64 datasets found
  1. Geography Lookup API - by Geography ID

    • catalog.data.gov
    • ntia.data.commerce.gov
    • +3more
    Updated Mar 11, 2021
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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://www.commerce.gov/
    Description

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

  2. D

    Geography Lookup Table

    • opendata.fcc.gov
    • catalog.data.gov
    application/rdfxml +5
    Updated Aug 15, 2022
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    (2022). Geography Lookup Table [Dataset]. https://opendata.fcc.gov/Wireline/Geography-Lookup-Table/v5vt-e7vw
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    csv, json, application/rssxml, xml, tsv, application/rdfxmlAvailable download formats
    Dataset updated
    Aug 15, 2022
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    Summary data of fixed broadband coverage by geographic area. License and Attribution: Broadband data from FCC Form 477, and data from the U.S. Census Bureau that are presented on this site are offered free and not subject to copyright restriction. Data and content created by government employees within the scope of their employment are not subject to domestic copyright protection under 17 U.S.C. § 105. See, e.g., U.S. Government Works.

    While not required, when using content, data, documentation, code and related materials from fcc.gov or broadbandmap.fcc.gov in your own work, we ask that proper credit be given. Examples include: • Source data: FCC Form 477 • Map layer based on FCC Form 477 • Code data based on broadbandmap.fcc.gov

    The geography look ups are created from the US census shapefiles, which are in Global Coordinate System North American Datum of 1983 (GCS NAD83). The coordinates do not get reprojected during processing. The "centroid_lng", "centroid_lat" columns in the lookup table are the exact values from the US census shapefile (INTPTLON, INTPTLAT). The "bbox_arr" column is calculated from the bounding box/extent of the original geometry in the shapefile; no reprojection or transformations are done to the geometry.

  3. g

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

    • gimi9.com
    Updated Dec 9, 2024
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    (2024). 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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    Dataset updated
    Dec 9, 2024
    License

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

    Description

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

  4. Broadband Summary API - By Geography Type and Geography ID

    • catalog.data.gov
    • ntia.data.commerce.gov
    • +1more
    Updated Mar 11, 2021
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    National Telecommunication and Information Administration, Department of Commerce (2021). Broadband Summary API - By Geography Type and Geography ID [Dataset]. https://catalog.data.gov/dataset/broadband-summary-api-by-geography-type-and-geography-id
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    Dataset updated
    Mar 11, 2021
    Dataset provided by
    United States Department of Commercehttp://www.commerce.gov/
    Description

    This API returns broadband summary data by geography IDs for a specific geography type. It is designed to retrieve broadband summary data by geography and census metrics (population or households) combined as search criteria. The data includes wireline and wireless providers, different technologies and broadband speeds reported in the particular area being searched for on a scale of 0 to 1.

  5. Almanac API - Ranking by Geography ID within the Nation

    • catalog.data.gov
    • ntia.data.commerce.gov
    Updated Mar 11, 2021
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    National Telecommunication and Information Administration, Department of Commerce (2021). Almanac API - Ranking by Geography ID within the Nation [Dataset]. https://catalog.data.gov/dataset/almanac-api-ranking-by-geography-id-within-the-nation
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    Dataset updated
    Mar 11, 2021
    Dataset provided by
    United States Department of Commercehttp://www.commerce.gov/
    Description

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

  6. a

    College Map

    • hub.arcgis.com
    • catalog.data.gov
    • +1more
    Updated Mar 15, 2017
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    National Center for Education Statistics (2017). College Map [Dataset]. https://hub.arcgis.com/items/54c1339972ad4b1eb347047c7ca3e616
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    Dataset updated
    Mar 15, 2017
    Dataset authored and provided by
    National Center for Education Statistics
    License

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

    Description

    Finding Schools is now easier than ever with the College Map, the first geographic search tool published by IPEDS (Integrated Postsecondary Education Data System) providing access to over 7,000 certificate, undergraduate and graduate-level schools. This all-in-one tool enables students, parents and counselors to filter potential programs for location, major, tuition and more. Including both certificate-level programs and advanced degrees, this public application makes the often overwhelming process of school searching simple, and it’s available on mobile devices.Once the results are narrowed down, users can share their lists on social media or download in excel format. Additionally, the College Map integrates with the College Navigator, a research based search tool providing data from the complete list of IPEDS Survey indicators.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.

