100+ datasets found
  1. BSEE Data Center - Geographic Mapping Data in Digital Format

    • catalog.data.gov
    • s.cnmilf.com
    Updated Apr 4, 2025
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    Bureau of Safety and Environmental Enforcement (2025). BSEE Data Center - Geographic Mapping Data in Digital Format [Dataset]. https://catalog.data.gov/dataset/bsee-data-center-geographic-mapping-data-in-digital-format
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    Dataset updated
    Apr 4, 2025
    Dataset provided by
    Bureau of Safety and Environmental Enforcementhttp://www.bsee.gov/
    Description

    The geographic data are built from the Technical Information Management System (TIMS). TIMS consists of two separate databases: an attribute database and a spatial database. The attribute information for offshore activities is stored in the TIMS database. The spatial database is a combination of the ARC/INFO and FINDER databases and contains all the coordinates and topology information for geographic features. The attribute and spatial databases are interconnected through the use of common data elements in both databases, thereby creating the spatial datasets. The data in the mapping files are made up of straight-line segments. If an arc existed in the original data, it has been replaced with a series of straight lines that approximate the arc. The Gulf of America OCS Region stores all its mapping data in longitude and latitude format. All coordinates are in NAD 27. Data can be obtained in three types of digital formats: INTERACTIVE MAP: The ArcGIS web maps are an interactive display of geographic information, containing a basemap, a set of data layers (many of which include interactive pop-up windows with information about the data), an extent, navigation tools to pan and zoom, and additional tools for geospatial analysis. SHP: A Shapefile is a digital vector (non-topological) storage format for storing geometric location and associated attribute information. Shapefiles can support point, line, and area features with attributes held in a dBASE format file. GEODATABASE: An ArcGIS geodatabase is a collection of geographic datasets of various types held in a common file system folder, a Microsoft Access database, or a multiuser relational DBMS (such as Oracle, Microsoft SQL Server, PostgreSQL, Informix, or IBM DB2). The geodatabase is the native data structure for ArcGIS and is the primary data format used for editing and data management.

  2. Geographic Information System Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Jun 30, 2025
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    Growth Market Reports (2025). Geographic Information System Market Research Report 2033 [Dataset]. https://growthmarketreports.com/report/geographic-information-system-market-global-industry-analysis
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    pdf, pptx, csvAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    Growth Market Reports
    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Geographic Information System Market Outlook



    As per our latest research, the global Geographic Information System (GIS) market size reached USD 12.3 billion in 2024. The industry is experiencing robust expansion, driven by a surging demand for spatial data analytics across diverse sectors. The market is projected to grow at a CAGR of 11.2% from 2025 to 2033, reaching an estimated USD 31.9 billion by 2033. This accelerated growth is primarily attributed to the integration of advanced technologies such as artificial intelligence, IoT, and cloud computing with GIS solutions, as well as the increasing adoption of location-based services and smart city initiatives worldwide.




    One of the primary growth factors fueling the GIS market is the rapid adoption of geospatial analytics in urban planning and infrastructure development. Governments and private enterprises are leveraging GIS to optimize land use, manage resources efficiently, and enhance public services. Urban planners utilize GIS to analyze demographic trends, plan transportation networks, and ensure sustainable development. The integration of GIS with Building Information Modeling (BIM) and real-time data feeds has further amplified its utility in smart city projects, driving demand for sophisticated GIS platforms. The proliferation of IoT devices and sensors has also enabled the collection of high-resolution geospatial data, which is instrumental in developing predictive models for urban growth and disaster management.




    Another significant driver of the GIS market is the increasing need for disaster management and risk mitigation. GIS technology plays a pivotal role in monitoring natural disasters such as floods, earthquakes, and wildfires. By providing real-time spatial data, GIS enables authorities to make informed decisions, coordinate response efforts, and allocate resources effectively. The growing frequency and intensity of natural disasters, coupled with heightened awareness about climate change, have compelled governments and humanitarian organizations to invest heavily in advanced GIS solutions. These investments are not only aimed at disaster response but also at long-term resilience planning, thereby expanding the scope and scale of GIS applications.




