81 datasets found
  1. a

    QGIS - Open Source GIS Software

    • hub.arcgis.com
    • home-ecgis.hub.arcgis.com
    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. a

    OpenStreetMap

    • ethiopia.africageoportal.com
    • data.baltimorecity.gov
    • +33more
    Updated May 19, 2020
    + more versions
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    Africa GeoPortal (2020). OpenStreetMap [Dataset]. https://ethiopia.africageoportal.com/maps/a5511fbe18ce46788b78adbcba13bc1e
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    Dataset updated
    May 19, 2020
    Dataset authored and provided by
    Africa GeoPortal
    Area covered
    Description

    This web map references the live tiled map service from the OpenStreetMap project. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information such as free satellite imagery, and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap server: http://www.OpenStreetMap.org. See that website for additional information about OpenStreetMap. It is made available as a basemap for GIS work in Esri products under a Creative Commons Attribution-ShareAlike license.Tip: This service is one of the basemaps used in the ArcGIS.com map viewer and ArcGIS Explorer Online. Simply click one of those links to launch the interactive application of your choice, and then choose Open Street Map from the Basemap control to start using this service. You'll also find this service in the Basemap gallery in ArcGIS Explorer Desktop and ArcGIS Desktop 10.

  3. U

    ArcGIS Desktop 10.8.2

    • dataverse.ucla.edu
    exe
    Updated Oct 24, 2022
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    ZHIYUAN YAO; ZHIYUAN YAO (2022). ArcGIS Desktop 10.8.2 [Dataset]. http://doi.org/10.25346/S6/UMGDRS
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    exe(1111667672)Available download formats
    Dataset updated
    Oct 24, 2022
    Dataset provided by
    UCLA Dataverse
    Authors
    ZHIYUAN YAO; ZHIYUAN YAO
    License

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

    Description

    ArcGIS Desktop 10.8.2. This is just a software. If you need a license, please send a request to Software Central (softwarecentral@ucla.edu).

  4. M

    DNR Toolbox for ArcGIS 10

    • gisdata.mn.gov
    • data.wu.ac.at
    esri_toolbox
    Updated May 25, 2024
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    DNR Toolbox for ArcGIS 10 [Dataset]. https://gisdata.mn.gov/dataset/dnr-arcgis-toolbox
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    esri_toolboxAvailable download formats
    Dataset updated
    May 25, 2024
    Dataset provided by
    Natural Resources Department
    Description

    The Minnesota DNR Toolbox and Hydro Tools provide a number of convenience geoprocessing tools used regularly by MNDNR staff. Many of these may be useful to the wider public. However, some tools may rely on data that is not available outside of the DNR. All tools require at least ArcGIS 10+.

    If you create a GDRS using GDRS Manager and include this toolbox resource and MNDNR Quick Layers, the DNR toolboxes will automatically be added to the ArcToolbox window whenever Quick Layers GDRS Location is set to the GDRS location that has the toolboxes.

    Toolsets included in MNDNR Tools V10:
    - Analysis Tools
    - Conversion Tools
    - Division Tools
    - General Tools
    - Hydrology Tools
    - LiDAR and DEM Tools
    - Raster Tools
    - Sampling Tools

    These toolboxes are provided free of charge and are not warrantied for any specific use. We do not provide support or assistance in downloading or using these tools. We do, however, strive to produce high-quality tools and appreciate comments you have about them.

  5. a

    USNG Map Book Template for ArcGIS Pro

    • hub.arcgis.com
    • gis-fema.hub.arcgis.com
    Updated May 25, 2018
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    NAPSG Foundation (2018). USNG Map Book Template for ArcGIS Pro [Dataset]. https://hub.arcgis.com/content/f93ebd6933cb4679a62ce4f71a2a9615
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    Dataset updated
    May 25, 2018
    Dataset authored and provided by
    NAPSG Foundation
    License

