100+ datasets found
  1. Geography Lookup API - by Geography ID

    • catalog.data.gov
    • s.cnmilf.com
    • +3more
    Updated Mar 11, 2021
    + more versions
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    National Telecommunication and Information Administration, Department of Commerce (2021). Geography Lookup API - by Geography ID [Dataset]. https://catalog.data.gov/dataset/geography-lookup-api-by-geography-id
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    Dataset updated
    Mar 11, 2021
    Dataset provided by
    United States Department of Commercehttp://commerce.gov/
    Description

    This API returns a geography of a specified geography type by the geography id.

  2. Geographic Information System Analytics Market Analysis, Size, and Forecast...

    • technavio.com
    Updated Jul 15, 2024
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    Technavio (2024). Geographic Information System Analytics Market Analysis, Size, and Forecast 2024-2028: North America (US and Canada), Europe (France, Germany, UK), APAC (China, India, South Korea), Middle East and Africa , and South America [Dataset]. https://www.technavio.com/report/geographic-information-system-analytics-market-industry-analysis
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    Dataset updated
    Jul 15, 2024
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    France, United Kingdom, Canada, Germany, United States, Global
    Description

    Snapshot img

    Geographic Information System Analytics Market Size 2024-2028

    The geographic information system analytics market size is forecast to increase by USD 12 billion at a CAGR of 12.41% between 2023 and 2028.

    The GIS Analytics Market analysis is experiencing significant growth, driven by the increasing need for efficient land management and emerging methods in data collection and generation. The defense industry's reliance on geospatial technology for situational awareness and real-time location monitoring is a major factor fueling market expansion. Additionally, the oil and gas industry's adoption of GIS for resource exploration and management is a key trend. Building Information Modeling (BIM) and smart city initiatives are also contributing to market growth, as they require multiple layered maps for effective planning and implementation. The Internet of Things (IoT) and Software as a Service (SaaS) are transforming GIS analytics by enabling real-time data processing and analysis.
    Augmented reality is another emerging trend, as it enhances the user experience and provides valuable insights through visual overlays. Overall, heavy investments are required for setting up GIS stations and accessing data sources, making this a promising market for technology innovators and investors alike.
    

    What will be the Size of the GIS Analytics Market during the forecast period?

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    The geographic information system analytics market encompasses various industries, including government sectors, agriculture, and infrastructure development. Smart city projects, building information modeling, and infrastructure development are key areas driving market growth. Spatial data plays a crucial role in sectors such as transportation, mining, and oil and gas. Cloud technology is transforming GIS analytics by enabling real-time data access and analysis. Startups are disrupting traditional GIS markets with innovative location-based services and smart city planning solutions. Infrastructure development in sectors like construction and green buildings relies on modern GIS solutions for efficient planning and management. Smart utilities and telematics navigation are also leveraging GIS analytics for improved operational efficiency.
    GIS technology is essential for zoning and land use management, enabling data-driven decision-making. Smart public works and urban planning projects utilize mapping and geospatial technology for effective implementation. Surveying is another sector that benefits from advanced GIS solutions. Overall, the GIS analytics market is evolving, with a focus on providing actionable insights to businesses and organizations.
    

    How is this Geographic Information System Analytics Industry segmented?

    The geographic information system analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

    End-user
    
      Retail and Real Estate
      Government
      Utilities
      Telecom
      Manufacturing and Automotive
      Agriculture
      Construction
      Mining
      Transportation
      Healthcare
      Defense and Intelligence
      Energy
      Education and Research
      BFSI
    
    
    Components
    
      Software
      Services
    
    
    Deployment Modes
    
      On-Premises
      Cloud-Based
    
    
    Applications
    
      Urban and Regional Planning
      Disaster Management
      Environmental Monitoring Asset Management
      Surveying and Mapping
      Location-Based Services
      Geospatial Business Intelligence
      Natural Resource Management
    
    
    Geography
    
      North America
    
        US
        Canada
    
    
      Europe
    
        France
        Germany
        UK
    
    
      APAC
    
        China
        India
        South Korea
    
    
      Middle East and Africa
    
        UAE
    
    
      South America
    
        Brazil
    
    
      Rest of World
    

    By End-user Insights

    The retail and real estate segment is estimated to witness significant growth during the forecast period.

    The GIS analytics market analysis is witnessing significant growth due to the increasing demand for advanced technologies in various industries. In the retail sector, for instance, retailers are utilizing GIS analytics to gain a competitive edge by analyzing customer demographics and buying patterns through real-time location monitoring and multiple layered maps. The retail industry's success relies heavily on these insights for effective marketing strategies. Moreover, the defense industries are integrating GIS analytics into their operations for infrastructure development, permitting, and public safety. Building Information Modeling (BIM) and 4D GIS software are increasingly being adopted for construction project workflows, while urban planning and designing require geospatial data for smart city planning and site selection.