    The expanding application of GIS in the agriculture and utilities sectors is another crucial growth factor. Precision agriculture relies on GIS to analyze soil conditions, monitor crop health, and optimize irrigation practices, ultimately boosting productivity and sustainability. In the utilities sector, GIS is indispensable for asset management, network optimization, and outage response. The integration of GIS with remote sensing technologies and drones has revolutionized data collection and analysis, enabling more accurate and timely decision-making. Moreover, the emergence of cloud-based GIS platforms has democratized access to geospatial data and analytics, empowering small and medium enterprises to harness the power of GIS for operational efficiency and strategic planning.




    From a regional perspective, North America continues to dominate the GIS market, supported by substantial investments in smart infrastructure, advanced research capabilities, and a strong presence of leading technology providers. However, Asia Pacific is emerging as the fastest-growing region, driven by rapid urbanization, government initiatives for digital transformation, and increasing adoption of GIS in agriculture and disaster management. Europe is also witnessing significant growth, particularly in transportation, environmental monitoring, and public safety applications. The Middle East & Africa and Latin America are gradually catching up, with growing investments in infrastructure development and resource management. This regional diversification is expected to drive innovation and competition in the global GIS market over the forecast period.





    Component Analysis



    The Geographic Information System market is segmented by component into hardware, software, and services, each playing a unique role

  3. d

    Detention Centers, LAGIC is consulting with local parish GIS departments to...

    • datadiscoverystudio.org
    • data.wu.ac.at
    html
    Updated Aug 19, 2017
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    (2017). Detention Centers, LAGIC is consulting with local parish GIS departments to create spatially accurate point and polygons data sets including the locations and building footprints of schools, churches, government buildings, law enforcement and emergency response offices, pha, Published in 2011, 1:12000 (1in=1000ft) scale, LSU Louisiana Geographic Information Center (LAGIC).. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/93146a877c734fd0bfffbf6891dd217c/html
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    htmlAvailable download formats
    Dataset updated
    Aug 19, 2017
    Description

    description: Detention Centers dataset current as of 2011. LAGIC is consulting with local parish GIS departments to create spatially accurate point and polygons data sets including the locations and building footprints of schools, churches, government buildings, law enforcement and emergency response offices, pha.; abstract: Detention Centers dataset current as of 2011. LAGIC is consulting with local parish GIS departments to create spatially accurate point and polygons data sets including the locations and building footprints of schools, churches, government buildings, law enforcement and emergency response offices, pha.

  4. H

    GEOGRAPHICAL INFORMATION SYSTEMS (GIS) DATA SETS

    • dataverse.harvard.edu
    Updated Apr 12, 2010
    + more versions
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    Andrew D. Mellinger (2010). GEOGRAPHICAL INFORMATION SYSTEMS (GIS) DATA SETS [Dataset]. http://doi.org/10.7910/DVN/BGZLD9
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 12, 2010
    Dataset provided by
    Harvard Dataverse
    Authors
    Andrew D. Mellinger
    License

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

    Description

    These data sets were created as part of The Center for International Development’s ongoing research into the role of geography in economic development (see www.cid.harvard.edu/economic.htm). They have been created between 1998 and 1999.

  5. w

    Building Footprints, LAGIC is consulting with local parish GIS departments...

    • data.wu.ac.at
    • datadiscoverystudio.org
    html
    Updated Aug 19, 2017
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    NSGIC Education | GIS Inventory (2017). Building Footprints, LAGIC is consulting with local parish GIS departments to create spatially accurate point and polygons data sets including the locations and building footprints of schools, churches, government buildings, law enforcement and emergency response offices, pha, Published in 2011, 1:12000 (1in=1000ft) scale, LSU Louisiana Geographic Information Center (LAGIC). [Dataset]. https://data.wu.ac.at/schema/data_gov/NTdjNWEyZjEtOTZjYS00YmM0LTgzN2ItYmE1MmM2Zjc3MmFj
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    htmlAvailable download formats
    Dataset updated
    Aug 19, 2017
    Dataset provided by
    NSGIC Education | GIS Inventory
    Area covered
    a57b6f3805987c1d9aefdac4648d5a6e71a93bd8
    Description

    Building Footprints dataset current as of 2011. LAGIC is consulting with local parish GIS departments to create spatially accurate point and polygons data sets including the locations and building footprints of schools, churches, government buildings, law enforcement and emergency response offices, pha.