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

    Description

    Contents: This is an ArcGIS Pro zip file that you can download and use for creating map books based on United States National Grid (USNG). It contains a geodatabase, layouts, and tasks designed to teach you how to create a basic map book.Version 1.0.0 Uploaded on May 24th and created with ArcGIS Pro 2.1.3 - Please see the README below before getting started!Updated to 1.1.0 on August 20thUpdated to 1.2.0 on September 7thUpdated to 2.0.0 on October 12thUpdate to 2.1.0 on December 29thBack to 1.2.0 due to breaking changes in the templateBack to 1.0.0 due to breaking changes in the template as of June 11th 2019Updated to 2.1.1 on October 8th 2019Audience: GIS Professionals and new users of ArcGIS Pro who support Public Safety agencies with map books. If you are looking for apps that can be used by any public safety professional, see the USNG Lookup Viewer.Purpose: To teach you how to make a map book with critical infrastructure and a basemap, based on USNG. You NEED to follow the steps in the task and not try to take shortcuts the first time you use this task in order to receive the full benefits. Background: This ArcGIS Pro template is meant to be a starting point for your map book projects and is based on best practices by the USNG National Implementation Center (TUNIC) at Delta State University and is hosted by the NAPSG Foundation. This does not replace previous templates created in ArcMap, but is a new experimental approach to making map books. We will continue to refine this template and work with other organizations to make improvements over time. So please send us your feedback admin@publicsafetygis.org and comments below. Instructions: Download the zip file by clicking on the thumbnail or the Download button.Unzip the file to an appropriate location on your computer (C:\Users\YourUsername\Documents\ArcGIS\Projects is a common location for ArcGIS Pro Projects).Open the USNG Map book Project File (APRX).If the Task is not already open by default, navigate to Catalog > Tasks > and open 'Create a US National Grid Map Book' Follow the instructions! This task will have some automated processes and models that run in the background but you should pay close attention to the instructions so you also learn all of the steps. This will allow you to innovate and customize the template for your own use.FAQsWhat is US National Grid? The US National Grid (USNG) is a point and area reference system that provides for actionable location information in a uniform format. Its use helps achieve consistent situational awareness across all levels of government, disciplines, and threats & hazards – regardless of your role in an incident.One of the key resources NAPSG makes available to support emergency responders is a basic USNG situational awareness application. See the NAPSG Foundation and USNG Center websites for more information.What is an ArcGIS Pro Task? A task is a set of preconfigured steps that guide you and others through a workflow or business process. A task can be used to implement a best-practice workflow, improve the efficiency of a workflow, or create a series of interactive tutorial steps. See "What is a Task?" for more information.Do I need to be proficient in ArcGIS Pro to use this template? We feel that this is a good starting point if you have already taken the ArcGIS Pro QuickStart Tutorials. While the task will automate many steps, you will want to get comfortable with the map layouts and other new features in ArcGIS Pro.Is this template free? This resources is provided at no-cost, but also with no guarantees of quality assurance or support at this time. Can't I just use ArcMap? Ok - here you go. USNG 1:24K Map Template for ArcMapKnown Limitations and BugsZoom To: It appears there may be a bug or limitation with automatically zooming the map to the proper extent, so get comfortable with navigation or zoom to feature via the attribute table.FGDC Compliance: We are seeking feedback from experts in the field to make sure that this meets minimum requirements. At this point in time we do not claim to have any official endorsement of standardization. File Size: Highly detailed basemaps can really add up and contribute to your overall file size, especially over a large area / many pages. Consider making a simple "Basemap" of street centerlines and building footprints.We will do the best we can to address limitations and are very open to feedback!

  6. a

    GIS Data Download

    • carlton-county-gis-data-hub-carltoncounty.hub.arcgis.com
    Updated Feb 18, 2017
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    GIS Data Download [Dataset]. https://carlton-county-gis-data-hub-carltoncounty.hub.arcgis.com/datasets/gis-data-download
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    Dataset updated
    Feb 18, 2017
    Dataset authored and provided by
    Carlton County, MN
    Description

    Link to Carlton County's Open & Free GIS Portal

  7. M

    Status of Free and Open Public Geospatial Data from Minnesota Counties

    • gisdata.mn.gov
    • data.wu.ac.at
    fgdb, gpkg, html +3
    Updated Apr 24, 2025
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    Geospatial Information Office (2025). Status of Free and Open Public Geospatial Data from Minnesota Counties [Dataset]. https://gisdata.mn.gov/dataset/bdry-mn-county-open-data-status
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    printable_map, jpeg, fgdb, html, shp, gpkgAvailable download formats
    Dataset updated
    Apr 24, 2025
    Dataset provided by
    Geospatial Information Office
    Area covered
    Minnesota
    Description

    This map shows the free and open data status of county public geospatial (GIS) data across Minnesota. The accompanying data set can be used to make similar maps using GIS software.

    Counties shown in this dataset as having free and open public geospatial data (with or without a policy) are: Aitkin, Anoka, Becker, Beltrami, Benton, Big Stone, Carlton, Carver, Cass, Chippewa, Chisago, Clay, Clearwater, Cook, Crow Wing, Dakota, Douglas, Grant, Hennepin, Hubbard, Isanti, Itasca, Kittson, Koochiching, Lac qui Parle, Lake, Lyon, Marshall, McLeod, Meeker, Mille Lacs, Morrison, Mower, Norman, Olmsted, Otter Tail, Pipestone, Polk, Pope, Ramsey, Renville, Rice, Scott, Sherburne, Stearns, Steele, Stevens, St. Louis, Traverse, Waseca, Washington, Wilkin, Winona, Wright and Yellow Medicine.