    The oil and gas industry is leveraging satellite imaging and IoT devices for land acquisition and mining operations. In the public sector,

  3. Demographics API - By Geography Type and Geography ID

    • datasets.ai
    • catalog.data.gov
    • +2more
    23
    Updated Sep 4, 2024
    + more versions
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    Department of Commerce (2024). Demographics API - By Geography Type and Geography ID [Dataset]. https://datasets.ai/datasets/demographics-api-by-geography-type-and-geography-id
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    23Available download formats
    Dataset updated
    Sep 4, 2024
    Dataset provided by
    United States Department of Commercehttp://commerce.gov/
    Authors
    Department of Commerce
    Description

    This API returns a search for the demographic information for a particular geography type and geography ID

  4. NGDAID 34 - Geographic Names Information System (GNIS) - USGS National Map...

    • ngda-cultural-resources-geoplatform.hub.arcgis.com
    Updated Aug 9, 2022
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    GeoPlatform ArcGIS Online (2022). NGDAID 34 - Geographic Names Information System (GNIS) - USGS National Map Downloadable Data Collection [Dataset]. https://ngda-cultural-resources-geoplatform.hub.arcgis.com/datasets/ngdaid-34-geographic-names-information-system-gnis-usgs-national-map-downloadable-data-collection
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    Dataset updated
    Aug 9, 2022
    Dataset provided by
    https://arcgis.com/
    Authors
    GeoPlatform ArcGIS Online
    Area covered
    Description

    USGS developed The National Map Gazetteer as the Federal and national standard (ANSI INCITS 446-2008) for geographic nomenclature based on the Geographic Names Information System (GNIS). The National Map Gazetteer contains information about physical and cultural geographic features, geographic areas, and locational entities that are generally recognizable and locatable by name (have achieved some landmark status) and are of interest to any level of government or to the public for any purpose that would lead to the representation of the feature in printed or electronic maps and/or geographic information systems. The dataset includes features of all types in the United States, its associated areas, and Antarctica, current and historical, but not including roads and highways. The dataset holds the federally recognized name of each feature and defines the feature location by state, county, USGS topographic map, and geographic coordinates. Other attributes include names or spellings other than the official name, feature classification, and historical and descriptive information. The dataset assigns a unique, permanent feature identifier, the Feature ID, as a standard Federal key for accessing, integrating, or reconciling feature data from multiple data sets. This dataset is a flat model, establishing no relationships between features, such as hierarchical, spatial, jurisdictional, organizational, administrative, or in any other manner. As an integral part of The National Map, the Gazetteer collects data from a broad program of partnerships with federal, state, and local government agencies and other authorized contributors. The Gazetteer provides data to all levels of government and to the public, as well as to numerous applications through a web query site, web map, feature and XML services, file download services, and customized files upon request. The National Map download client allows free downloads of public domain geographic names data by state in a pipe-delimited text format. For additional information on the GNIS, go to httpS://nationalmap.gov/gnis.html.

  5. Image Geo-localization dataset

    • kaggle.com
    Updated Feb 23, 2025
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    Hamidreza_Sj (2025). Image Geo-localization dataset [Dataset]. https://www.kaggle.com/datasets/hamidrezasj/image-geo-localization-dataset
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 23, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Hamidreza_Sj
    Description

    Image Geo-Localization Dataset

    Overview

    This dataset is designed for Visual Geo-Localization (VG), also known as Visual Place Recognition (VPR). The task involves determining the geographic location of a given image by retrieving the most visually similar images from a database. This dataset provides a diverse collection of urban images, enabling researchers and practitioners to train and evaluate geo-localization models under challenging real-world conditions.

    Dataset Details

    This dataset consists of images curated for training and evaluation of visual geo-localization models. The data is drawn from multiple sources to ensure diversity in lighting conditions, perspectives, and geographical contexts.

    1️⃣ GSV-Cities (Subset)

    • Purpose: Used for training the model.
    • Description: A subset of Google Street View city images, covering various urban environments.
    • Key Features: Diverse cityscapes to facilitate robust feature learning. Includes different architectural styles, seasons, and lighting conditions.

    2️⃣ SF-XS (San Francisco Extra Small)

    • Purpose: Used for testing geo-localization models.
    • Description: A challenging dataset containing images from San Francisco, USA.
    • Key Challenges: Urban landscapes with similar-looking structures. Perspective changes due to camera viewpoints. Variations in weather and time of day.

    3️⃣ Tokyo-XS (Tokyo Extra Small)

    • Purpose: Used for testing geo-localization models.
    • Description: A dataset containing images from Tokyo, Japan, offering significant differences from Western cities.
    • Key Challenges: Cultural and architectural diversity. Extreme viewpoint and lighting variations. High-density urban scenery.

    Usage & Applications

    This dataset is ideal for: ✅ Training and testing deep learning models for visual geo-localization. ✅ Studying the impact of lighting, perspective, and cultural diversity on place recognition. ✅ Benchmarking retrieval-based localization methods. ✅ Exploring feature extraction techniques for geo-localization tasks.

    How to Use This Dataset

    1. Download the dataset.
    2. Use the GSV-Cities subset for model training.
    3. Evaluate performance on SF-XS and Tokyo-XS datasets.

