20 datasets found
  1. a

    QGIS - Open Source GIS Software

    • hub.arcgis.com
    • data-ecgis.opendata.arcgis.com
    • +1more
    Updated Aug 9, 2018
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    Eaton County Michigan (2018). QGIS - Open Source GIS Software [Dataset]. https://hub.arcgis.com/documents/57198670f4234919bfab87fb64d40a82
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    Dataset updated
    Aug 9, 2018
    Dataset authored and provided by
    Eaton County Michigan
    Description

    This is a link to the QGIS website where you can download open-source GIS software for viewing, analyzing and manipulating geodata like our downloadable shapefiles.

  2. GIS In Utility Industry Market Analysis North America, Europe, APAC, Middle...

    • technavio.com
    Updated Dec 31, 2024
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    Technavio (2024). GIS In Utility Industry Market Analysis North America, Europe, APAC, Middle East and Africa, South America - US, China, Canada, Japan, Germany, Russia, India, Brazil, France, UAE - Size and Forecast 2025-2029 [Dataset]. https://www.technavio.com/report/gis-market-in-the-utility-industry-analysis
    Explore at:
    Dataset updated
    Dec 31, 2024
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    Germany, Canada, United States, France, Global
    Description

    Snapshot img

    What is the GIS In Utility Industry Market Size?

    The GIS market in the utility industry size is forecast to increase by USD 3.55 billion at a CAGR of 19.8% between 2023 and 2028. Market expansion hinges on various factors, such as the rising adoption of Geographic Information System (GIS) solutions in the utility sector, the convergence of GIS with Building Information Modeling, and the fusion of Augmented Reality with GIS technology. These elements collectively drive market growth, reflecting advancements in spatial data analytics and technological convergence. The increased adoption of GIS solutions in the utility industry underscores the importance of geospatial data in optimizing infrastructure management. Simultaneously, the integration of GIS with BIM signifies the synergy between spatial and building information for enhanced project planning and management. Additionally, the integration of AR with GIS technology highlights the potential for interactive and interactive visualization experiences in spatial data analysis. Thus, the interplay of these factors delineates the landscape for the anticipated expansion of the market catering to GIS and related technologies.

    What will be the size of Market during the forecast period?

    Request Free GIS In Utility Industry Market Sample

    Market Segmentation

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

    Product
    
      Software
      Data
      Services
    
    
    Deployment
    
      On-premises
      Cloud
    
    
    Geography
    
      North America
    
        Canada
        US
    
    
      Europe
    
        Germany
        France
    
    
      APAC
    
        China
        India
        Japan
    
    
      Middle East and Africa
    
    
    
      South America
    
        Brazil
    

    Which is the largest segment driving market growth?

    The software segment is estimated to witness significant growth during the forecast period. In the utility industry, the spatial context of geographic information systems (GIS) plays a pivotal role in site selection, land acquisition, planning, designing, visualizing, building, and project management. Utilities, including electricity, gas, water, and telecommunications providers, leverage GIS software to efficiently manage their assets and infrastructure. This technology enables the collection, management, analysis, and visualization of geospatial data, derived from satellite imaging, aerial photography, remote sensors, and artificial intelligence. Geospatial AI, sensor technology, and digital reality solutions are integral components of GIS, enhancing capabilities for smart city planning, urban planning, water management, mapping systems, grid modernization, transportation, and green buildings.

    Get a glance at the market share of various regions. Download the PDF Sample

    The software segment was valued at USD 541.50 million in 2018. Moreover, the geospatial industry continues to evolve, with startups and software solutions driving innovation in hardware, smart city planning, land use management, smart infrastructure planning, and smart utilities. GIS solutions facilitate 4D visualization, enabling stakeholders to overcome geospatial data barriers and make informed decisions. The utility industry's reliance on GIS extends to building information modeling, augmented reality, and smart urban planning, ultimately contributing to the growth of the geospatial technology market.

    Which region is leading the market?

    For more insights on the market share of various regions, Request Free Sample

    North America is estimated to contribute 37% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

    How do company ranking index and market positioning come to your aid?

    Companies are implementing various strategies, such as strategic alliances, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the market.

    AABSyS IT Pvt. Ltd. - The company offers GIS solutions such as remote sensing and computer aided design and drafting solutions for electric and gas utility.

    Technavio provides the ranking index for the top 20 companies along with insights on the market positioning of:

    AABSyS IT Pvt. Ltd.
    Autodesk Inc.
    Avineon Inc.
    Bentley Systems Inc.
    Blue Marble Geographics
    Cadcorp Ltd.
    Caliper Corp.
    Environmental Systems Research Institute Inc.
    General Electric Co.
    Hexagon AB
    Mapbox Inc.
    Maxar Technologies Inc.
    Mobile GIS Services Ltd.
    NV5 Global Inc.
    Orbital Insight Inc.
    Pitney Bowes Inc.
    Schneider Electric SE
    SuperMap Software Co. Ltd.
    Trimble Inc.
    VertiGIS Ltd.
    

    Explore our company rankings and market positioning. Request Free Sample

    How can Technavio assist you in ma

  3. Land cover of Indonesia - Globcover (22 classes)

    • data.amerigeoss.org
    html, http, png, zip
    Updated Mar 14, 2023
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    Food and Agriculture Organization (2023). Land cover of Indonesia - Globcover (22 classes) [Dataset]. https://data.amerigeoss.org/dataset/f3f61bb2-78bf-4aba-a5ba-e708183336ec
    Explore at:
    html, http, png, zipAvailable download formats
    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Area covered
    Indonesia
    Description

    This land cover data set is derived from the original raster based Globcover global archive. It has been post-processed to generate a vector version at national extent with the LCCS regional legend (22 classes worldwide). The database can be analyzed in the GLCN software Advanced Database Gateway (ADG), which provides a user-friendly interface and advanced functionalities to breakdown the LCCS classes in their classifiers for further aggregations and analysis.