  6. w

    Court Buildings, LAGIC is consulting with local parish GIS departments to...

    • data.wu.ac.at
    • datadiscoverystudio.org
    html
    Updated Aug 19, 2017
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    NSGIC Education | GIS Inventory (2017). Court Buildings, LAGIC is consulting with local parish GIS departments to create spatially accurate point and polygons data sets including the locations and building footprints of schools, churches, government buildings, law enforcement and emergency response offices, pha, Published in 2011, 1:12000 (1in=1000ft) scale, LSU Louisiana Geographic Information Center (LAGIC). [Dataset]. https://data.wu.ac.at/schema/data_gov/NGFkN2ZmNGItMzJmYS00YjFhLWE4OTUtZWQzZGJjZWRjOThh
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    htmlAvailable download formats
    Dataset updated
    Aug 19, 2017
    Dataset provided by
    NSGIC Education | GIS Inventory
    Area covered
    c581dcb00135871d2cc521a7ae66f18686cd6551
    Description

    Court Buildings dataset current as of 2011. LAGIC is consulting with local parish GIS departments to create spatially accurate point and polygons data sets including the locations and building footprints of schools, churches, government buildings, law enforcement and emergency response offices, pha.

  7. d

    Geographic Information System (GIS) characterization of Perdido Bay...

    • catalog.data.gov
    • search.dataone.org
    Updated Jul 1, 2025
    + more versions
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    (Point of Contact) (2025). Geographic Information System (GIS) characterization of Perdido Bay historical seagrass coverage, 1940 (NCEI Accession 0000604) [Dataset]. https://catalog.data.gov/dataset/geographic-information-system-gis-characterization-of-perdido-bay-historical-seagrass-coverage-1
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    Dataset updated
    Jul 1, 2025
    Dataset provided by
    (Point of Contact)
    Area covered
    Perdido Bay
    Description

    GIS representations of 1940 Historical seagrass coverage in Perdido Bay from United States Geological Survey/National Wetlands Research Center (USGS/NWRC).

  8. d

    Data from: Geographic Locations of Seabed Sediment Samples from the...

    • search.dataone.org
    • data.usgs.gov
    • +3more
    Updated Feb 1, 2018
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    Leslie B. Gallea (2018). Geographic Locations of Seabed Sediment Samples from the Stellwagen Bank National Marine Sanctuary Region (SB_SEDSAMPLES Shapefile) [Dataset]. https://search.dataone.org/view/1c719594-465d-47c1-bc48-0457150c9078
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    Dataset updated
    Feb 1, 2018
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Leslie B. Gallea
    Time period covered
    Jan 1, 1993 - Jan 1, 2004
    Area covered
    Variables measured
    FID, Mud, Quad, Year, Shape, Latitude, 1_phi_siz, 2_phi_siz, 3_phi_siz, 4_phi_siz, and 27 more
    Description

    The U.S. Geological Survey, in collaboration with the National Oceanic and Atmospheric Administration's (NOAA) National Marine Sanctuary Program, conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary region from 1993 to 2004. The mapped area is approximately 3,700 square km (1,100 square nm) in size and was subdivided into 18 quadrangles. Several series of sea floor maps of the region based on multibeam sonar surveys have been published. In addition, 2,628 seabed sediment samples were collected and analyzed and approximately 10,600 still photographs of the seabed were acquired during the project. These data provide the basis for scientists, policymakers, and managers for understanding the complex ecosystem of the sanctuary region and for monitoring and managing its economic and natural resources.