    If you find this dataset useful, please consider citing it in your research or giving it an upvote on Kaggle! 🚀

  6. North America Geographic Information System Market Analysis - Size and...

    • technavio.com
    pdf
    Updated Feb 21, 2025
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    Technavio (2025). North America Geographic Information System Market Analysis - Size and Forecast 2025-2029 [Dataset]. https://www.technavio.com/report/north-america-gis-market-analysis
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Feb 21, 2025
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2025 - 2029
    Area covered
    North America
    Description

    Snapshot img

    North America Geographic Information System Market Size 2025-2029

    The geographic information system market size in North America is forecast to increase by USD 11.4 billion at a CAGR of 23.7% between 2024 and 2029.

    The market is experiencing significant growth due to the increasing adoption of advanced technologies such as artificial intelligence, satellite imagery, and sensors in various industries. In fleet management, GIS software is being used to optimize routes and improve operational efficiency. In the context of smart cities, GIS solutions are being utilized for content delivery, public safety, and building information modeling. The demand for miniaturization of technologies is also driving the market, allowing for the integration of GIS into smaller devices and applications. However, data security concerns remain a challenge, as the collection and storage of sensitive information requires robust security measures. The insurance industry is also leveraging GIS for telematics and risk assessment, while the construction sector uses GIS for server-based project management and planning. Overall, the GIS market is poised for continued growth as these trends and applications continue to evolve.
    

    What will be the Size of the market During the Forecast Period?

    Request Free Sample

    The Geographic Information System (GIS) market encompasses a range of technologies and applications that enable the collection, management, analysis, and visualization of spatial data. Key industries driving market growth include transportation, infrastructure planning, urban planning, and environmental monitoring. Remote sensing technologies, such as satellite imaging and aerial photography, play a significant role in data collection. Artificial intelligence and the Internet of Things (IoT) are increasingly integrated into GIS solutions for real-time location data processing and operational efficiency.
    Applications span various sectors, including agriculture, natural resources, construction, and smart cities. GIS is essential for infrastructure analysis, disaster management, and land management. Geospatial technology enables spatial data integration, providing valuable insights for decision-making and optimization. Market size is substantial and growing, fueled by increasing demand for efficient urban planning, improved infrastructure, and environmental sustainability. Geospatial startups continue to emerge, innovating in areas such as telematics, natural disasters, and smart city development.
    

    How is this market segmented and which is the largest segment?

    The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

    Component
    
      Software
      Data
      Services
    
    
    Deployment
    
      On-premise
      Cloud
    
    
    Geography
    
      North America
    
        Canada
        Mexico
        US
    

    By Component Insights

    The software segment is estimated to witness significant growth during the forecast period.
    

    The Geographic Information System (GIS) market encompasses desktop, mobile, cloud, and server software for managing and analyzing spatial data. In North America, industry-specific GIS software dominates, with some commercial entities providing open-source alternatives for limited functions like routing and geocoding. Despite this, counterfeit products pose a threat, making open-source software a viable option for smaller applications. Market trends indicate a shift towards cloud-based GIS solutions for enhanced operational efficiency and real-time location data. Spatial data applications span various sectors, including transportation infrastructure planning, urban planning, natural resources management, environmental monitoring, agriculture, and disaster management. Technological innovations, such as artificial intelligence, the Internet of Things (IoT), and satellite imagery, are revolutionizing GIS solutions.

    Cloud-based GIS solutions, IoT integration, and augmented reality are emerging trends. Geospatial technology is essential for smart city projects, climate monitoring, intelligent transportation systems, and land management. Industry statistics indicate steady growth, with key players focusing on product innovation, infrastructure optimization, and geospatial utility solutions.

    Get a glance at the market report of share of various segments Request Free Sample

    Market Dynamics

    Our North America Geographic Information System Market researchers analyzed the data with 2024 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.

    What are the key market drivers leading to the rise in the adoption of the North America Geographic Information System Market?

    Rising applications of geographi

  7. Geographic Names Information System (GNIS) Feature Layers

    • hub.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +1more
    Updated Apr 16, 2024
    + more versions
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    GeoPlatform ArcGIS Online (2024). Geographic Names Information System (GNIS) Feature Layers [Dataset]. https://hub.arcgis.com/maps/5091b822ad3e47f3b6bc5bc275fb3c22
    Explore at:
    Dataset updated
    Apr 16, 2024
    Dataset provided by
    https://arcgis.com/
    Authors
    GeoPlatform ArcGIS Online
    Area covered
    Description

    USGS developed The National Map Gazetteer as the Federal and national standard (ANSI INCITS 446-2008) for geographic nomenclature based on the Geographic Names Information System (GNIS). The National Map Gazetteer contains information about physical and cultural geographic features, geographic areas, and locational entities that are generally recognizable and locatable by name (have achieved some landmark status) and are of interest to any level of government or to the public for any purpose that would lead to the representation of the feature in printed or electronic maps and/or geographic information systems. The dataset includes features of all types in the United States, its associated areas, and Antarctica, current and historical, but not including roads and highways. The dataset holds the federally recognized name of each feature and defines the feature location by state, county, USGS topographic map, and geographic coordinates. Other attributes include names or spellings other than the official name, feature classification, and historical and descriptive information. The dataset assigns a unique, permanent feature identifier, the Feature ID, as a standard Federal key for accessing, integrating, or reconciling feature data from multiple data sets. This dataset is a flat model, establishing no relationships between features, such as hierarchical, spatial, jurisdictional, organizational, administrative, or in any other manner. As an integral part of The National Map, the Gazetteer collects data from a broad program of partnerships with federal, state, and local government agencies and other authorized contributors. The Gazetteer provides data to all levels of government and to the public, as well as to numerous applications through a web query site, web map, feature and XML services, file download services, and customized files upon request. The National Map download client allows free downloads of public domain geographic names data by state in a pipe-delimited text format. For additional information on the GNIS, go to https://www.usgs.gov/tools/geographic-names-information-system-gnis. See https://apps.nationalmap.gov/help/ for assistance with The National Map viewer, download client, services, or metadata. Data Refreshed March, 2025