    The data set is intended for free public access.

    The shape file's attributes contain the following fields: -Area (sqm) -Perimeter (m) -ID -Gridcode (Globcover cell value) -LCCCode (unique LCCS code)

    You can download a zip archive containing: -the shape file (.shp) -the ArcGis layer file with global legend (.lyr) -the ArcView 3 legend file (.avl) -the LCCS legend table (.xls)

    Supplemental Information:

    This land cover product is a vector version (ESRI shape) of the Globcover archive that was published in 2008 as result of an initiative launched in 2004 by the European Space Agency (ESA). Globcover is currently the most recent (2005) and resoluted (300 m) datasets on land cover globally. Given the need of this valuable information for environmental studies, natural resources management and policy formulation, through activities of the Global Land Cover Network (GLCN) programme, the Globcover has been reprocessed to generate databases at national extent that can be analyzed through the Advanced Database Gateway software (ADG) by GLCN. ADG is a cross-cutting interrogation software that allows the easy and fast recombination of land cover polygons according to the individual end-user requirements. Aggregated land cover classes can be generated not only by name, but also using the set of existing classifiers. ADG uses land cover data with a Land Cover Classification System (LCCS) legend. The ADG software is available for download on the GLCN web site at http://www.glcn.org/sof_7_en.jsp

    Contact points:

    Metadata Contact: FAO-Data

    Resource Contact: Antonio Martucci

    Data lineage:

    This land cover database is provided as ESRI shape file (vector format) and derives from reprocessing the raster based global archive, Globcover. Globcover database has undergone the following process: a) vectoralization at the national extent using ESRI ArcGis (arcinfo) 9.3; b) topological reconstruction (custom AML scripts launched inside ArcGis-arcinfo 9.3); c) simplification of areas according to a minimum mapping unit of 0.1 skim (10 ha) (custom AML scripts launched inside ArcGis-arcinfo 9.3); application of the FAO/UNEP Land Cover Classification System (LCCS) legend (24 classes globally); final processing to assure full compatibility with the GLCN software Advanced Database Gateway (ADG).

    Online resources:

    Download Land cover of Indonesia - Shape file format

    GLOBCOVER on the ESA Web site

    Global Land Cover Network - GLCN

  4. Digital Geologic-GIS Map of Yosemite National Park and Vicinity, California...

    • catalog.data.gov
    • gimi9.com
    Updated Jun 5, 2024
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    National Park Service (2024). Digital Geologic-GIS Map of Yosemite National Park and Vicinity, California (NPS, GRD, GRI, YOSE, YOSE digital map) adapted from U.S. Geological Survey Geologic Quadrangle Maps by Bateman, Kistler, Huber, Dodge, Krauskopf, Peck and others (1965, 1966, 1968, 1971, 1980, 1985, 1987, 1989 and 2002), Miscellaneous Field Studies Maps by Huber (1983), and Bateman and Krauskopf (1987) and a Geologic Investigations Series Map by Wahrhaftig (2000), and a California Geological Survey Map Sheet map by Chesterman (1975 [Dataset]. https://catalog.data.gov/dataset/digital-geologic-gis-map-of-yosemite-national-park-and-vicinity-california-nps-grd-gri-yos
    Explore at:
    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    California
    Description

    The Digital Geologic-GIS Map of Yosemite National Park and Vicinity, California is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (yose_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (yose_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (yose_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (yose_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (yose_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (yose_geology_metadata_faq.pdf). Please read the yose_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey and California Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (yose_geology_metadata.txt or yose_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:62,500 and United States National Map Accuracy Standards features are within (horizontally) 31.8 meters or 104.2 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

  5. Land cover of Benin - Globcover Regional (46 classes)

    • data.amerigeoss.org
    html, http, png, wms +1
    Updated Mar 14, 2023
    + more versions
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    Food and Agriculture Organization (2023). Land cover of Benin - Globcover Regional (46 classes) [Dataset]. https://data.amerigeoss.org/dataset/df8d1b3f-5640-4e8e-a546-faa6ec4a02b1
    Explore at:
    wms, html, png, http, zipAvailable download formats
    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Area covered
    Benin
    Description

    This land cover data set is derived from the original raster based Globcover regional (Africa) archive. It has been post-processed to generate a vector version at national extent with the LCCS regional legend (46 classes). This database can be analyzed in the GLCN software Advanced Database Gateway (ADG), which provides a user-friendly interface and advanced functionalities to breakdown the LCCS classes in their classifiers for further aggregations and analysis.

    The data set is intended for free public access.

    The shape file's attributes contain the following fields: -Area (sqm) -ID -Gridcode (Globcover cell value) -LCCCode (unique LCCS code)

    You can download a zip archive containing: -the shape file (.shp) -the ArcGis layer file with global legend (.lyr) -the ArcView 3 legend file (.avl) -the LCCS legend tables (.xls)

    Supplemental Information:

    This land cover product is a vector version (ESRI shape) of the Globcover archive that was published in 2008 as result of an initiative launched in 2004 by the European Space Agency (ESA). Globcover is currently the most recent (2005) and resoluted (300 m) datasets on land cover globally. Given the need of this valuable information for environmental studies, natural resources management and policy formulation, through activities of the Global Land Cover Network (GLCN) programme, the Globcover has been reprocessed to generate databases at national extent that can be analyzed through the Advanced Database Gateway software (ADG) by GLCN. ADG is a cross-cutting interrogation software that allows the easy and fast recombination of land cover polygons according to the individual end-user requirements. Aggregated land cover classes can be generated not only by name, but also using the set of existing classifiers. ADG uses land cover data with a Land Cover Classification System (LCCS) legend. The ADG software is available for download on the GLCN web site at http://www.glcn.org/sof_7_en.jsp

