scholarly articles cite this dataset (View in Google Scholar)
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.

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