  8. Community Anchor Institutions API - By Geography Type and Geography ID

    • catalog.data.gov
    • datadiscoverystudio.org
    • +2more
    Updated Mar 11, 2021
    + more versions
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    National Telecommunication and Information Administration, Department of Commerce (2021). Community Anchor Institutions API - By Geography Type and Geography ID [Dataset]. https://catalog.data.gov/dataset/community-anchor-institutions-api-by-geography-type-and-geography-id
    Explore at:
    Dataset updated
    Mar 11, 2021
    Dataset provided by
    United States Department of Commercehttp://commerce.gov/
    Description

    This API returns the broadband availability among the Community Anchor Institutions by geography type and ID.

  9. G

    Geographic Information System (GIS) Software Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Sep 1, 2025
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    Growth Market Reports (2025). Geographic Information System (GIS) Software Market Research Report 2033 [Dataset]. https://growthmarketreports.com/report/geographic-information-system-software-market-global-industry-analysis
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Sep 1, 2025
    Dataset authored and provided by
    Growth Market Reports
    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Geographic Information System (GIS) Software Market Outlook



    According to our latest research, the global Geographic Information System (GIS) Software market size reached USD 11.6 billion in 2024, reflecting a robust demand for spatial data analytics and location-based services across various industries. The market is experiencing a significant growth trajectory, driven by a CAGR of 12.4% from 2025 to 2033. By the end of 2033, the GIS Software market is forecasted to attain a value of USD 33.5 billion. This remarkable expansion is primarily attributed to the integration of advanced technologies such as artificial intelligence, IoT, and cloud computing, which are enhancing the capabilities and accessibility of GIS platforms.




    One of the major growth factors propelling the GIS Software market is the increasing adoption of location-based services across urban planning, transportation, and utilities management. Governments and private organizations are leveraging GIS solutions to optimize infrastructure development, streamline resource allocation, and improve emergency response times. The proliferation of smart city initiatives worldwide has further fueled the demand for GIS tools, as urban planners and municipal authorities require accurate spatial data for effective decision-making. Additionally, the evolution of 3D GIS and real-time mapping technologies is enabling more sophisticated modeling and simulation, expanding the scope of GIS applications beyond traditional mapping to include predictive analytics and scenario planning.




    Another significant driver for the GIS Software market is the rapid digitization of industries such as agriculture, mining, and oil & gas. Precision agriculture, for example, relies heavily on GIS platforms to monitor crop health, manage irrigation, and enhance yield forecasting. Similarly, the mining sector uses GIS for exploration, environmental impact assessment, and asset management. The integration of remote sensing data with GIS software is providing stakeholders with actionable insights, leading to higher efficiency and reduced operational risks. Furthermore, the growing emphasis on environmental sustainability and regulatory compliance is prompting organizations to invest in advanced GIS solutions for monitoring land use, tracking deforestation, and managing natural resources.



    The evolution of 3D GIS is revolutionizing the way spatial data is visualized and analyzed, offering a more immersive and detailed perspective of geographic information. This technology allows for the creation of three-dimensional models that provide a realistic representation of urban landscapes, infrastructure, and natural environments. By integrating 3D GIS with real-time data feeds, organizations can enhance their spatial analysis capabilities, enabling more accurate simulations and predictions. This advancement is particularly beneficial for urban planners and architects who require detailed visualizations to assess the impact of new developments and infrastructure projects. Moreover, 3D GIS is facilitating better communication and collaboration among stakeholders by providing a common platform for visualizing complex spatial data.




    The expanding use of cloud-based GIS solutions is also a key factor driving market growth. Cloud deployment offers scalability, cost-effectiveness, and remote accessibility, making GIS tools more accessible to small and medium enterprises as well as large organizations. The cloud model supports real-time data sharing and collaboration, which is particularly valuable for disaster management and emergency response teams. As organizations increasingly prioritize digital transformation, the demand for cloud-native GIS platforms is expected to rise, supported by advancements in data security, interoperability, and integration with other enterprise systems.




    Regionally, North America remains the largest market for GIS Software, accounting for a significant share of global revenues. This leadership is underpinned by substantial investments in smart infrastructure, advanced transportation systems, and environmental monitoring programs. The Asia Pacific region, however, is witnessing the fastest growth, driven by rapid urbanization, government-led digital initiatives, and the expansion of the utility and agriculture sectors. Europe continues to demonstrate steady adoption, particularly in environmental manage

  10. A

    VT Geographic Names

    • data.amerigeoss.org
    csv, esri rest +5
    Updated Jul 30, 2019
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    United States[old] (2019). VT Geographic Names [Dataset]. https://data.amerigeoss.org/id/dataset/vt-geographic-names
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    zip, html, csv, kml, esri rest, geojson, ogc wmsAvailable download formats
    Dataset updated
    Jul 30, 2019
    Dataset provided by
    United States[old]
    Description

    (Link to Metadata) BasemapLandmarks_GEONAME is derived from the US Geological Survey's National Geographic Names Database (GNIS). The data were obtained by VCGI for distribution.