    Contact points:

    Metadata Contact: FAO-Data

    Resource Contact: Antonio Martucci

    Data lineage:

    This land cover database is provided as ESRI shape file (vector format) and derives from reprocessing the raster based Globcover database (regional version). Globcover has undergone the following process: a) vectoralization at the national extent using ESRI ArcGis (arcinfo) 9.3; b) topological reconstruction (custom AML scripts launched inside ArcGis-arcinfo 9.3); c) simplification of areas according to a minimum mapping unit of 0.1 skim (10 ha) (custom AML scripts launched inside ArcGis-arcinfo 9.3); application of the FAO/UNEP Land Cover Classification System (LCCS) legend (46 classes); final processing to assure full compatibility with the GLCN software Advanced Database Gateway (ADG).

    Online resources:

    Download - Land cover of Benin - Shape file format

    GLOBCOVER on the ESA Web site

    Global Land Cover Network - GLCN

  6. w

    World - Terrain Elevation Above Sea Level (ELE) GIS Data, (Global Solar...

    • datacatalog.worldbank.org
    • data.subak.org
    tiff
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    https://globalsolaratlas.info/, World - Terrain Elevation Above Sea Level (ELE) GIS Data, (Global Solar Atlas) [Dataset]. https://datacatalog.worldbank.org/search/dataset/0037910
    Explore at:
    tiffAvailable download formats
    Dataset provided by
    https://globalsolaratlas.info/
    License

    https://datacatalog.worldbank.org/public-licenses?fragment=cchttps://datacatalog.worldbank.org/public-licenses?fragment=cc

    Area covered
    World
    Description

    Developed by SOLARGIS and provided by the Global Solar Atlas (GSA), this data resource contains terrain elevation above sea level (ELE) in [m a.s.l.] covering the globe. Data is provided in a geographic spatial reference (EPSG:4326). The resolution (pixel size) of solar resource data (GHI, DIF, GTI, DNI) is 9 arcsec (nominally 250 m), PVOUT and TEMP 30 arcsec (nominally 1 km) and OPTA 2 arcmin (nominally 4 km).

    The data is hyperlinked under 'resources' with the following characeristics:
    ELE - GISdata (GeoTIFF)
    Data format: GEOTIFF
    File size : 826.8 MB

    There are two temporal representation of solar resource and PVOUT data available:
    • Longterm yearly/monthly average of daily totals (LTAym_AvgDailyTotals)
    • Longterm average of yearly/monthly totals (LTAym_YearlyMonthlyTotals)

    Both type of data are equivalent, you can select the summarization of your preference. The relation between datasets is described by simple equations:
    • LTAy_YearlyTotals = LTAy_DailyTotals * 365.25
    • LTAy_MonthlyTotals = LTAy_DailyTotals * Number_of_Days_In_The_Month

    *For individual country or regional data downloads please see: https://globalsolaratlas.info/download (use the drop-down menu to select country or region of interest)
    *For data provided in AAIGrid please see: https://globalsolaratlas.info/download/world.

    For more information and terms of use, please, read metadata, provided in PDF and XML format for each data layer in a download file. For other data formats, resolution or time aggregation, please, visit Solargis website. Data can be used for visualization, further processing, and geo-analysis in all mainstream GIS software with raster data processing capabilities (such as open source QGIS, commercial ESRI ArcGIS products and others).

  7. Land cover of United Republic of Tanzania - Globcover Regional (46 classes)

    • data.amerigeoss.org
    html, http, png, wms +1
    Updated Mar 14, 2023
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    Food and Agriculture Organization (2023). Land cover of United Republic of Tanzania - Globcover Regional (46 classes) [Dataset]. https://data.amerigeoss.org/dataset/adb0b581-b530-4a06-8a86-ed562ddc63b6
    Explore at:
    zip, png, html, http, wmsAvailable download formats
    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Area covered
    Tanzania
    Description

    This land cover data set is derived from the original raster based Globcover regional (Africa) archive. It has been post-processed to generate a vector version at national extent with the LCCS regional legend (46 classes). This database can be analyzed in the GLCN software Advanced Database Gateway (ADG), which provides a user-friendly interface and advanced functionalities to breakdown the LCCS classes in their classifiers for further aggregations and analysis.

    The data set is intended for free public access.

    The shape file's attributes contain the following fields: -Area (sqm) -ID -Gridcode (Globcover cell value) -LCCCode (unique LCCS code)

    You can download a zip archive containing: -the shape file (.shp) -the ArcGis layer file with global legend (.lyr) -the ArcView 3 legend file (.avl) -the LCCS legend tables (.xls)

    Supplemental Information:

    This land cover product is a vector version (ESRI shape) of the Globcover archive that was published in 2008 as result of an initiative launched in 2004 by the European Space Agency (ESA). Globcover is currently the most recent (2005) and resoluted (300 m) datasets on land cover globally. Given the need of this valuable information for environmental studies, natural resources management and policy formulation, through activities of the Global Land Cover Network (GLCN) programme, the Globcover has been reprocessed to generate databases at national extent that can be analyzed through the Advanced Database Gateway software (ADG) by GLCN. ADG is a cross-cutting interrogation software that allows the easy and fast recombination of land cover polygons according to the individual end-user requirements. Aggregated land cover classes can be generated not only by name, but also using the set of existing classifiers. ADG uses land cover data with a Land Cover Classification System (LCCS) legend. The ADG software is available for download on the GLCN web site at http://www.glcn.org/sof_7_en.jsp

    Contact points:

    Metadata Contact: FAO-Data

    Resource Contact: Antonio Martucci

    Data lineage:

    This land cover database is provided as ESRI shape file (vector format) and derives from reprocessing the raster based Globcover database (regional version). Globcover has undergone the following process: a) vectoralization at the national extent using ESRI ArcGis (arcinfo) 9.3; b) topological reconstruction (custom AML scripts launched inside ArcGis-arcinfo 9.3); c) simplification of areas according to a minimum mapping unit of 0.1 skim (10 ha) (custom AML scripts launched inside ArcGis-arcinfo 9.3); application of the FAO/UNEP Land Cover Classification System (LCCS) legend (46 classes); final processing to assure full compatibility with the GLCN software Advanced Database Gateway (ADG).