  9. Libraries, LAGIC is consulting with local parish GIS departments to create...

    • data.wu.ac.at
    • datadiscoverystudio.org
    html
    Updated Aug 19, 2017
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    NSGIC Education | GIS Inventory (2017). Libraries, LAGIC is consulting with local parish GIS departments to create spatially accurate point and polygons data sets including the locations and building footprints of schools, churches, government buildings, law enforcement and emergency response offices, pha, Published in 2011, 1:12000 (1in=1000ft) scale, LSU Louisiana Geographic Information Center (LAGIC). [Dataset]. https://data.wu.ac.at/schema/data_gov/NmM2OGY0MzktZmJjYy00ZDRlLWFlYTctOTM2ZjM2ZDg0N2E1
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    htmlAvailable download formats
    Dataset updated
    Aug 19, 2017
    Dataset provided by
    National States Geographic Information Council
    Area covered
    e4b7561b7a43cd5414e16ad8abc41b817b0f4e62
    Description

    Libraries dataset current as of 2011. LAGIC is consulting with local parish GIS departments to create spatially accurate point and polygons data sets including the locations and building footprints of schools, churches, government buildings, law enforcement and emergency response offices, pha.

  10. Grocery Stores, LAGIC is consulting with local parish GIS departments to...

    • data.wu.ac.at
    • datadiscoverystudio.org
    html
    Updated Aug 19, 2017
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    NSGIC Education | GIS Inventory (2017). Grocery Stores, LAGIC is consulting with local parish GIS departments to create spatially accurate point and polygons data sets including the locations and building footprints of schools, churches, government buildings, law enforcement and emergency response offices, pha, Published in 2011, 1:12000 (1in=1000ft) scale, LSU Louisiana Geographic Information Center (LAGIC). [Dataset]. https://data.wu.ac.at/schema/data_gov/MzVmNmM4YWEtYmIyMS00Y2M4LTg2YzgtMjhiMjE0YjM2NzQy
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    htmlAvailable download formats
    Dataset updated
    Aug 19, 2017
    Dataset provided by
    National States Geographic Information Council
    Area covered
    979dd67c9c9344e569f37538ef2cffc7d41864e4
    Description

    Grocery Stores dataset current as of 2011. LAGIC is consulting with local parish GIS departments to create spatially accurate point and polygons data sets including the locations and building footprints of schools, churches, government buildings, law enforcement and emergency response offices, pha.

  11. w

    Universities, LAGIC is consulting with local parish GIS departments to...

    • data.wu.ac.at
    html
    Updated Aug 19, 2017
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    NSGIC Education | GIS Inventory (2017). Universities, LAGIC is consulting with local parish GIS departments to create spatially accurate point and polygons data sets including the locations and building footprints of schools, churches, government buildings, law enforcement and emergency response offices, pha, Published in 2011, 1:12000 (1in=1000ft) scale, LSU Louisiana Geographic Information Center (LAGIC). [Dataset]. https://data.wu.ac.at/schema/data_gov/NTMzZDc3NWUtZDM4My00MTIzLThhZGEtM2EwYTQwYTRhNWJl
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    htmlAvailable download formats
    Dataset updated
    Aug 19, 2017
    Dataset provided by
    NSGIC Education | GIS Inventory
    Area covered
    d7b4ac81769e0579b9b19c498afa37aff0405dbf
    Description

    Universities dataset current as of 2011. LAGIC is consulting with local parish GIS departments to create spatially accurate point and polygons data sets including the locations and building footprints of schools, churches, government buildings, law enforcement and emergency response offices, pha.

  12. a

    Quarter Sections

    • canadian-county-geographic-information-center-canadiancounty.hub.arcgis.com
    • canadian-county-public-gis-data-canadiancounty.hub.arcgis.com
    Updated Jun 6, 2024
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    CanadianCounty (2024). Quarter Sections [Dataset]. https://canadian-county-geographic-information-center-canadiancounty.hub.arcgis.com/datasets/d4d420c325bb43ceadd5dafd6688a6af
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    Dataset updated
    Jun 6, 2024
    Dataset authored and provided by
    CanadianCounty
    Area covered
    Description