  7. d

    Almanac API - Ranking by Geography ID within a State

    • datasets.ai
    • cloud.csiss.gmu.edu
    • +3more
    23
    Updated Aug 6, 2024
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    Department of Commerce (2024). Almanac API - Ranking by Geography ID within a State [Dataset]. https://datasets.ai/datasets/almanac-api-ranking-by-geography-id-within-a-state
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    23Available download formats
    Dataset updated
    Aug 6, 2024
    Dataset authored and provided by
    Department of Commerce
    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.

  8. s

    Covid Infection Survey Geography (2020) to the Regions (2019) Lookup for the...

    • geoportal.statistics.gov.uk
    • hub.arcgis.com
    Updated Dec 2, 2020
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    Office for National Statistics (2020). Covid Infection Survey Geography (2020) to the Regions (2019) Lookup for the UK [Dataset]. https://geoportal.statistics.gov.uk/datasets/511cfedc32544d139b7ea6de02470ecf
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    Dataset updated
    Dec 2, 2020
    Dataset authored and provided by
    Office for National Statistics
    License

    https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences

    Area covered
    Description

    A lookup file between 2020 Covid Infection Survey Geography to 2020 Local Authority Districts to 2019 Regions in the United Kingdom, as at 1 October 2020. (File size - 56KB) Field Names - CIS20CD, LAD20CDS, RGN19CD, RGN19NM, FIDField Types - Text, Text, Text, Text, NumericField Lengths - 9, 255, 9, 255FID = The FID, or Feature ID is created by the publication process when the names and codes / lookup products are published to the Open Geography portal. REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/CIS20_to_RGN19_Lookup_b5eba17b771a43d7a6b956376b274c8f/FeatureServer

  9. H

    WHO GeoNetwork

    • data.niaid.nih.gov
    • dataverse.harvard.edu
    Updated May 5, 2011
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    (2011). WHO GeoNetwork [Dataset]. http://doi.org/10.7910/DVN/BRSYDO
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    Dataset updated
    May 5, 2011
    License

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

    Description

    Users can view maps, spatial, and statistical information drawn from different databases around the world. In addition, users can download data sets pertaining to prevalence and location of health facilities. Background The World Health Organization GeoNetwork is a geographic information management system that contains geo-referenced data sets and maps to facilitate the planning and monitoring of health related activities and health conditions. Information is available regarding the prevalence and location of health facilities. User Functionality Users must download the Geographic Information Systems (GIS) and Remote-Sensing (RSS) software applications to interact with the data tools, including digital maps, satellite images, and other geographic information. To obtain maps and other geographic information, users can search by term or geographic location or conduct an advanced search by time frame, year, and geographic location. There is a useful manual located under the “Help” tab, which enables users to learn more about GIS and how to use the GeoNetwork. Data Notes Data sources include: Food and Agriculture Organization of the United Nations (FAO), World Food Programme (WFP), and the United Nations Environment Programme (UNEP). The website announces datasets that have most recently been added to the GeoNetwork, but does not indicate the date it was updated.

  10. d

    Hunter 1 million scale geological units

    • data.gov.au
    • researchdata.edu.au
    • +2more
    zip
    Updated Apr 13, 2022
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    Bioregional Assessment Program (2022). Hunter 1 million scale geological units [Dataset]. https://data.gov.au/data/dataset/6d8c6d87-c397-4b84-be39-4b7831fb293e
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    zip(2039851)Available download formats
    Dataset updated
    Apr 13, 2022
    Dataset authored and provided by
    Bioregional Assessment Program
    License

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

    Description

    Abstract

    The dataset was derived by the Bioregional Assessment Programme. This dataset was derived from the Surface Geology of Australia, 1:1 000 000 scale, 2012 edition dataset. You can find a link to the parent dataset in the Lineage Field in this metadata statement. The History Field in this metadata statement describes how this dataset was derived.