  11. g

    Geographic Identification Code Scheme

    • datasearch.gesis.org
    • dataverse-staging.rdmc.unc.edu
    Updated Jan 22, 2020
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    U.S. Department of Commerce; U.S. Bureau of the Census (2020). Geographic Identification Code Scheme [Dataset]. https://datasearch.gesis.org/dataset/httpsdataverse.unc.eduoai--hdl1902.29CD-0064
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    Dataset updated
    Jan 22, 2020
    Dataset provided by
    Odum Institute Dataverse Network
    Authors
    U.S. Department of Commerce; U.S. Bureau of the Census
    Description

    This CD (TIGER/GICS file) contains the entity names, codes, selected geographic relationships, total population, total number of housing units, area measurements (land, total water, inland water, coastal water, Great Lakes water, and territorial water), and internal points for the high-level geographic entities discussed in the next section. The data dictionary identifies the data items reported in this file. This file contains information related to: - The regions and divisions established b y the Bureau of the Census for statistical purposes - The 50 States and several statistically equivalent entities: the District of Columbia, six territories under U.S. jurisdiction (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, the Republic of Palau, Puerto Rico, and the Virgin Islands of the United States), and two freely associated entities for which the Census Bureau prepared TIGER/Line(TM) files although they were not included in the 1990 census the Federated States of Micronesia and the Marshall Islands - American Indian and Alaska Native areas - Counties and statistically equivalent entities - County subdivisions - Places - Metropolitan Areas - Urbanized Areas The TIGER/GICS file is composed of 12 separate files, 6 files with national hierarchies and 6 with State hierarchies.

    Note to Users: This CD is part of a collection located in the Data Archive of the Odum Institute for Research in Social Science, at the University of North Carolina at Chapel Hill. The collection is located in Room 10, Manning Hall. Users may check the CDs out subscribing to the honor system. Items can be checked out for a period of two weeks. Loan forms are located adjacent to the collection.

  12. A

    USGS Geographic Names (GNIS) Overlay Map Service from The National Map -...

    • data.amerigeoss.org
    • catalog.data.gov
    • +1more
    esri rest, wfs, wms
    Updated Aug 21, 2022
    + more versions
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    United States (2022). USGS Geographic Names (GNIS) Overlay Map Service from The National Map - National Geospatial Data Asset (NGDA) Geographic Names Information System (GNIS) [Dataset]. https://data.amerigeoss.org/tl/dataset/usgs-geographic-names-gnis-overlay-map-service-from-the-national-map-national-geospatial-data-a
    Explore at:
    esri rest, wfs, wmsAvailable download formats
    Dataset updated
    Aug 21, 2022
    Dataset provided by
    United States
    Description

    USGS developed The National Map (TNM) Gazetteer as the Federal and national standard (ANSI INCITS 446-2008) for geographic nomenclature based on the Geographic Names Information System (GNIS). The National Map Gazetteer contains information about physical and cultural geographic features, geographic areas, and locational entities that are generally recognizable and locatable by name (have achieved some landmark status) and are of interest to any level of government or to the public for any purpose that would lead to the representation of the feature in printed or electronic maps and/or geographic information systems. The dataset includes features of all types in the United States, its associated areas, and Antarctica, current and historical, but not including roads and highways. The dataset holds the federally recognized name of each feature and defines the feature location by state, county, USGS topographic map, and geographic coordinates. Other attributes include names or spellings other than the official name, feature classification, and historical and descriptive information. The dataset assigns a unique, permanent feature identifier, the Feature ID, as a standard Federal key for accessing, integrating, or reconciling feature data from multiple data sets. This dataset is a flat model, establishing no relationships between features, such as hierarchical, spatial, jurisdictional, organizational, administrative, or in any other manner. As an integral part of The National Map, the Gazetteer collects data from a broad program of partnerships with federal, state, and local government agencies and other authorized contributors. The Gazetteer provides data to all levels of government and to the public, as well as to numerous applications through a web query site, web map, feature and XML services, file download services, and customized files upon request. The National Map viewer allows free downloads of public domain geographic names data by state in a pipe-delimited text format. For additional information on the GNIS, go to https://nationalmap.gov/gnis.html.

  13. Washington Land Area in Square Miles

    • open.piercecountywa.gov
    • internal.open.piercecountywa.gov
    csv, xlsx, xml
    Updated Jun 13, 2023
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    U.S. Census Bureau (2023). Washington Land Area in Square Miles [Dataset]. https://open.piercecountywa.gov/w/265y-pus5/default?cur=FXhJphlsKeZ
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    csv, xml, xlsxAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    U.S. Census Bureau
    Area covered
    Washington
    Description

    U.S. Census Bureau, data file from Geography Division based on the TIGER/Geographic Identification Code Scheme (TIGER/GICS) computer file. Land area updated every 10 years. http://www.census.gov/geo/www/tiger/index.html or http://factfinder2.census.gov.