    Layers in this dataset represent Public Land Survey System subdivisions for Canadian County. Included are Townships, Sections, Quarter Sections and Government Lots. This data was created from 2019 to 2021 as part of a project to update county parcel data in partnership with ProWest & Associates (https://www.prowestgis.com/) and CEC Corporation (https://www.connectcec.com/). Corners were located to the quarter section level and additional corners were determined for the South Canadian River meanders based on the original government surveys. Quarter section corners were located using Certified Corner Records ( filed by Oklahoma licensed professional surveyors with the Oklahoma Department of Libraries where those records included coordinates. When a corner record could not be found or did not include coordinates, other interpolation methods were employed. These included connecting known corner record locations to unknown corners using data from filed subdivisions or from highway plans on record with the Oklahoma Department of Transportation. Where no corner records with coordinates were available and no interpolation methods could be used, aerial inspection was used to locate corners as the last option.Corner location accuracy varies as the method of locating the corner varies. For corners located using Certified Corner Records, accuracy is high depending on the age of the corner record and can possibly be less than 1 U.S. Foot. For corners located using interpolation methods, accuracy depends on the additional material used to interpolate the corner. In general, newer subdivisions and highway plans yield higher accuracy. For meander corners located using original government surveys, accuracy will be low due to the age of those surveys which date to the 1870's at the earliest. Additionally, corners that were located with aerials as the last available option cannot be assumed to be accurate.The data was built at the quarter section level first by connecting located corners and larger subdivisions were created from the quarter sections. For townships that extend into Grady County, township lines were only roughly located outside sections not in Canadian County.

  13. Geographic Information System (GIS) Software Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Jun 30, 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
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    pdf, csv, pptxAvailable download formats
    Dataset updated
    Jun 30, 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 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 management and urban planning, while Latin America and the Middle East & Africa are emerging as promising markets due to increasing investments in infrastructure and resource management.





    Component Analysis



    The GIS Software market is segmented by component into Software and Services, each playing a pivotal role in the overall value chain. The software segment includes comprehensive GIS platforms, spatial analytics tools, and specialized applications

  14. T

    Iowa Geographic Map Server

    • mydata.iowa.gov
    • data.iowa.gov
    • +1more
    application/rdfxml +5
    Updated Feb 14, 2017
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    Iowa State University, Geographic Information Systems Support and Research Facility (2017). Iowa Geographic Map Server [Dataset]. https://mydata.iowa.gov/w/vcpw-3ijw/default?cur=UcHB8GE_sD&from=vxtNo1Bf2fZ
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    csv, xml, tsv, application/rssxml, application/rdfxml, jsonAvailable download formats
    Dataset updated
    Feb 14, 2017
    Dataset authored and provided by
    Iowa State University, Geographic Information Systems Support and Research Facility
    Area covered
    Iowa
    Description

    This site provides free access to Iowa geographic map data, including aerial photography, orthophotos, elevation maps, and historical maps. The data is available through an on-line map viewer and through Web Map Service (WMS) connections for GIS. The site was developed by the Iowa State University Geographic Information Systems Support and Research Facility in cooperation with the Iowa Department of Natural Resources, the USDA Natural Resources Conservation Service, and the Massachusetts Institute of Technology. This site was first launched in March 1999.

  15. v

    VT US National Grid Index

    • geodata.vermont.gov
    • data.amerigeoss.org
    • +3more
    Updated Aug 3, 2008
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    VT Center for Geographic Information (2008). VT US National Grid Index [Dataset]. https://geodata.vermont.gov/datasets/vt-us-national-grid-index
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    Dataset updated
    Aug 3, 2008
    Dataset authored and provided by
    VT Center for Geographic Information
    License

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

    Area covered
    Description

    (Link to Metadata) USNGVT is a U.S. National Grid Index (1000m x 1000m) covering Vermont. Its a polygon feature class originally constructed by the Center for Interdisciplinary Geospatial Information Technologies at Delta State University with support from the US Geological Survey under the Cooperative Agreement 07ERAG0083. VCGI merged UTM zone 18 and 19 into a single layer, the projected to VCS NAD83. Further information about the US National Grid is available from http://www.fgdc.gov/usng and a viewing of these layers as applied to local geography may be seen at the National Map, http://www.nationalmap.gov. This dataset includes the USNG grid for parts of Vermont, New Hampshire, Massachusetts and Connecticut that lie in UTM zone 18.