    Online resources:

    Download - Land cover of United Republic of Tanzania - Shape file format

    GLOBCOVER on the ESA Web site

    Global Land Cover Network - GLCN

  8. Land cover of Mozambique - Globcover Regional (46 classes)

    • data.amerigeoss.org
    html, http, png, wms +1
    Updated Mar 14, 2023
    + more versions
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    Food and Agriculture Organization (2023). Land cover of Mozambique - Globcover Regional (46 classes) [Dataset]. https://data.amerigeoss.org/it/dataset/e58eada2-046a-4277-a812-5c11762ed902
    Explore at:
    wms, http, html, png, zipAvailable download formats
    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Area covered
    Mozambique
    Description

    This land cover data set is derived from the original raster based Globcover regional (Africa) archive. It has been post-processed to generate a vector version at national extent with the LCCS regional legend (46 classes). This database can be analyzed in the GLCN software Advanced Database Gateway (ADG), which provides a user-friendly interface and advanced functionalities to breakdown the LCCS classes in their classifiers for further aggregations and analysis.

    The data set is intended for free public access.

    The shape file's attributes contain the following fields: -Area (sqm) -ID -Gridcode (Globcover cell value) -LCCCode (unique LCCS code)

    You can download a zip archive containing: -the shape file (.shp) -the ArcGis layer file with global legend (.lyr) -the ArcView 3 legend file (.avl) -the LCCS legend tables (.xls)

    Supplemental Information:

    This land cover product is a vector version (ESRI shape) of the Globcover archive that was published in 2008 as result of an initiative launched in 2004 by the European Space Agency (ESA). Globcover is currently the most recent (2005) and resoluted (300 m) datasets on land cover globally. Given the need of this valuable information for environmental studies, natural resources management and policy formulation, through activities of the Global Land Cover Network (GLCN) programme, the Globcover has been reprocessed to generate databases at national extent that can be analyzed through the Advanced Database Gateway software (ADG) by GLCN. ADG is a cross-cutting interrogation software that allows the easy and fast recombination of land cover polygons according to the individual end-user requirements. Aggregated land cover classes can be generated not only by name, but also using the set of existing classifiers. ADG uses land cover data with a Land Cover Classification System (LCCS) legend. The ADG software is available for download on the GLCN web site at http://www.glcn.org/sof_7_en.jsp

    Contact points:

    Metadata Contact: FAO-Data

    Resource Contact: Antonio Martucci

    Data lineage:

    This land cover database is provided as ESRI shape file (vector format) and derives from reprocessing the raster based Globcover database (regional version). Globcover has undergone the following process: a) vectoralization at the national extent using ESRI ArcGis (arcinfo) 9.3; b) topological reconstruction (custom AML scripts launched inside ArcGis-arcinfo 9.3); c) simplification of areas according to a minimum mapping unit of 0.1 skim (10 ha) (custom AML scripts launched inside ArcGis-arcinfo 9.3); application of the FAO/UNEP Land Cover Classification System (LCCS) legend (46 classes); final processing to assure full compatibility with the GLCN software Advanced Database Gateway (ADG).

    Online resources:

    Download - Land cover of Mozambique - Shape file format

    GLOBCOVER on the ESA Web site

    Global Land Cover Network - GLCN

  9. Address Point Rooftop Data

    • caliper.com
    cdf, dwg, dxf, gdb +9
    Updated Nov 17, 2020
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    Caliper Corporation (2020). Address Point Rooftop Data [Dataset]. https://www.caliper.com/mapping-software-data/address-point-data.htm
    Explore at:
    sql server mssql, kml, shp, postgresql, cdf, postgis, gdb, sdo, ntf, kmz, geojson, dwg, dxfAvailable download formats
    Dataset updated
    Nov 17, 2020
    Dataset authored and provided by
    Caliper Corporationhttp://www.caliper.com/
    License

    https://www.caliper.com/license/maptitude-license-agreement.htmhttps://www.caliper.com/license/maptitude-license-agreement.htm

    Time period covered
    2020
    Area covered
    United States
    Description

    Address point data for use with GIS mapping software, databases, and web applications are from Caliper Corporation and contain a point layer of over 48 million addresses in 22 states and the District of Columbia.

  10. Land cover of Liberia - Globcover Regional (46 classes)

    • data.amerigeoss.org
    html, http, png, wms +1
    Updated Mar 14, 2023
    + more versions
    Share
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    Food and Agriculture Organization (2023). Land cover of Liberia - Globcover Regional (46 classes) [Dataset]. https://data.amerigeoss.org/dataset/68f12101-c75a-45d0-9d85-5bb49859040d
    Explore at:
    zip, http, wms, html, pngAvailable download formats
    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Area covered
    Liberia
    Description

    This land cover data set is derived from the original raster based Globcover regional (Africa) archive. It has been post-processed to generate a vector version at national extent with the LCCS regional legend (46 classes). This database can be analyzed in the GLCN software Advanced Database Gateway (ADG), which provides a user-friendly interface and advanced functionalities to breakdown the LCCS classes in their classifiers for further aggregations and analysis.

    The data set is intended for free public access.