    To see if a county's data is distributed via the Minnesota Geospatial Commons, check the Commons organizations page: https://gisdata.mn.gov/organization

    To see if a county distributes data via its website, check the link(s) on the Minnesota County GIS Contacts webpage: https://www.mngeo.state.mn.us/county_contacts.html

  8. Links to all datasets and downloads for 80 A0/A3 digital image of map...

    • data.csiro.au
    • researchdata.edu.au
    Updated Jan 18, 2016
    + more versions
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    Kristen Williams; Nat Raisbeck-Brown; Tom Harwood; Suzanne Prober (2016). Links to all datasets and downloads for 80 A0/A3 digital image of map posters accompanying AdaptNRM Guide: Helping Biodiversity Adapt: supporting climate adaptation planning using a community-level modelling approach [Dataset]. http://doi.org/10.4225/08/569C1F6F9DCC3
    Explore at:
    Dataset updated
    Jan 18, 2016
    Dataset provided by
    CSIROhttp://www.csiro.au/
    Authors
    Kristen Williams; Nat Raisbeck-Brown; Tom Harwood; Suzanne Prober
    License

    https://research.csiro.au/dap/licences/csiro-data-licence/https://research.csiro.au/dap/licences/csiro-data-licence/

    Time period covered
    Jan 1, 2015 - Jan 10, 2015
    Area covered
    Dataset funded by
    CSIROhttp://www.csiro.au/
    Description

    This dataset is a series of digital map-posters accompanying the AdaptNRM Guide: Helping Biodiversity Adapt: supporting climate adaptation planning using a community-level modelling approach.

    These represent supporting materials and information about the community-level biodiversity models applied to climate change. Map posters are organised by four biological groups (vascular plants, mammals, reptiles and amphibians), two climate change scenario (1990-2050 MIROC5 and CanESM2 for RCP8.5), and five measures of change in biodiversity.

    The map-posters present the nationally consistent data at locally relevant resolutions in eight parts – representing broad groupings of NRM regions based on the cluster boundaries used for climate adaptation planning (http://www.environment.gov.au/climate-change/adaptation) and also Nationally.

    Map-posters are provided in PNG image format at moderate resolution (300dpi) to suit A0 printing. The posters were designed to meet A0 print size and digital viewing resolution of map detail. An additional set in PDF image format has been created for ease of download for initial exploration and printing on A3 paper. Some text elements and map features may be fuzzy at this resolution.

    Each map-poster contains four dataset images coloured using standard legends encompassing the potential range of the measure, even if that range is not represented in the dataset itself or across the map extent.

    Most map series are provided in two parts: part 1 shows the two climate scenarios for vascular plants and mammals and part 2 shows reptiles and amphibians. Eight cluster maps for each series have a different colour theme and map extent. A national series is also provided. Annotation briefly outlines the topics presented in the Guide so that each poster stands alone for quick reference.

    An additional 77 National maps presenting the probability distributions of each of 77 vegetation types – NVIS 4.1 major vegetation subgroups (NVIS subgroups) - are currently in preparation.

    Example citations:

    Williams KJ, Raisbeck-Brown N, Prober S, Harwood T (2015) Generalised projected distribution of vegetation types – NVIS 4.1 major vegetation subgroups (1990 and 2050), A0 map-poster 8.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

    Williams KJ, Raisbeck-Brown N, Harwood T, Prober S (2015) Revegetation benefit (cleared natural areas) for vascular plants and mammals (1990-2050), A0 map-poster 9.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

    This dataset has been delivered incrementally. Please check that you are accessing the latest version of the dataset. Lineage: The map posters show case the scientific data. The data layers have been developed at approximately 250m resolution (9 second) across the Australian continent to incorporate the interaction between climate and topography, and are best viewed using a geographic information system (GIS). Each data layers is 1Gb, and inaccessible to non-GIS users. The map posters provide easy access to the scientific data, enabling the outputs to be viewed at high resolution with geographical context information provided.

    Maps were generated using layout and drawing tools in ArcGIS 10.2.2

    A check list of map posters and datasets is provided with the collection.

    Map Series: 7.(1-77) National probability distribution of vegetation type – NVIS 4.1 major vegetation subgroup pre-1750 #0x

    8.1 Generalised projected distribution of vegetation types (NVIS subgroups) (1990 and 2050)

    9.1 Revegetation benefit (cleared natural areas) for plants and mammals (1990-2050)

    9.2 Revegetation benefit (cleared natural areas) for reptiles and amphibians (1990-2050)

    10.1 Need for assisted dispersal for vascular plants and mammals (1990-2050)

    10.2 Need for assisted dispersal for reptiles and amphibians (1990-2050)

    11.1 Refugial potential for vascular plants and mammals (1990-2050)

    11.1 Refugial potential for reptiles and amphibians (1990-2050)

    12.1 Climate-driven future revegetation benefit for vascular plants and mammals (1990-2050)

    12.2 Climate-driven future revegetation benefit for vascular reptiles and amphibians (1990-2050)

  9. GIS Market in EMEA by Component, End-user, and Geography - Forecast and...

    • technavio.com
    Updated Apr 6, 2022
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    Technavio (2022). GIS Market in EMEA by Component, End-user, and Geography - Forecast and Analysis 2022-2026 [Dataset]. https://www.technavio.com/report/gis-market-industry-in-emea-analysis
    Explore at:
    Dataset updated
    Apr 6, 2022
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    Europe, the Middle East and Africa, Middle East, UK, Africa, Europe
    Description

    Snapshot img

    The GIS market share in EMEA is expected to increase to USD 2.01 billion from 2021 to 2026, and the market’s growth momentum will accelerate at a CAGR of 8.23%.