  16. g

    Utah Automated Geographic Reference Center (ARGC)

    • data.geospatialhub.org
    Updated Jul 29, 2022
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    WyomingGeoHub (2022). Utah Automated Geographic Reference Center (ARGC) [Dataset]. https://data.geospatialhub.org/datasets/e872a146adda4098bb4cd72b895ed500
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    Dataset updated
    Jul 29, 2022
    Dataset authored and provided by
    WyomingGeoHub
    Description

    Metadata record for Utah's ARGC. Link in record. The Utah Automated Geographic Reference Center (AGRC) provides a wide range of Geographic Information System (GIS) support to the State of Utah. AGRC strives to facilitate coordination among Utah GIS users and effective, efficient use of GIS resources. Other services include stewardship of the State Geographic Information Database (SGID), facilitation of programs and activities to implement GIS technology across the state, and coordination of GIS policy development and implementation activities.

  17. Campgrounds

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Jun 30, 2021
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    Esri U.S. Federal Datasets (2021). Campgrounds [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/datasets/95cbb2dfda7e4cfdb6eb7a26a36a710b
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    Dataset updated
    Jun 30, 2021
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri U.S. Federal Datasets
    License

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

    Area covered
    Description

    Recreation StructuresThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Geological Survey, displays recreation structures in the U.S. Per the USGS, "Structures data are designed to be used in general mapping and in the analysis of structure related activities using geographic information system technology. The National Map structures data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and transportation, to produce general reference base maps."Headquarters & Picnic Areas (Core Banks, NC)Data currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Recreation) and will support mapping, analysis, data exports and OGC API – Feature accessNGDAID: 135 (USGS National Structures Dataset - USGS National Map Downloadable Data Collection)OGC API Features Link: (Recreation Structures - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: The National MapFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Real Property Theme Community. Per the Federal Geospatial Data Committee (FGDC), Real Property is defined as "the spatial representation (location) of real property entities, typically consisting of one or more of the following: unimproved land, a building, a structure, site improvements and the underlying land. Complex real property entities (that is "facilities") are used for a broad spectrum of functions or missions. This theme focuses on spatial representation of real property assets only and does not seek to describe special purpose functions of real property such as those found in the Cultural Resources, Transportation, or Utilities themes."For other NGDA Content: Esri Federal Datasets

  18. n

    Address Pre Input Output - AddressNC

    • nconemap.gov
    • hub.arcgis.com
    • +1more
    Updated Jul 1, 2022
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    NC OneMap / State of North Carolina (2022). Address Pre Input Output - AddressNC [Dataset]. https://www.nconemap.gov/datasets/address-pre-input-output-addressnc
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    Dataset updated
    Jul 1, 2022
    Dataset authored and provided by
    NC OneMap / State of North Carolina
    Area covered
    Description

    AddressNC has been prioritized by the North Carolina Geographic Information Coordinating Council (GICC) as a critical framework dataset. The AddressNC Program runs parallel to and is derived from the North Carolina 911 Board Next Generation 911 (NG911) Program.  Address data has been identified as mission critical for validation and accurate call routing within NG911 and the AddressNC Program completes a full-circle approach of address maintenance and sustainability through applied enhancements and quality control beyond 911 requirements.  A primary goal of AddressNC is to continually develop and maintain quality address points on a continuous cycle through updates published in NG911. Various agencies in federal, state, and local government can benefit by applying practical applications of quality addressing in their own programs, negating the need to rely on outdated statewide addressing data and/or using paid address data sets from third party sources.