    The shape file's attributes contain the following fields: -Area (sqm) -ID -Gridcode (Globcover cell value) -LCCCode (unique LCCS code)

    You can download a zip archive containing: -the shape file (.shp) -the ArcGis layer file with global legend (.lyr) -the ArcView 3 legend file (.avl) -the LCCS legend tables (.xls)

    Supplemental Information:

    This land cover product is a vector version (ESRI shape) of the Globcover archive that was published in 2008 as result of an initiative launched in 2004 by the European Space Agency (ESA). Globcover is currently the most recent (2005) and resoluted (300 m) datasets on land cover globally. Given the need of this valuable information for environmental studies, natural resources management and policy formulation, through activities of the Global Land Cover Network (GLCN) programme, the Globcover has been reprocessed to generate databases at national extent that can be analyzed through the Advanced Database Gateway software (ADG) by GLCN. ADG is a cross-cutting interrogation software that allows the easy and fast recombination of land cover polygons according to the individual end-user requirements. Aggregated land cover classes can be generated not only by name, but also using the set of existing classifiers. ADG uses land cover data with a Land Cover Classification System (LCCS) legend. The ADG software is available for download on the GLCN web site at http://www.glcn.org/sof_7_en.jsp

    Contact points:

    Metadata Contact: FAO-Data

    Resource Contact: Antonio Martucci

    Data lineage:

    This land cover database is provided as ESRI shape file (vector format) and derives from reprocessing the raster based Globcover database (regional version). Globcover has undergone the following process: a) vectoralization at the national extent using ESRI ArcGis (arcinfo) 9.3; b) topological reconstruction (custom AML scripts launched inside ArcGis-arcinfo 9.3); c) simplification of areas according to a minimum mapping unit of 0.1 skim (10 ha) (custom AML scripts launched inside ArcGis-arcinfo 9.3); application of the FAO/UNEP Land Cover Classification System (LCCS) legend (46 classes); final processing to assure full compatibility with the GLCN software Advanced Database Gateway (ADG).

    Online resources:

    Download - Land cover of Liberia - Shape file format

    GLOBCOVER on the ESA Web site

    Global Land Cover Network - GLCN

  11. GEODATA TOPO 250K Series 3 (Google Earth format)

    • ecat.ga.gov.au
    • researchdata.edu.au
    Updated Jan 1, 2007
    + more versions
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    Commonwealth of Australia (Geoscience Australia) (2007). GEODATA TOPO 250K Series 3 (Google Earth format) [Dataset]. https://ecat.ga.gov.au/geonetwork/srv/api/records/a05f7892-cfc7-7506-e044-00144fdd4fa6
    Explore at:
    www:link-1.0-http--linkAvailable download formats
    Dataset updated
    Jan 1, 2007
    Dataset provided by
    Geoscience Australiahttp://ga.gov.au/
    Area covered
    Description

    PLEASE NOTE: These data do not include data over Tasmania. Please see links relevant to that area.

    GEODATA TOPO 250K Series 3 is a vector representation of the major topographic features appearing on the 1:250,000 scale NATMAPs supplied in KML format and is designed for use in a range of commercial GIS software. Data is arranged within specific themes. All data is based on the GDA94 coordinate system.

    GEODATA TOPO 250K Series 3 is available as a free download product in Personal Geodatabase, ArcView Shapefile or MapInfo TAB file formats. Each package includes data arranged in ten main themes - cartography, elevation, framework, habitation, hydrography, infrastructure, terrain, transport, utility and vegetation. Data is also available as GEODATA TOPO 250K Series 3 for Google Earth in kml format for use on Google Earth TM Mapping Service.

    Product Specifications

    Themes: Cartography, Elevation, Framework, Habitation, Hydrography, Infrastructure, Terrain, Transport, Utility and Vegetation

    Coverage: National (Powerlines not available in South Australia)

    Currency: Data has a currency of less than five years for any location

    Coordinates: Geographical

    Datum: Geocentric Datum of Australia (GDA94)

    Formats: Personal Geodatabase, kml, Shapefile and MapInfo TAB

    Release Date: 26 June 2006

  12. d

    USGS Imagery Only Base Map Service from The National Map.

    • datadiscoverystudio.org
    • data.wu.ac.at
    xml
    Updated Feb 8, 2018
    + more versions
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    (2018). USGS Imagery Only Base Map Service from The National Map. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/c02a45986160400ca5bc3a71cb554a7f/html
    Explore at:
    xmlAvailable download formats
    Dataset updated
    Feb 8, 2018
    Description