    Geological units extracted from the national geodatabase for the Hunter subregion.

    The Surface Geology of Australia 1:1M scale dataset (2012 edition) is a seamless national coverage of outcrop and surficial geology, compiled for use at or around 1:1 million scale. The data maps outcropping bedrock geology and unconsolidated or poorly consolidated regolith material covering bedrock. Geological units are represented as polygon and line geometries, and are attributed with information regarding stratigraphic nomenclature and hierarchy, age, lithology, and primary data source. The dataset also contains geological contacts, structural features such as faults and shears, and miscellaneous supporting lines like the boundaries of water and ice bodies.

    The 2012 dataset has been updated from the previous 2010 data by updating geological unit data to 2012 information in the Australian Stratigraphic Units Database (http://www.ga.gov.au/products-services/data-applications/reference-databases/stratigraphic-units.html), incorporating new published mapping in the Northern Territory and Queensland, and correcting errors or inconsistent data identified in the previous edition, particularly in the Phanerozoic geology of Western Australia. The attribute structure of the dataset has also been revised to be more compatible with the GeoSciML data standard, published by the IUGS Commission for Geoscience Information.

    The first edition of this national dataset was first released in 2008, with map data compiled largely from simplifying and edgematching existing 1:250 000 scale geological maps. Where these maps were not current, more recent source maps ranging in scale from 1:50 000 to 1:1 million were used. In some areas where the only available geological maps were old and poorly located, some repositioning of mapping using recent satellite imagery or geophysics was employed.

    Dataset History

    Geological units extracted from the national geodatabase for the Hunter subregion.

    The 2012 dataset has been updated from the previous 2010 data by updating geological unit data to 2012 information in the Australian Stratigraphic Units Database (http://www.ga.gov.au/products-services/data-applications/reference-databases/stratigraphic-units.html), incorporating new published mapping in the Northern Territory and Queensland, and correcting errors or inconsistent data identified in the previous edition, particularly in the Phanerozoic geology of Western Australia. The attribute structure of the dataset has also been revised to be more compatible with the GeoSciML data standard, published by the IUGS Commission for Geoscience Information.

    The first edition of this national dataset was first released in 2008, with map data compiled largely from simplifying and edgematching existing 1:250 000 scale geological maps. Where these maps were not current, more recent source maps ranging in scale from 1:50 000 to 1:1 million were used. In some areas where the only available geological maps were old and poorly located, some repositioning of mapping using recent satellite imagery or geophysics was employed.

    Dataset Citation

    Bioregional Assessment Programme (2014) Hunter 1 million scale geological units. Bioregional Assessment Derived Dataset. Viewed 07 February 2017, http://data.bioregionalassessments.gov.au/dataset/6d8c6d87-c397-4b84-be39-4b7831fb293e.

    Dataset Ancestors

  11. a

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

    • catalogue.arctic-sdi.org
    Updated Aug 21, 2023
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    (2023). USGS Geographic Names (GNIS) Overlay Map Service from The National Map [Dataset]. https://catalogue.arctic-sdi.org/geonetwork/srv/search?keyword=name
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    Dataset updated
    Aug 21, 2023
    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 http://nationalmap.gov/gnis.html.

  12. a

    MSOA (2011) to Covid Infection Survey Geography (2020) Lookup in the UK

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • gimi9.com
    • +1more
    Updated Jan 13, 2021
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    MSOA (2011) to Covid Infection Survey Geography (2020) Lookup in the UK [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/datasets/709189c466b94aaea39f8363a52a5072
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    Dataset updated
    Jan 13, 2021
    Dataset authored and provided by
    Office for National Statistics
    License

    https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences

    Area covered
    Description

    A lookup file between 2011 Middle Layer Super Output Areas (MSOA) to 2020 Covid Infection Survey Geography in the United Kingdom, as at 1 October 2020. (File size - 920KB) Field Names - MSOA11CD, MSOA11NM, MSOA11NMW, CIS20CD, FIDField Types - Text, Text, Text, Text, NumericField Lengths - 9, 255, 255, 9FID = The FID, or Feature ID is created by the publication process when the names and codes / lookup products are published to the Open Geography portal. REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/MSOA11_to_CIS20_Lookup_131d08fc16814c5d8113175e0c9c6de2/FeatureServer