    This EMEA GIS market research report provides valuable insights on the post COVID-19 impact on the market, which will help companies evaluate their business approaches. Furthermore, this report extensively covers GIS market in EMEA segmentation by:

    Component - Software, data, and services
    End-user - Government, utilities, military, telecommunication, and others
    

    What will the GIS Market Size in EMEA be During the Forecast Period?

    Download the Free Report Sample to Unlock the GIS Market Size in EMEA for the Forecast Period and Other Important Statistics

    The EMEA GIS market report also offers information on several market vendors, including arxiT SA, Autodesk Inc., Bentley Systems Inc., Cimtex International, CNIM SA, Computer Aided Development Corp. Ltd., Environmental Systems Research Institute Inc., Fugro NV, General Electric Co., HERE Global BV, Hexagon AB, Hi-Target, Mapbox Inc., Maxar Technologies Inc., Pitney Bowes Inc., PSI Services LLC, Rolta India Ltd., SNC Lavalin Group Inc., SuperMap Software Co. Ltd., Takor Group Ltd., and Trimble Inc. among others.

    GIS Market in EMEA: Key Drivers, Trends, and Challenges

    The integration of BIM and GIS is notably driving the GIS market growth in EMEA, although factors such as data viability and risk of intrusion may impede market growth. Our research analysts have studied the historical data and deduced the key market drivers and the COVID-19 pandemic impact on the GIS industry in EMEA. The holistic analysis of the drivers will help in deducing end goals and refining marketing strategies to gain a competitive edge.

    Key GIS Market Driver in EMEA

    One of the key factors driving the geographic information system (GIS) market growth in EMEA is the integration of BIM and GIS. A GIS adds value to BIM by visualizing and analyzing the data with regard to the buildings and surrounding features, such as environmental and demographic information. BIM data and workflows include information regarding sensors and the placement of devices in IoT-connected networks. For instance, Dubai's Civil Defense Department has integrated GIS data with its automatic fire surveillance system. This information is provided in a matter of seconds on the building monitoring systems of the Civil Defense Department. Furthermore, location-based services offered by GIS providers help generate huge volumes of data from stationary and moving devices and enable users to perform real-time spatial analytics and derive useful geographic insights from it. Owing to the advantages associated with the integration of BIM with GIS solutions, the demand for GIS solutions is expected to increase during the forecast period.

    Key GIS Market Challenge in EMEA

    One of the key challenges to the is the GIS market growth in EMEA is the data viability and risk of intrusion. Hackers can hack into these systems with malicious intentions and manipulate the data, which could have destructive or negative repercussions. Such hacking of data could cause nationwide chaos. For instance, if a hacker manipulated the traffic management database, massive traffic jams and accidents could result. If a hacker obtained access to the database of a national disaster management organization and manipulated the data to create a false disaster situation, it could lead to a panic situation. Therefore, the security infrastructure accompanying the implementation of GIS software solutions must be robust. Such security threats may impede market growth in the coming years.

    Key GIS Market Trend in EMEA

    Integration of augmented reality (AR) and GIS is one of the key geographic information system market trends in EMEA that is expected to impact the industry positively in the forecast period. AR apps could provide GIS content to professional end-users and aid them in making decisions on-site, using advanced and reliable information available on their mobile devices and smartphones. For instance, when the user simply points the camera of the phone at the ground, the application will be able to show the user the location and orientation of water pipes and electric cables that are concealed underground. Organizations such as the Open Geospatial Consortium (OGC) and the World Wide Web Consortium (W3C) are seeking investments and are open to sponsors for an upcoming AR pilot project, which seeks to advance the standards of AR technology at both respective organizations. Such factors will further support the market growth in the coming years.

    This GIS market in EMEA analysis report also provides detailed information on other upcoming trends and challenges that will have a far-reaching effect on the market growth. The actionable insights on the trends and challenges will help companies evaluate and develop growth st

  10. M

    DNRGPS

    • gisdata.mn.gov
    • data.wu.ac.at
    windows_app
    Updated Sep 7, 2022
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    Natural Resources Department (2022). DNRGPS [Dataset]. https://gisdata.mn.gov/dataset/dnrgps
    Explore at:
    windows_appAvailable download formats
    Dataset updated
    Sep 7, 2022
    Dataset provided by
    Natural Resources Department
    Description

    DNRGPS is an update to the popular DNRGarmin application. DNRGPS and its predecessor were built to transfer data between Garmin handheld GPS receivers and GIS software.