    description: USGS Imagery Only is a tile cache base map of orthoimagery in The National Map visible to the 1:18,000 scale. Orthoimagery data are typically high resolution images that combine the visual attributes of an aerial photograph with the spatial accuracy and reliability of a planimetric map. USGS digital orthoimage resolution may vary from 6 inches to 1 meter. In the former resolution, every pixel in an orthoimage covers a six inch square of the earth's surface, while in the latter resolution, one meter square is represented by each pixel. Blue Marble: Next Generation source is displayed at small to medium scales. However, the majority of the imagery service source is from the National Agriculture Imagery Program (NAIP) for the conterminous United States. The data is 1-meter pixel resolution with "leaf-on". Collection of NAIP imagery is administered by the U.S. Department of Agriculture's Farm Service Agency (FSA). In areas where NAIP data is not available, other imagery may be acquired through partnerships by the USGS. The National Map program is working on acquisition of high resolution orthoimagery (HRO) for Alaska and Hawaii. Most of the new Alaska imagery data will not be available in this service due to license restrictions. The National Map viewer allows free downloads of public domain, 1-meter resolution orthoimagery in JPEG 2000 (jp2) format for the conterminous United States, with many urban areas and other locations at 1-foot (or better) resolution also in JPEG 2000 (jp2) format. For scales below 1:18,000, use the dynamic USGS Imagery Only Large service, https://services.nationalmap.gov/arcgis/rest/services/USGSImageOnlyLarge/MapServer.; abstract: USGS Imagery Only is a tile cache base map of orthoimagery in The National Map visible to the 1:18,000 scale. Orthoimagery data are typically high resolution images that combine the visual attributes of an aerial photograph with the spatial accuracy and reliability of a planimetric map. USGS digital orthoimage resolution may vary from 6 inches to 1 meter. In the former resolution, every pixel in an orthoimage covers a six inch square of the earth's surface, while in the latter resolution, one meter square is represented by each pixel. Blue Marble: Next Generation source is displayed at small to medium scales. However, the majority of the imagery service source is from the National Agriculture Imagery Program (NAIP) for the conterminous United States. The data is 1-meter pixel resolution with "leaf-on". Collection of NAIP imagery is administered by the U.S. Department of Agriculture's Farm Service Agency (FSA). In areas where NAIP data is not available, other imagery may be acquired through partnerships by the USGS. The National Map program is working on acquisition of high resolution orthoimagery (HRO) for Alaska and Hawaii. Most of the new Alaska imagery data will not be available in this service due to license restrictions. The National Map viewer allows free downloads of public domain, 1-meter resolution orthoimagery in JPEG 2000 (jp2) format for the conterminous United States, with many urban areas and other locations at 1-foot (or better) resolution also in JPEG 2000 (jp2) format. For scales below 1:18,000, use the dynamic USGS Imagery Only Large service, https://services.nationalmap.gov/arcgis/rest/services/USGSImageOnlyLarge/MapServer.

  13. Digital Geologic-GIS Map of Gettysburg National Military Park, Pennsylvania...

    • catalog.data.gov
    Updated Jun 5, 2024
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    National Park Service (2024). Digital Geologic-GIS Map of Gettysburg National Military Park, Pennsylvania (NPS, GRD, GRI, EISE, GETT, GETT digital map) adapted from U.S. Geological Survey Geologic Atlas of the United States Folio maps by Stose and Bascom (1929) [Dataset]. https://catalog.data.gov/dataset/digital-geologic-gis-map-of-gettysburg-national-military-park-pennsylvania-nps-grd-gri-eis
    Explore at:
    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    Pennsylvania, United States, Gettysburg
    Description

    The Digital Geologic-GIS Map of Gettysburg National Military Park, Pennsylvania is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (gett_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (gett_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (gett_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (gett_eise_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (gett_eise_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (gett_geology_metadata_faq.pdf). Please read the gett_eise_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (gett_geology_metadata.txt or gett_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:62,500 and United States National Map Accuracy Standards features are within (horizontally) 31.8 meters or 104.2 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

  14. G

    Rail Network

    • find.data.gov.scot
    • dtechtive.com
    geojson
    + more versions
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    Glasgow City Council (uSmart), Rail Network [Dataset]. https://find.data.gov.scot/datasets/39592
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    geojson(0.0174 MB), geojson(0.1965 MB)Available download formats
    Dataset provided by
    Glasgow City Council (uSmart)
    Description
  15. a

    Earth Explorer

    • hub.arcgis.com
    • amerigeo.org
    • +6more
    Updated Nov 9, 2018
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    AmeriGEOSS (2018). Earth Explorer [Dataset]. https://hub.arcgis.com/items/21a227e6c315488492d8f0a924cd487e
    Explore at:
    Dataset updated
    Nov 9, 2018
    Dataset authored and provided by
    AmeriGEOSS
    Description

    EarthExplorerUse the USGS EarthExplorer (EE) to search, download, and order satellite images, aerial photographs, and cartographic products. In addition to data from the Landsat missions and a variety of other data providers, EE provides access to MODIS land data products from the NASA Terra and Aqua missions, and ASTER level-1B data products over the U.S. and Territories from the NASA ASTER mission. Registered users of EE have access to more features than guest users.Earth Explorer Distribution DownloadThe EarthExplorer user interface is an online search, discovery, and ordering tool developed by the United States Geological Survey (USGS). EarthExplorer supports the searching of satellite, aircraft, and other remote sensing inventories through interactive and textual-based query capabilities. Through the interface, users can identify search areas, datasets, and display metadata, browse and integrated visual services within the interface.The distributable version of EarthExplorer provides the basic software to provide this functionality. Users are responsible for verification of system recommendations for hosting the application on your own servers. By default, this version of our code is not hooked up to a data source so you will have to integrate the interface with your data. Integration options include service-based API's, databases, and anything else that stores data. To integrate with a data source simply replace the contents of the 'getDataset' and 'search' functions in the CWIC.php file.Distribution is being provided due to users requests for the codebase. The EarthExplorer source code is provided "As Is", without a warranty or support of any kind. The software is in the public domain; it is available to any government or private institution.The software code base is managed through the USGS Configuration Management Board. The software is managed through an automated configuration management tool that updates the code base when new major releases have been thoroughly reviewed and tested.Link: https://earthexplorer.usgs.gov/

  16. m

    Queensland geology and structural framework - GIS data July 2012

    • demo.dev.magda.io
    • researchdata.edu.au
    • +2more
    zip
    Updated Apr 13, 2022
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    Bioregional Assessment Program (2022). Queensland geology and structural framework - GIS data July 2012 [Dataset]. https://demo.dev.magda.io/dataset/ds-dga-32ede73f-85f8-4053-acf1-bf72265dd539
    Explore at:
    zipAvailable download formats
    Dataset updated
    Apr 13, 2022
    Dataset provided by
    Bioregional Assessment Program
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Area covered
    Queensland
    Description

    Abstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. This dataset was sourced from the Queensland Department of Natural Resources and Mines in 2012. Information provided by the Department describes the dataset as follows: This data was originally provided on DVD and contains the converted shapefiles, layer files, raster images and project .mxd files used on the Queensland geology …Show full descriptionAbstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. This dataset was sourced from the Queensland Department of Natural Resources and Mines in 2012. Information provided by the Department describes the dataset as follows: This data was originally provided on DVD and contains the converted shapefiles, layer files, raster images and project .mxd files used on the Queensland geology and structural framework map. The maps were done in ArcGIS 9.3.1 and the data stored in file geodatabases, topology created and validated. This provides greater data quality by performing topological validation on the feature's spatial relationships. For the purposes of the DVD, shapefiles were created from the file geodatabases and for MapInfo users MapInfo .tab and .wor files. The shapefiles on the DVD are a revision of the 1975 Queensland geology data, and are both are available for display, query and download on the department's online GIS application. The Queensland geology map is a digital representation of the distribution or extent of geological units within Queensland. In the GIS, polygons have a range of attributes including unit name, type of unit, age, lithological description, dominant rock type, and an abbreviated symbol for use in labelling the polygons. The lines in this dataset are a digital representation of the position of the boundaries of geological units and other linear features such as faults and folds. The lines are attributed with a description of the type of line represented. Approximately 2000 rock units were grouped into the 250 map units in this data set. The digital data was generalised and simplified from the Department's detailed geological data and was captured at 1:500 000 scale for output at 1:2 000 000 scale. In the ESRI version, a layer file is provided which presents the units in the colours and patterns used on the printed hard copy map. For Map Info users, a simplified colour palette is provided without patterns. However a georeferenced image of the hard copy map is included and can be displayed as a background in both Arc Map and Map Info. The geological framework of Queensland is classified by structural or tectonic unit (provinces and basins) in which the rocks formed. These are referred to as basins (or in some cases troughs and depressions) where the original form and structure are still apparent. Provinces (and subprovinces) are generally older basins that have been strongly tectonised and/or metamorphosed so that the original basin extent and form are no longer preserved. Note that intrusive and some related volcanic rocks that overlap these provinces and basins have not been included in this classification. The map was compiled using boundaries modified and generalised from the 1:2 000 000 Queensland Geology map (2012). Outlines of subsurface basins are also shown and these are based on data and published interpretations from petroleum exploration and geophysical surveys (seismic, gravity and magnetics). For the structural framework dataset, two versions are provided. In QLD_STRUCTURAL_FRAMEWORK, polygons are tagged with the name of the surface structural unit, and names of underlying units are imbedded in a text string in the HIERARCHY field. In QLD_STRUCTURAL_FRAMEWORK_MULTI_POLYS, the data is structured into a series of overlapping, multi-part polygons, one for each structural unit. Two layer files are provided with the ESRI data, one where units are symbolised by name. Because the dataset has been designed for units display in the order of superposition, this layer file assigns colours to the units that occur at the surface with concealed units being left uncoloured. Another layer file symbolises them by the orogen of which they are part. A similar set of palettes has been provided for Map Info. Dataset History Details on the source data can be found in the xml file associated with data layer. Data in this release *ESRI.shp and MapInfo .tab files of rock unit polygons and lines with associated layer attributes of Queensland geology *ESRI.shp and MapInfo .tab files of structural unit polygons and lines with associated layer attributes of structural framework *ArcMap .mxd and .lyr files and MapInfo .wor files containing symbology *Georeferenced Queensland geology map, gravity and magnetic images *Queensland geology map, structural framework and schematic diagram PDF files *Data supplied in geographical coordinates (latitude/longitude) based on Geocentric Datum of Australia - GDA94 Accessing the data Programs exist for the viewing and manipulation of the digital spatial data contained on this DVD. Accessing the digital datasets will require GIS software. The following GIS viewers can be downloaded from the internet. ESRI ArcExplorer can be found by a search of www.esriaustralia.com.au and MapInfo ProViewer by a search on www.pbinsight.com.au collectively ("the websites"). Metadata Metadata is contained in .htm files placed in the root folder of each vector data folder. For ArcMap users metadata for viewing in ArcCatalog is held in an .xml file with each shapefile within the ESRI Shapefile folders. Disclaimer The State of Queensland is not responsible for the privacy practices or the content of the websites and makes no statements, representations, or warranties about the content or accuracy or completeness of, any information or products contained on the websites. Despite our best efforts, the State of Queensland makes no warranties that the information or products available on the websites are free from infection by computer viruses or other contamination. The State of Queensland disclaims all responsibility and all liability (including without limitation, liability in negligence) for all expenses, losses, damages and costs you might incur as a result of accessing the websites or using the products available on the websites in any way, and for any reason. The State of Queensland has included the websites in this document as an information source only. The State of Queensland does not promote or endorse the websites or the programs contained on them in any way. WARNING: The Queensland Government and the Department of Natural Resources and Mines accept no liability for and give no undertakings, guarantees or warranties concerning the accuracy, completeness or fitness for the purposes of the information provided. The consumer must take all responsible steps to protect the data from unauthorised use, reproduction, distribution or publication by other parties. Please view the 'readme.html' and 'licence.html' file for further, more complete information Dataset Citation Geological Survey of Queensland (2012) Queensland geology and structural framework - GIS data July 2012. Bioregional Assessment Source Dataset. Viewed 07 December 2018, http://data.bioregionalassessments.gov.au/dataset/69da6301-04c1-4993-93c1-4673f3e22762.