    Land area is the size, in square units (metric and nonmetric) of all areas designated as land in the Census Bureau's national geographic (TIGER®) database.

  14. Geographic Locator Codes for US States

    • kaggle.com
    Updated Feb 14, 2018
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    Holly (2018). Geographic Locator Codes for US States [Dataset]. https://www.kaggle.com/datasets/hollyg/glcs-for-us-states
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 14, 2018
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Holly
    License

    http://www.gnu.org/licenses/old-licenses/gpl-2.0.en.htmlhttp://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html

    Area covered
    United States
    Description

    Content

    Useful for the US Traffic Fatality Records dataset

    Acknowledgements

    From gsa.gov

  15. u

    Earth Data Analysis Center

    • gstore.unm.edu
    zip
    Updated Jan 27, 2014
    + more versions
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    Earth Data Analysis Center (2014). Earth Data Analysis Center [Dataset]. https://gstore.unm.edu/apps/rgis/datasets/a8b934f4-4377-402d-b455-5e0ccc65ee36/metadata/FGDC-STD-001-1998.html
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    zip(14)Available download formats
    Dataset updated
    Jan 27, 2014
    Dataset provided by
    Earth Data Analysis Center
    Time period covered
    Nov 30, 2012
    Area covered
    West Bounding Coordinate -109.050113 East Bounding Coordinate -103.000673 North Bounding Coordinate 36.99943 South Bounding Coordinate 31.331905, New Mexico
    Description

    The Protected Areas Database of the United States (PAD-US) is a geodatabase, managed by USGS GAP, that illustrates and describes public land ownership, management and other conservation lands, including voluntarily provided privately protected areas. The State, Regional and LCC geodatabases contain two feature classes. The PADUS1_3_FeeEasement feature class and the national MPA feature class. Legitimate and other protected area overlaps exist in the full inventory, with Easements loaded on top of Fee. Parcel data within a protected area are dissolved in this file that powers the PAD-US Viewer. As overlaps exist, GAP creates separate analytical layers to summarize area statistics for "GAP Status Code" and "Owner Name". Contact the PAD-US Coordinator for more information. The lands included in PAD-US are assigned conservation measures that qualify their intent to manage lands for the preservation of biological diversity and to other natural, recreational and cultural uses; managed for these purposes through legal or other effective means. The geodatabase includes: 1) Geographic boundaries of public land ownership and voluntarily provided private conservation lands (e.g., Nature Conservancy Preserves); 2) The combination land owner, land manager, management designation or type, parcel name, GIS Acres and source of geographic information of each mapped land unit 3) GAP Status Code conservation measure of each parcel based on USGS National Gap Analysis Program (GAP) protection level categories which provide a measurement of management intent for long-term biodiversity conservation 4) IUCN category for a protected area's inclusion into UNEP-World Conservation Monitoring Centre's World Database for Protected Areas. IUCN protected areas are defined as, "A clearly defined geographical space, recognized, dedicated and managed, through legal or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values" and are categorized following a classification scheme available through USGS GAP; 5) World Database of Protected Areas (WDPA) Site Codes linking the multiple parcels of a single protected area in PAD-US and connecting them to the Global Community. As legitimate and other overlaps exist in the combined inventory GAP creates separate analytical layers to obtain area statistics for "GAP Status Code" and "Owner Name". PAD-US version 1.3 Combined updates include: 1) State, local government and private protected area updates delivered September 2011 from PAD-US State Data Stewards: CO (Colorado State University), FL (Florida Natural Areas Inventory), ID (Idaho Fish and Game), MA (The Commonwealth's Office of Geographic Information Systems, MassGIS), MO (University of Missouri, MoRAP), MT (Montana Natural Heritage Program), NM (Natural Heritage New Mexico), OR (Oregon Natural Heritage Program), VA (Department of Conservation and Recreation, Virginia Natural Heritage Program). 2) Select local government (i.e. county, city) protected areas (3,632) across the country (to complement the current PAD-US inventory) aggregated by the Trust for Public Land (TPL) for their Conservation Almanac that tracks the conservation finance movement across the country. 3) A new Date of Establishment field that identifies the year an area was designated or otherwise protected, attributed for 86% of GAP Status Code 1 and 2 protected areas. Additional dates will be provided in future updates. 4) A national wilderness area update from wilderness.net 5) The Access field that describes public access to protected areas as defined by data stewards or categorical assignment by Primary Designation Type. . The new Access Source field documents local vs. categorical assignments. See the PAD-US Standard Manual for more information: gapanalysis.usgs.gov/padus 6) The transfer of conservation measures (i.e. GAP Status Codes, IUCN Categories) and documentation (i.e. GAP Code Source, GAP Code Date) from PAD-US version 1.2 or categorical assignments (see PAD-US Standard) when not provided by data stewards 7) Integration of non-sensitive National Conservation Easement Database (NCED) easements from August 2011, July 2012 with PAD-US version 1.2 easements. Duplicates were removed, unless 'Stacked' = Y and multiple easements exist. 8) Unique ID's transferred from NCED or requested for new easements. NCED and PAD-US are linked via Source UID in the PAD-US version 1.3 Easement feature class. 9) Official (member and eligible) MPAs from the NOAA MPA Inventory (March 2011, www.mpa.gov) translated into the PAD-US schema with conservation measures transferred from PAD-US version 1.2 or categorically assigned to new protected areas. Contact the PAD-US Coordinator for documentation of categorical GAP Status Code assignments for MPAs. 10) Identified MPA records that overlap existing protected areas in the PAD-US Fee feature class (i.e. PADUS Overlap field in MPA feature class). For example, many National Wildlife Refuges and National Parks are also MPAs and are represented in the PAD-US MPA and Fee feature classes.