    DNRGPS was released as Open Source software with the intention that the GPS user community will become stewards of the application, initiating future modifications and enhancements.

    DNRGPS does not require installation. Simply run the application .exe

    See the DNRGPS application documentation for more details.

    Compatible with: Windows (XP, 7, 8, 10, and 11), ArcGIS shapefiles and file geodatabases, Google Earth, most hand-held Garmin GPSs, and other NMEA output GPSs

    Limited Compatibility: Interactions with ArcMap layer files and ArcMap graphics are no longer supported. Instead use shapefile or geodatabase.

    Prerequisite: .NET 4 Framework

    DNR Data and Software License Agreement

    Subscribe to the DNRGPS announcement list to be notified of upgrades or updates.

  11. Global map of tree density

    • figshare.com
    zip
    Updated May 31, 2023
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    Crowther, T. W.; Glick, H. B.; Covey, K. R.; Bettigole, C.; Maynard, D. S.; Thomas, S. M.; Smith, J. R.; Hintler, G.; Duguid, M. C.; Amatulli, G.; Tuanmu, M. N.; Jetz, W.; Salas, C.; Stam, C.; Piotto, D.; Tavani, R.; Green, S.; Bruce, G.; Williams, S. J.; Wiser, S. K.; Huber, M. O.; Hengeveld, G. M.; Nabuurs, G. J.; Tikhonova, E.; Borchardt, P.; Li, C. F.; Powrie, L. W.; Fischer, M.; Hemp, A.; Homeier, J.; Cho, P.; Vibrans, A. C.; Umunay, P. M.; Piao, S. L.; Rowe, C. W.; Ashton, M. S.; Crane, P. R.; Bradford, M. A. (2023). Global map of tree density [Dataset]. http://doi.org/10.6084/m9.figshare.3179986.v2
    Explore at:
    zipAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Crowther, T. W.; Glick, H. B.; Covey, K. R.; Bettigole, C.; Maynard, D. S.; Thomas, S. M.; Smith, J. R.; Hintler, G.; Duguid, M. C.; Amatulli, G.; Tuanmu, M. N.; Jetz, W.; Salas, C.; Stam, C.; Piotto, D.; Tavani, R.; Green, S.; Bruce, G.; Williams, S. J.; Wiser, S. K.; Huber, M. O.; Hengeveld, G. M.; Nabuurs, G. J.; Tikhonova, E.; Borchardt, P.; Li, C. F.; Powrie, L. W.; Fischer, M.; Hemp, A.; Homeier, J.; Cho, P.; Vibrans, A. C.; Umunay, P. M.; Piao, S. L.; Rowe, C. W.; Ashton, M. S.; Crane, P. R.; Bradford, M. A.
    License

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

    Description

    Crowther_Nature_Files.zip This description pertains to the original download. Details on revised (newer) versions of the datasets are listed below. When more than one version of a file exists in Figshare, the original DOI will take users to the latest version, though each version technically has its own DOI. -- Two global maps (raster files) of tree density. These maps highlight how the number of trees varies across the world. One map was generated using biome-level models of tree density, and applied at the biome scale. The other map was generated using ecoregion-level models of tree density, and applied at the ecoregion scale. For this reason, transitions between biomes or between ecoregions may be unrealistically harsh, but large-scale estimates are robust (see Crowther et al 2015 and Glick et al 2016). At the outset, this study was intended to generate reliable estimates at broad spatial scales, which inherently comes at the cost of fine-scale precision. For this reason, country-scale (or larger) estimates are generally more robust than individual pixel-level estimates. Additionally, due to data limitations, estimates for Mangroves and Tropical coniferous forest (as identified by WWF and TNC) were generated using models constructed from Topical moist broadleaf forest data and Temperate coniferous forest data, respectively. Because we used ecological analogy, the estimates for these two biomes should be considered less reliable than those of other biomes . These two maps initially appeared in Crowther et al (2015), with the biome map being featured more prominently. Explicit publication of the data is associated with Glick et al (2016). As they are produced, updated versions of these datasets, as well as alternative formats, will be made available under Additional Versions (see below).

    Methods: We collected over 420,000 ground-sources estimates of tree density from around the world. We then constructed linear regression models using vegetative, climatic, topographic, and anthropogenic variables to produce forest tree density estimates for all locations globally. All modeling was done in R. Mapping was done using R and ArcGIS 10.1.