  13. a

    LSOA (2011) to Covid Infection Survey Geography (2020) Lookup in the UK

    • hub.arcgis.com
    • gimi9.com
    • +1more
    Updated Jan 13, 2021
    + more versions
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    Office for National Statistics (2021). LSOA (2011) to Covid Infection Survey Geography (2020) Lookup in the UK [Dataset]. https://hub.arcgis.com/maps/b16c6ba98e2047359a3207f5bd40e472_0/about
    Explore at:
    Dataset updated
    Jan 13, 2021
    Dataset authored and provided by
    Office for National Statistics
    License

    https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences

    Area covered
    Description

    A lookup file between 2011 Lower layer Super Output Areas (LSOA) to 2020 Covid Infection Survey Geography in the United Kingdom, as at 1 October 2020. (File size - 5MB) Field Names - LSOA11CD, LSOA11NM, LSOA11NMW, CIS20CD, FIDField Types - Text, Text, Text, Text, NumericField Lengths - 9, 255, 255, 9FID = The FID, or Feature ID is created by the publication process when the names and codes / lookup products are published to the Open Geography portal. REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LSOA11_to_CIS20_Lookup_532f33a284be4668b314a5dbc742e653/FeatureServer

  14. w

    U.S. Geological Survey Gap Analysis Program- Land Cover Data v2.2

    • data.wu.ac.at
    • datadiscoverystudio.org
    • +3more
    esri rest
    Updated Jun 8, 2018
    + more versions
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    Department of the Interior (2018). U.S. Geological Survey Gap Analysis Program- Land Cover Data v2.2 [Dataset]. https://data.wu.ac.at/schema/data_gov/MmMzYjljMzQtZmJjMy00NjUwLWE3YmMtNzRlOWRmMTFkZTVj
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    esri restAvailable download formats
    Dataset updated
    Jun 8, 2018
    Dataset provided by
    Department of the Interior
    Area covered
    d8998031d4cf34652dda2763c83c7b599a8a3521
    Description

    This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer

  15. d

    Geoscape Geocoded National Address File (G-NAF)

    • data.gov.au
    • researchdata.edu.au
    • +1more
    pdf, zip
    Updated Feb 17, 2025
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    Department of Industry, Science and Resources (DISR) (2025). Geoscape Geocoded National Address File (G-NAF) [Dataset]. https://data.gov.au/data/dataset/geocoded-national-address-file-g-naf
    Explore at:
    zip(1677778357), pdf, pdf(651732), zip(1673953258)Available download formats
    Dataset updated
    Feb 17, 2025
    Dataset authored and provided by
    Department of Industry, Science and Resources (DISR)
    Description

    Geoscape G-NAF is the geocoded address database for Australian businesses and governments. It’s the trusted source of geocoded address data for Australia with over 50 million contributed addresses distilled into 15.4 million G-NAF addresses. It is built and maintained by Geoscape Australia using independently examined and validated government data.

    From 22 August 2022, Geoscape Australia is making G-NAF available in an additional simplified table format. G-NAF Core makes accessing geocoded addresses easier by utilising less technical effort.

    G-NAF Core will be updated on a quarterly basis along with G-NAF.

    Further information about contributors to G-NAF is available here.

    With more than 15 million Australian physical address record, G-NAF is one of the most ubiquitous and powerful spatial datasets. The records include geocodes, which are latitude and longitude map coordinates. G-NAF does not contain personal information or details relating to individuals.

    Updated versions of G-NAF are published on a quarterly basis. Previous versions are available here

    Users have the option to download datasets with feature coordinates referencing either GDA94 or GDA2020 datums.

    Changes in the February 2025 release

    • Nationally, the February 2025 update of G-NAF shows an overall increase of 47,284 addresses (0.30%). The total number of addresses in G-NAF now stands at 15,706,733 of which 14,867,032 or 94.65% are principal.