  19. a

    Political Input Output - AddressNC

    • nc-onemap-2-nconemap.hub.arcgis.com
    Updated Jul 1, 2022
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    NC OneMap / State of North Carolina (2022). Political Input Output - AddressNC [Dataset]. https://nc-onemap-2-nconemap.hub.arcgis.com/items/9b63a9d0c0144a49b855128083a18caf
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    Dataset updated
    Jul 1, 2022
    Dataset authored and provided by
    NC OneMap / State of North Carolina
    Area covered
    Description

    AddressNC has been prioritized by the North Carolina Geographic Information Coordinating Council (GICC) as a critical framework dataset. The AddressNC Program runs parallel to and is derived from the North Carolina 911 Board Next Generation 911 (NG911) Program.  Address data has been identified as mission critical for validation and accurate call routing within NG911 and the AddressNC Program completes a full-circle approach of address maintenance and sustainability through applied enhancements and quality control beyond 911 requirements.  A primary goal of AddressNC is to continually develop and maintain quality address points on a continuous cycle through updates published in NG911. Various agencies in federal, state, and local government can benefit by applying practical applications of quality addressing in their own programs, negating the need to rely on outdated statewide addressing data and/or using paid address data sets from third party sources.

  20. d

    Location and sediment texture information of surficial sediment samples...

    • search.dataone.org
    • data.usgs.gov
    • +2more
    Updated Feb 1, 2018
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    U.S. Geological Survey (2018). Location and sediment texture information of surficial sediment samples collected within the New York Bight by the U.S. Geological Survey, 1995 - 1999 (Esri point shapefile, Geographic, WGS84) [Dataset]. https://search.dataone.org/view/4b53edf6-b781-47f4-9c97-69c03f4f02b6
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    Dataset updated
    Feb 1, 2018
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey
    Time period covered
    Jan 1, 1995 - Jan 1, 1998
    Area covered
    Variables measured
    Clay, Mean, Phi0, Phi1, Phi2, Phi3, Phi4, Phi5, Phi6, Phi7, and 23 more
    Description

    A better understanding of sediment dynamics in coastal areas can be attained by mapping the surface sediment distribution and subsurface stratigraphy of the lower shoreface and inner-continental shelf. In 1995, the U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, began a program to produce geologic maps of the sea floor throughout the New York Bight Apex using high-resolution sidescan-sonar, subbottom profiling, and sediment sampling techniques. The goals of the investigation are to investigate the role that inner-shelf morphology and geologic framework play in the evolution of the coastal region.

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Bureau of Safety and Environmental Enforcement (2025). BSEE Data Center - Geographic Mapping Data in Digital Format [Dataset]. https://catalog.data.gov/dataset/bsee-data-center-geographic-mapping-data-in-digital-format
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BSEE Data Center - Geographic Mapping Data in Digital Format

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Dataset updated
Apr 4, 2025
Dataset provided by
Bureau of Safety and Environmental Enforcementhttp://www.bsee.gov/
Description

The geographic data are built from the Technical Information Management System (TIMS). TIMS consists of two separate databases: an attribute database and a spatial database. The attribute information for offshore activities is stored in the TIMS database. The spatial database is a combination of the ARC/INFO and FINDER databases and contains all the coordinates and topology information for geographic features. The attribute and spatial databases are interconnected through the use of common data elements in both databases, thereby creating the spatial datasets. The data in the mapping files are made up of straight-line segments. If an arc existed in the original data, it has been replaced with a series of straight lines that approximate the arc. The Gulf of America OCS Region stores all its mapping data in longitude and latitude format. All coordinates are in NAD 27. Data can be obtained in three types of digital formats: INTERACTIVE MAP: The ArcGIS web maps are an interactive display of geographic information, containing a basemap, a set of data layers (many of which include interactive pop-up windows with information about the data), an extent, navigation tools to pan and zoom, and additional tools for geospatial analysis. SHP: A Shapefile is a digital vector (non-topological) storage format for storing geometric location and associated attribute information. Shapefiles can support point, line, and area features with attributes held in a dBASE format file. GEODATABASE: An ArcGIS geodatabase is a collection of geographic datasets of various types held in a common file system folder, a Microsoft Access database, or a multiuser relational DBMS (such as Oracle, Microsoft SQL Server, PostgreSQL, Informix, or IBM DB2). The geodatabase is the native data structure for ArcGIS and is the primary data format used for editing and data management.

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