    Viewing Instructions: Load the files into an appropriate geographic information system (GIS). For the original download (ArcGIS geodatabase files), load the files into ArcGIS to view or export the data to other formats. Because these datasets are large and have a unique coordinate system that is not read by many GIS, we suggest loading them into an ArcGIS dataframe whose coordinate system matches that of the data (see File Format). For GeoTiff files (see Additional Versions), load them into any compatible GIS or image management program.

    Comments: The original download provides a zipped folder that contains (1) an ArcGIS File Geodatabase (.gdb) containing one raster file for each of the two global models of tree density – one based on biomes and one based on ecoregions; (2) a layer file (.lyr) for each of the global models with the symbology used for each respective model in Crowther et al (2015); and an ArcGIS Map Document (.mxd) that contains the layers and symbology for each map in the paper. The data is delivered in the Goode homolosine interrupted projected coordinate system that was used to compute biome, ecoregion, and global estimates of the number and density of trees presented in Crowther et al (2015). To obtain maps like those presented in the official publication, raster files will need to be reprojected to the Eckert III projected coordinate system. Details on subsequent revisions and alternative file formats are list below under Additional Versions.----------

    Additional Versions: Crowther_Nature_Files_Revision_01.zip contains tree density predictions for small islands that are not included in the data available in the original dataset. These predictions were not taken into consideration in production of maps and figures presented in Crowther et al (2015), with the exception of the values presented in Supplemental Table 2. The file structure follows that of the original data and includes both biome- and ecoregion-level models.

    Crowther_Nature_Files_Revision_01_WGS84_GeoTiff.zip contains Revision_01 of the biome-level model, but stored in WGS84 and GeoTiff format. This file was produced by reprojecting the original Goode homolosine files to WGS84 using nearest neighbor resampling in ArcMap. All areal computations presented in the manuscript were computed using the Goode homolosine projection. This means that comparable computations made with projected versions of this WGS84 data are likely to differ (substantially at greater latitudes) as a product of the resampling. Included in this .zip file are the primary .tif and its visualization support files.

    References:

    Crowther, T. W., Glick, H. B., Covey, K. R., Bettigole, C., Maynard, D. S., Thomas, S. M., Smith, J. R., Hintler, G., Duguid, M. C., Amatulli, G., Tuanmu, M. N., Jetz, W., Salas, C., Stam, C., Piotto, D., Tavani, R., Green, S., Bruce, G., Williams, S. J., Wiser, S. K., Huber, M. O., Hengeveld, G. M., Nabuurs, G. J., Tikhonova, E., Borchardt, P., Li, C. F., Powrie, L. W., Fischer, M., Hemp, A., Homeier, J., Cho, P., Vibrans, A. C., Umunay, P. M., Piao, S. L., Rowe, C. W., Ashton, M. S., Crane, P. R., and Bradford, M. A. 2015. Mapping tree density at a global scale. Nature, 525(7568): 201-205. DOI: http://doi.org/10.1038/nature14967Glick, H. B., Bettigole, C. B., Maynard, D. S., Covey, K. R., Smith, J. R., and Crowther, T. W. 2016. Spatially explicit models of global tree density. Scientific Data, 3(160069), doi:10.1038/sdata.2016.69.

  12. 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
    Canada, United States, Global
    Description

    Snapshot img

    GIS In Utility Industry Market Size 2025-2029

    The gis in utility industry market size is forecast to increase by USD 3.55 billion, at a CAGR of 19.8% between 2024 and 2029.

    The utility industry's growing adoption of Geographic Information Systems (GIS) is driven by the increasing need for efficient and effective infrastructure management. GIS solutions enable utility companies to visualize, analyze, and manage their assets and networks more effectively, leading to improved operational efficiency and customer service. A notable trend in this market is the expanding application of GIS for water management, as utilities seek to optimize water distribution and reduce non-revenue water losses. However, the utility GIS market faces challenges from open-source GIS software, which can offer cost-effective alternatives to proprietary solutions. These open-source options may limit the functionality and support available to users, necessitating careful consideration when choosing a GIS solution. To capitalize on market opportunities and navigate these challenges, utility companies must assess their specific needs and evaluate the trade-offs between cost, functionality, and support when selecting a GIS provider. Effective strategic planning and operational execution will be crucial for success in this dynamic market.

    What will be the Size of the GIS In Utility Industry Market during the forecast period?

    Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
    Request Free SampleThe Global Utilities Industry Market for Geographic Information Systems (GIS) continues to evolve, driven by the increasing demand for advanced data management and analysis solutions. GIS services play a crucial role in utility infrastructure management, enabling asset management, data integration, project management, demand forecasting, data modeling, data analytics, grid modernization, data security, field data capture, outage management, and spatial analysis. These applications are not static but rather continuously unfolding, with new patterns emerging in areas such as energy efficiency, smart grid technologies, renewable energy integration, network optimization, and transmission lines. Spatial statistics, data privacy, geospatial databases, and remote sensing are integral components of this evolving landscape, ensuring the effective management of utility infrastructure. Moreover, the adoption of mobile GIS, infrastructure planning, customer service, asset lifecycle management, metering systems, regulatory compliance, GIS data management, route planning, environmental impact assessment, mapping software, GIS consulting, GIS training, smart metering, workforce management, location intelligence, aerial imagery, construction management, data visualization, operations and maintenance, GIS implementation, and IoT sensors is transforming the industry. The integration of these technologies and services facilitates efficient utility infrastructure management, enhancing network performance, improving customer service, and ensuring regulatory compliance. The ongoing evolution of the utilities industry market for GIS reflects the dynamic nature of the sector, with continuous innovation and adaptation to meet the changing needs of utility providers and consumers.

    How is this GIS In Utility Industry Industry segmented?

    The gis in utility industry industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. ProductSoftwareDataServicesDeploymentOn-premisesCloudGeographyNorth AmericaUSCanadaEuropeFranceGermanyRussiaMiddle East and AfricaUAEAPACChinaIndiaJapanSouth AmericaBrazilRest of World (ROW).

    By Product Insights

    The software segment is estimated to witness significant growth during the forecast period.In the utility industry, Geographic Information Systems (GIS) play a pivotal role in optimizing operations and managing infrastructure. Utilities, including electricity, gas, water, and telecommunications providers, utilize GIS software for asset management, infrastructure planning, network performance monitoring, and informed decision-making. The GIS software segment in the utility industry encompasses various solutions, starting with fundamental GIS software that manages and analyzes geographical data. Additionally, utility companies leverage specialized software for field data collection, energy efficiency, smart grid technologies, distribution grid design, renewable energy integration, network optimization, transmission lines, spatial statistics, data privacy, geospatial databases, GIS services, project management, demand forecasting, data modeling, data analytics, grid modernization, data security, field data capture, outage ma

  13. The GeoMAP (v.2022-08) continent-wide detailed geological dataset of...

    • doi.pangaea.de
    • antcat.antarcticanz.govt.nz
    html, tsv
    Updated Mar 16, 2023
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    Simon Christopher Cox; Christine S Smith Siddoway; Giovanni Capponi; Tamer Abu-Alam; Jasmine F Mawson; Nicola Dal Seno; Laura Crispini; Jacqueline A Halpin; Adam P Martin; Fraser Morgan; Gary S Wilson; Belinda Smith Lyttle; Samuel Elkind; Paul Morin; Matilda Ballinger; Lauren Bamber; Brett Kitchener; Luigi Lelli; Alexie Millikin; Louis Whitburn; Tristan White; Alex Burton-Johnson; David Elliot; Synnøve Elvevold; John W Goodge; Joachim Jacobs; Eugene Mikhalsky; John Smellie; Phil Scadden (2023). The GeoMAP (v.2022-08) continent-wide detailed geological dataset of Antarctica [Dataset]. http://doi.org/10.1594/PANGAEA.951482
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    html, tsvAvailable download formats
    Dataset updated
    Mar 16, 2023
    Dataset provided by
    PANGAEA
    Authors
    Simon Christopher Cox; Christine S Smith Siddoway; Giovanni Capponi; Tamer Abu-Alam; Jasmine F Mawson; Nicola Dal Seno; Laura Crispini; Jacqueline A Halpin; Adam P Martin; Fraser Morgan; Gary S Wilson; Belinda Smith Lyttle; Samuel Elkind; Paul Morin; Matilda Ballinger; Lauren Bamber; Brett Kitchener; Luigi Lelli; Alexie Millikin; Louis Whitburn; Tristan White; Alex Burton-Johnson; David Elliot; Synnøve Elvevold; John W Goodge; Joachim Jacobs; Eugene Mikhalsky; John Smellie; Phil Scadden
    License

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

    Variables measured
    Binary Object, Binary Object (MD5 Hash), Binary Object (File Size), Binary Object (Media Type)
    Description

    A dataset describing exposed bedrock and surficial geology of Antarctica constructed by the GeoMAP Action Group of SCAR (The Scientific Committee on Antarctic Research) and GNS Science, New Zealand. Legacy geological map data have been captured into a geographic information system (GIS), refining its spatial reliability, harmonising classification, then improving representation of glacial sequences and geomorphology. A total 99,080 polygons have been unified for depicting geology at 1:250,000 scale, but locally there are some areas with higher spatial precision. Geological definition in GeoMAP v.2022-08 is founded on a mixed chronostratigraphic- and lithostratigraphic-based classification. Description of rock and moraine polygons employs international GeoSciML data protocols to provide attribute-rich and queriable data; including bibliographic links to 589 source maps and scientific literature. Data are provided under CC-BY License as zipped ArcGIS geodatabase, QGIS geopackage or GoogleEarth kmz files. GeoMAP is the first detailed geological dataset covering all of Antarctica. GeoMAP depicts 'known geology' of rock exposures rather than 'interpreted' sub-ice features and is suitable for continent-wide perspectives and cross-discipline interrogation.