  16. 2023 Geography: GEOINFO | Annual Geographic Information Table (GEO Geography...

    • data.census.gov
    Updated Aug 15, 2024
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    CED (2024). 2023 Geography: GEOINFO | Annual Geographic Information Table (GEO Geography Information) [Dataset]. https://data.census.gov/cedsci/table?q=Table
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    Dataset updated
    Aug 15, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    CED
    License

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

    Time period covered
    2023
    Description

    Key Table Information.Table Title.Annual Geographic Information Table.Table ID.GEOINFO2023.GEOINFO.Survey/Program.Geography.Year.2023.Dataset.GEO Geography Information.Source.U.S. Census Bureau, 2023 Geography.Release Date.August 15, 2024.Dataset Universe.Geographic information available in data.census.gov for year 2023.Methodology.Data Items and Other Identifying Records.Geographic Area Name Area (Land, in square meters) Area (Land, in square miles) Area (Water, in square meters) Area (Water, in square miles) Internal Point (Latitude) Internal Point (Longitude) For full list of all the variables including those available in the API refer to the following link: https://api.census.gov/data/2023/geoinfo/variables.html.Unit(s) of Observation.Geographic entity.Geography Coverage.For a full list defining the geographies covered go to https://api.census.gov/data/2023/geoinfo/geography.html.Technical Documentation/Methodology.https://www.census.gov/programs-surveys/geography/about/glossary.html.Table Information.API Information.https://api.census.gov/data/2023/geoinfo.html.Data-Specific Notes.The Geography Information dataset (GEOINFO) contains all the geographies that are disseminated by the U.S Census Bureau during a calendar year. The dataset combines all these disseminated geographies into one centralized location to allow for easy user access. The Geography Information dataset includes spatial attributes for the disseminated geographies, such as a point of internal latitude, a point of internal longitude, and the area of the water and land both in square meters and square miles. The geographies contained in the Geography Information dataset are the geographies disseminated for surveys and programs such as the American Community Survey, Community Resilience Estimates, Current Population Survey, Decennial Census, Economic Census, Economic Surveys, Household Pulse Survey, International Database, Population Estimates, Secondary Employment Outcomes, Public Sector, and Survey of Market Absorption. The Geography Information dataset does include island area geographies but does not contain any international geographies. The Geography Information dataset will be created annually for the calendar year prior once all of the Geographic Information Tables for the various surveys and programs are received for the year. The Geography Information dataset will be released around the early summer every year. The program will first produce a Geography Information dataset for data year 2023 and eventually produce datasets going backwards to data year 2020. The program will also produce a Geography Information dataset for every subsequent year after data year 2023. Note: The Geography Information dataset contains the geographies disseminated for the Population Estimates Program but does not currently support the release of the population estimates. Please refer to the following URL for population estimates: https://www.census.gov/programs-surveys/popest/data.html Note: The Geography Information dataset for 2023 does not include any island area geographies..Additional Information.Contact Information.census.data@census.gov.Suggested Citation.U.S. Census Bureau. "Annual Geographic Information Table" Geography, GEO Geography Information, Table GEOINFO, -1, https://data.census.gov/table/GEOINFO2023.GEOINFO?q=GEOINFO: Accessed on August 31, 2025..

  17. a

    tl SDC TN PL20 QuickStat BlockGroup 150 gdb

    • hub.arcgis.com
    Updated Aug 17, 2021
    + more versions
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    University of Tennessee (2021). tl SDC TN PL20 QuickStat BlockGroup 150 gdb [Dataset]. https://hub.arcgis.com/datasets/501a40cf72204893b513131bc4dde2eb
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    Dataset updated
    Aug 17, 2021
    Dataset authored and provided by
    University of Tennessee
    License

    Public Domain Mark 1.0https://creativecommons.org/publicdomain/mark/1.0/
    License information was derived automatically

    Description

    The 2020 Census Redistricting Summary File contains several hundred data fields spread over six different file segments. To facilitate access to more popular variables, the Tennessee State Data Center compiled a “QuickStat” reports detailing population, race/ethnicity and housing information. These fields are combined with geographic fields from the 2020 TIGER/Line Shapefiles for use with mapping software.Field names, descriptions and types selected from the two sources are detailed below.