  17. Digital Geologic-GIS Map of the Yellowstone National Park and Vicinity,...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Jun 5, 2024
    + more versions
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    National Park Service (2024). Digital Geologic-GIS Map of the Yellowstone National Park and Vicinity, Wyoming, Montana and Idaho (NPS, GRD, GRI, YELL, YELL digital map) adapted from U.S. Geological Survey maps by Christiansen, Blank, Prostka, Smedes, Pierce, the U.S. Geological Survey, Elliot, Nelson, Wahl, Witkind, Love and others (1956 to 2007), and a Montana Bureau of Mines and Geology map by Berg, Lonn and Locke (1999) [Dataset]. https://catalog.data.gov/dataset/digital-geologic-gis-map-of-the-yellowstone-national-park-and-vicinity-wyoming-montana-and
    Explore at:
    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    Montana, Wyoming
    Description

    The Digital Geologic-GIS Map of the Yellowstone National Park and Vicinity, Wyoming, Montana and Idaho is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (yell_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (yell_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (yell_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) this file (yell_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (yell_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (yell_geology_metadata_faq.pdf). Please read the yell_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey and Montana Bureau of Mines and Geology. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (yell_geology_metadata.txt or yell_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:62,500 and United States National Map Accuracy Standards features are within (horizontally) 63.5 meters or 208.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

  18. d

    Parks - Facilities & Features - Shapefiles

    • catalog.data.gov
    • data.cityofchicago.org
    • +4more
    Updated Dec 16, 2023
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    data.cityofchicago.org (2023). Parks - Facilities & Features - Shapefiles [Dataset]. https://catalog.data.gov/dataset/parks-facilities-features-shapefiles
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    Dataset updated
    Dec 16, 2023
    Dataset provided by
    data.cityofchicago.org
    Description

    Facilities and features in Chicago parks. For more information, visit http://www.chicagoparkdistrict.com/facilities/search/. To view or use these shapefiles, compression software and special GIS software, such as ESRI ArcGIS or QGIS, is required. To download this file, right-click the "Download" link above and choose "Save link as."

  19. a

    Address Ranges

    • disasters-geoplatform.hub.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +3more
    Updated Aug 30, 2024
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    GeoPlatform ArcGIS Online (2024). Address Ranges [Dataset]. https://disasters-geoplatform.hub.arcgis.com/datasets/address-ranges-2024
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    Dataset updated
    Aug 30, 2024
    Dataset authored and provided by
    GeoPlatform ArcGIS Online
    Description

    Address ranges describe a label given to a unique collection of addresses that fall along a road or path. Address ranges provide a way of locating homes and businesses based on their street addresses when no other location information is available.Using a house number, street name, street side and ZIP code, address ranges can locate the address to the geographic area associated to that side of the street. Once geocoded, the U.S. Census Bureau can assign the address to a field assignment area or tabulate the data for that address. In addition, academics, researchers, professionals and government agencies outside of the Census Bureau use MAF/TIGER address ranges to transform tabular addresses into geographical datasets for decision-making and analytical purposes.Address ranges must be unique to geocode addresses to the correct location and avoid geocoding conflicts. Multiple elements in MAF/TIGER are required to make an address range unique including street names, address house numbers and street feature geometries, such as street centerlines. The address range data model is designed to maximize geocoding matches with their correct geographic areas in MAF/TIGER by allowing an unlimited number of address range-to-street feature relationships.The Census Bureau’s Geography Division devises numerous operations and processes to build and maintain high quality address ranges so that:Address ranges accurately describe the location of addresses on the ground.Address All possible city-style addresses are geocoded.Address ranges can handle all known address and street name variations.Address ranges conform with current U.S. Postal Service ZIP codes.Address ranges are reliable and free from conflicts.Automated software continually updates existing address ranges, builds new address ranges and corrects errors. An automated operation links address location points and tabular address information to street feature edges with matching street names in the same block to build and modify address ranges.Many business rules and legal value checks ensure quality address range data in MAF/TIGER. For example, business rules prevent adding or modifying address ranges that overlap another house number range with the same street name and ZIP code. Legal value checks verify that address ranges include mandatory attribute information, valid data types and valid character values.Some of the TIGER/Line products for the public include address ranges and give the public the ability to geocode addresses to MAF/TIGER address ranges for the user’s own purpose. The address range files are available for the nation, Puerto Rico and the U.S. Island Areas at the county level. TIGER/Line files require geographic information system (GIS) software to use.The Census Bureau Geocoder Service is a web service provided to the public. The service accepts up to 1,000 input addresses and, based on Census address ranges, returns the interpolated geocoded location and census geographies. Users can access the service a web interface or a representational state transfer (REST) application program interface (API) web service.Download: https://www2.census.gov/geo/tiger/TGRGDB24/tlgdb_2024_a_us_addr.gdb.zip

  20. d

    West Africa Land Use Land Cover Time Series

    • catalog.data.gov
    • data.usgs.gov
    Updated Jul 6, 2024
    + more versions
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    U.S. Geological Survey (2024). West Africa Land Use Land Cover Time Series [Dataset]. https://catalog.data.gov/dataset/west-africa-land-use-land-cover-time-series
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Africa, West Africa
    Description

    This series of three-period land use land cover (LULC) datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources (exception is Tchad at 4 kilometers). To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate the photo-interpretation using Esri’s ArcGIS Desktop ArcMap software. Citation: Trochain, J.-L., 1957, Accord interafricain sur la définition des types de végétation de l’Afrique tropicale: Institut d’études centrafricaines.

  21. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Eaton County Michigan (2018). QGIS - Open Source GIS Software [Dataset]. https://hub.arcgis.com/documents/57198670f4234919bfab87fb64d40a82

QGIS - Open Source GIS Software

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29 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Aug 9, 2018
Dataset authored and provided by
Eaton County Michigan
Description

This is a link to the QGIS website where you can download open-source GIS software for viewing, analyzing and manipulating geodata like our downloadable shapefiles.

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