    • In the February 2025 release of G-NAF, over 300 addresses in Morra, Western Australia have been updated. About 150 addresses have changed locations and 160 properties now have street numbers instead of lot numbers. Some properties are still using lot-numbers, resulting in two addressees. This issue will be resolved in the May 2025 update of G-NAF.

    • In the February release, Geoscape has re-classified geocode types of ‘Property Access Point Setback’ (PAPS) to be ‘Property Access Point’ (PAP) in South Australia where the geocode falls within a road casement as the geocode is not set back into a land parcel. This update has changed approximately 57,000 geocodes to PAP from their previous classification of PAPS, while there are some 14,000 PAPS geocodes that remain unchanged.

    • Geoscape has moved product descriptions, guides and reports online to https://docs.geoscape.com.au.

    Further information on G-NAF, including FAQs on the data, is available here or through Geoscape Australia’s network of partners. They provide a range of commercial products based on G-NAF, including software solutions, consultancy and support.

    Additional information: On 1 October 2020, PSMA Australia Limited began trading as Geoscape Australia.

    License Information

    Use of the G-NAF downloaded from data.gov.au is subject to the End User Licence Agreement (EULA)

    The EULA terms are based on the Creative Commons Attribution 4.0 International license (CC BY 4.0). However, an important restriction relating to the use of the open G-NAF for the sending of mail has been added.

    The open G-NAF data must not be used for the generation of an address or the compilation of an address for the sending of mail unless the user has verified that each address to be used for the sending of mail is capable of receiving mail by reference to a secondary source of information. Further information on this use restriction is available here.

    End users must only use the data in ways that are consistent with the Australian Privacy Principles issued under the Privacy Act 1988 (Cth).

    Users must also note the following attribution requirements:

    Preferred attribution for the Licensed Material:

    _G-NAF © Geoscape Australia licensed by the Commonwealth of Australia under the _Open Geo-coded National Address File (G-NAF) End User Licence Agreement.

    Preferred attribution for Adapted Material:

    Incorporates or developed using G-NAF © Geoscape Australia licensed by the Commonwealth of Australia under the Open Geo-coded National Address File (G-NAF) End User Licence Agreement.

    What to Expect When You Download G-NAF

    G-NAF is a complex and large dataset (approximately 5GB unpacked), consisting of multiple tables that will need to be joined prior to use. The dataset is primarily designed for application developers and large-scale spatial integration. Users are advised to read the technical documentation, including product change notices and the individual product descriptions before downloading and using the product. A quick reference guide on unpacking the G-NAF is also available.

  16. a

    Cobb County Parcel Viewer

    • geo-cobbcountyga.hub.arcgis.com
    Updated May 13, 2019
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    Cobb County, Georgia (2019). Cobb County Parcel Viewer [Dataset]. https://geo-cobbcountyga.hub.arcgis.com/app/e22d8c597b4e4762bcd2caa6127696e4
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    Dataset updated
    May 13, 2019
    Dataset authored and provided by
    Cobb County, Georgia
    Description

    GIS Map view look up parcel information including owner, taxes, market value and more.Important Mailing Label Information:The "Mailing Labels" button is is copy of the Parcels Layer and is intended to be turned OFF on the map, and is there just for the "Public Notification" Widget. This widget obtains information on the pop-up of a selected layer to create "Mailing Labels." This said, this layer contains the Owners Mailing Address information. Below is Arcaded used to customize the pop-up:Made three custom Arcade Lines below: Proper($feature["OWNER_NAM1"]) + Proper($feature["OWNER_NAM2"])Proper($feature["OWNER_ADDR"])Proper($feature["OWNER_CITY"]) + ',' + $feature["OWNER_STAT"] + ',' + $feature["OWNER_ZIP"]Below is the custom pop-up:{expression/expr0}{expression/expr1}{expression/expr2}

  17. Soil Survey Geographic (SSURGO) database for City of Baltimore, Maryland BES...

    • search.dataone.org
    Updated Jun 11, 2013
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    U.S. Department of Agriculture, Natural Resources Conservation Service (2013). Soil Survey Geographic (SSURGO) database for City of Baltimore, Maryland BES ID 331- [Dataset]. https://search.dataone.org/view/knb-lter-bes.331.56
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    Dataset updated
    Jun 11, 2013
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    U.S. Department of Agriculture, Natural Resources Conservation Service
    Area covered
    Description