          Field Name
          Alias
          Data Type
          Length
    
    
    
          OBJECTID
          OBJECTID
          Object ID
    
    
    
          Shape
          Shape
          Geometry
    
    
    
          STATEFP
          State FIPS code
          Text
          2
    
    
          COUNTYFP
          County FIPS code
          Text
          3
    
    
          TRACTCE
          Tract code
          Text
          6
    
    
          BLKGRPCE
          BLKGRPCE
          Text
          1
    
    
          GEOID
          Geographic identifier
          Text
          12
    
    
          NAMELSAD
          Legal/statistical area description
          Text
          13
    
    
          MTFCC
          MAF/TIGER feature class code
          Text
          5
    
    
          FUNCSTAT
          Functional status
          Text
          1
    
    
          ALAND
          Land area
          Long
    
    
    
          AWATER
          Water area
          Long
    
    
    
          INTPTLAT
          Latitude of the internal point
          Text
          11
    
    
          INTPTLON
          Longitude of the internal point
          Text
          12
    
    
          SUMLEV
          Summary Level
          Text
          255
    
    
          LOGRECNO
          Logical Record Number
          Long
    
    
    
          P0010001
          Total population
          Long
    
    
    
          P0010002
          Population of one race
          Long
    
    
    
          P0010003
          White alone
          Long
    
    
    
          P0010004
          Black or African American alone
          Long
    
    
    
          P0010005
          American Indian and Alaska Native alone
          Long
    
    
    
          P0010006
          Asian alone
          Long
    
    
    
          P0010007
          Native Hawaiian and Other Pacific Islander alone
          Long
    
    
    
          P0010008
          Some Other Race alone
          Long
    
    
    
          P0010009
          Population of two or more races:
          Long
    
    
    
          P0020002
          Hispanic or Latino
          Long
    
    
    
          P0020003
          Not Hispanic or Latino:
          Long
    
    
    
          P0020004
          Population of one race (Not Hispanic or Latino)
          Long
    
    
    
          P0020005
          White alone (Not Hispanic or Latino)
          Long
    
    
    
          P0020006
          Black or African American alone (Not Hispanic or Latino)
          Long
    
    
    
          P0020007
          American Indian and Alaska Native alone (Not Hispanic or Latino)
          Long
    
    
    
          P0020008
          Asian alone (Not Hispanic or Latino)
          Long
    
    
    
          P0020009
          Native Hawaiian and Other Pacific Islander alone (Not Hispanic or Latino)
          Long
    
    
    
          P0020010
          Some Other Race alone (Not Hispanic or Latino)
          Long
    
    
    
          P0020011
          Population of two or more races (Not Hispanic or Latino)
          Long
    
    
    
          P0030001
          Total population 18 years and over
          Long
    
    
    
          H0010001
          Total housing units
          Long
    
    
    
          H0010002
          Occupied housing units
          Long
    
    
    
          H0010003
          Vacant housing units
          Long
    
    
    
          P0050001
          Total population in group quarters
          Long
    
    
    
          P0050002
          Institutionalized population
          Long
    
    
    
          P0050003
          Correctional facilities for adults
          Long
    
    
    
          P0050004
          Juvenile facilities
          Long
    
    
    
          P0050005
          Nursing facilities/Skilled-nursing facilities
          Long
    
    
    
          P0050006
          Other institutional facilities
          Long
    
    
    
          P0050007
          Noninstitutionalized population
          Long
    
    
    
          P0050008
          College/University student housing
          Long
    
    
    
          P0050009
          Military quarters
          Long
    
    
    
          P0050010
          Other noninstitutional facilities
          Long
    
    
    
          Shape_Length
    
          Double
    
    
    
          Shape_Area
    
          Double
    
  18. g

    Demographics API - By Geography Type and Geography ID | gimi9.com

    • gimi9.com
    + more versions
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    Demographics API - By Geography Type and Geography ID | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_demographics-api-by-geography-type-and-geography-id/
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    License

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

    Description

    🇺🇸 미국

  19. g

    Community Anchor Institutions API - By Geography Type and Geography ID |...

    • gimi9.com
    Updated Feb 17, 2011
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    (2011). Community Anchor Institutions API - By Geography Type and Geography ID | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_community-anchor-institutions-api-by-geography-type-and-geography-id/
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    Dataset updated
    Feb 17, 2011
    License

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

    Description

    🇺🇸 미국

  20. Almanac API - Ranking by Geography ID within a State

    • s.cnmilf.com
    • datasets.ai
    • +3more
    Updated Mar 11, 2021
    + more versions
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    National Telecommunication and Information Administration, Department of Commerce (2021). Almanac API - Ranking by Geography ID within a State [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/almanac-api-ranking-by-geography-id-within-a-state
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    Dataset updated
    Mar 11, 2021
    Dataset provided by
    United States Department of Commercehttp://commerce.gov/
    Description

    This API is designed to find the rankings by geography within the state for a specific metric (population or household) and rank (any of the metrics from provider, demographic, technology or speed). The results are the top ten and bottom ten records within the state for the particular geography type and my area rankings. Additionally we include +/- 5 rankings from the 'my' area rank.

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National Telecommunication and Information Administration, Department of Commerce (2021). Geography Lookup API - by Geography ID [Dataset]. https://catalog.data.gov/dataset/geography-lookup-api-by-geography-id
Organization logo

Geography Lookup API - by Geography ID

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Dataset updated
Mar 11, 2021
Dataset provided by
United States Department of Commercehttp://commerce.gov/
Description

This API returns a geography of a specified geography type by the geography id.

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