    This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a 3.75 minute quadrangle format and include a detailed, field verified inventory of soils and nonsoil areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

  18. Bathymetry grids of SOJN05MV Survey (GA-1175)

    • ecat.ga.gov.au
    • researchdata.edu.au
    Updated Oct 7, 2020
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    Commonwealth of Australia (Geoscience Australia) (2020). Bathymetry grids of SOJN05MV Survey (GA-1175) [Dataset]. https://ecat.ga.gov.au/geonetwork/srv/api/records/56307c37-d595-4785-b589-f1fd3f5b0159
    Explore at:
    www:link-1.0-http--linkAvailable download formats
    Dataset updated
    Oct 7, 2020
    Dataset provided by
    Geoscience Australiahttp://ga.gov.au/
    Time period covered
    Feb 19, 1997 - Mar 2, 1997
    Area covered
    Description

    The SOJN05MV bathymetry survey, GA-1175 was acquired by Oregon state University onboard the Scripps Institution of Oceanography (SIO) RV Melville from the 19th of February to the 02nd of march 1997 using a SeaBeam 2000 sonar system. The bathymetry dataset was acquired while the RV Melville was transiting from Fremantle to Hobart. This dataset contains the 128m resolution, 32-bit geotiffs of the SOJN05MV survey produced from the processed SeaBeam system bathymetry data of the survey area using the CARIS HIPS and SIPS software. This dataset is published with the permission of the CEO, Geoscience Australia. Not to be used for navigational purposes.

    Appropriate acknowledgment must be given to both the original scientists (Christie, David) (http://www.marine-geo.org/tools/search/entry.php?id=SOJN05MV#datasets) and to the Marine Geoscience Data System (www.marine-geo.org).

  19. Ice Shelf Surface Elevation data: Amery Ice Shelf 1968

    • data.aad.gov.au
    • catalogue-temperatereefbase.imas.utas.edu.au
    • +2more
    Updated Oct 7, 1999
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    ALLISON, IAN (1999). Ice Shelf Surface Elevation data: Amery Ice Shelf 1968 [Dataset]. http://doi.org/10.4225/15/5ad8330bea559
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    Dataset updated
    Oct 7, 1999
    Dataset provided by
    Australian Antarctic Divisionhttps://www.antarctica.gov.au/
    Australian Antarctic Data Centre
    Authors
    ALLISON, IAN
    License

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

    Time period covered
    Oct 1, 1968 - Feb 28, 1969
    Area covered
    Description

    Ice shelf surface elevation data from an oversnow ground-based traverse along the centre of the Amery Ice Shelf from A509 (69.06 S, 72.15 E) to T4 (71.22 S, 69.48 E), including two transverse arms; between G1 (69.49 S, 71.72 E) and A119 (69.81 S, 73.28 E); and between T3 (70.79 S, 68.89 E) and T2 (71.00 S, 70.75 E) during the 1968 spring-summer season. More information can be found at the BEDMAP website.

    The fields in this dataset are:

    Mission ID Latitude Longitude Ice Thickness Surface Elevation Water Column Thickness Bed Elevation

  20. w

    Books called How to find out in geography : a guide to current books in...

    • workwithdata.com
    Updated Jul 12, 2024
    + more versions
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    Work With Data (2024). Books called How to find out in geography : a guide to current books in English [Dataset]. https://www.workwithdata.com/datasets/books?f=1&fcol0=book&fop0=%3D&fval0=How+to+find+out+in+geography+%3A+a+guide+to+current+books+in+English
    Explore at:
    Dataset updated
    Jul 12, 2024
    Dataset authored and provided by
    Work With Data
    License

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

    Description

    This dataset is about books and is filtered where the book is How to find out in geography : a guide to current books in English, featuring 7 columns including author, BNB id, book, book publisher, and ISBN. The preview is ordered by publication date (descending).

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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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Geography Lookup API - by Geography ID

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

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

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