  14. e

    World - High Resolution Solar Resource (GHI, DIF, GTI, DNI) GIS Data,...

    • energydata.info
    Updated Nov 28, 2023
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    (2023). World - High Resolution Solar Resource (GHI, DIF, GTI, DNI) GIS Data, (Global Solar Atlas) - Dataset - ENERGYDATA.INFO [Dataset]. https://energydata.info/dataset/world-high-resolution-solar-resource-ghi-dif-gti-dni-gis-data-global-solar-atlas
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    Dataset updated
    Nov 28, 2023
    License

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

    Area covered
    World
    Description

    Developed by SOLARGIS and provided by the Global Solar Atlas (GSA), this data resource contains solar resource data for: direct normal irradiation (DNI), global horizontal irradiation (GHI), diffuse horizontal irradiation data (DIF), and global irradiation for optimally tilted surfaces (GTI), all in kWh/m² 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). Due to the large amount of data, the coverage has been divided into eight segments. Four segments for the North hemisphere: WWN (West-west-north), WN (West-north), EN (East-north), EEN (East-east-north). Analogically four segments for the South hemisphere: WWS, WS, ES, EES. The data is hyperlinked under 'resources' with the following characteristics: DNI LTAy_AvgDailyTotals (GeoTIFF) Data format: raster (gridded), GEOTIFF File size : 343.99 MB 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).

  15. W

    ESRI CS-W Client for ArcGIS

    • cloud.csiss.gmu.edu
    Updated Mar 21, 2019
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    GEOSS CSR (2019). ESRI CS-W Client for ArcGIS [Dataset]. https://cloud.csiss.gmu.edu/uddi/dataset/esri-cs-w-client-for-arcgis
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    Dataset updated
    Mar 21, 2019
    Dataset provided by
    GEOSS CSR
    Description

    This FREE extension enables discovering and using GIS resources available in a GEOSS Clearinghouse directly from ArcGIS Desktop and ArcGIS Explorer. The CS-W Client for ArcGIS can search many implementations of CS-W implementing CS-W 2.0.0, 2.0.1, 2.0.2 and a number of Application Profiles (OGCCORE, APISO, EBRIM). Providers can extend the CS-W Client by creating a profile of their CS-W service and including that in the CS-W client configuration. View the title, abstract, or footprints of search results or view and download the full metadata. Add referenced live map services (ArcGIS Server, ArcIMS, WMS) to an ArcMap document or ArcGIS Explorer globe. ArcGIS Desktop 9.3 is required to install the ArcMap component of the CS-W Clients for ArcGIS. The CS-W Clients for ArcGIS component for ArcGIS Explorer requires ArcGIS Explorer 380 or higher.

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

    • catalog.data.gov
    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
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    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).

  17. a

    Custom GIS Services

    • data-peoriacountygis.opendata.arcgis.com
    • hub.arcgis.com
    Updated Sep 14, 2017
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    County of Peoria (2017). Custom GIS Services [Dataset]. https://data-peoriacountygis.opendata.arcgis.com/documents/604092eea8df41a6be397e0b1144576b
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    Dataset updated
    Sep 14, 2017
    Dataset authored and provided by
    County of Peoria
    Description

    The Peoria County GIS open data website provides GIS data, interactive maps, and digital maps free of charge under an open data license agreement. Peoria County GIS also provides custom GIS services upon request for GIS data and digital maps not available on the open data website. Please click the Download button to download and view the current request form for custom GIS services. All custom services are charged at $60 per hour.Contact InformationEmail: gis@peoriacounty.orgPhysical AddressPeoria County CourthouseIT Service Department - GIS Division324 Main St.Room G11Peoria, IL 61602

  18. a

    ArcGIS Desktop 10.6.1

    • hub.arcgis.com
    Updated Feb 19, 2019
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    Prefeitura da Cidade do Rio de Janeiro (2019). ArcGIS Desktop 10.6.1 [Dataset]. https://hub.arcgis.com/content/1dc834ad1ad04f70bf7a689cbdcd2b73
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    Dataset updated
    Feb 19, 2019
    Dataset authored and provided by
    Prefeitura da Cidade do Rio de Janeiro
    Description
  19. O

    Norfolk Open GIS Data

    • data.norfolk.gov
    • data.virginia.gov
    application/rdfxml +5
    Updated Jan 3, 2019
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    IT- GIS Department (2019). Norfolk Open GIS Data [Dataset]. https://data.norfolk.gov/Maps/Norfolk-Open-GIS-Data/v4g5-yqn9
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    csv, application/rssxml, xml, tsv, application/rdfxml, jsonAvailable download formats
    Dataset updated
    Jan 3, 2019
    Dataset authored and provided by
    IT- GIS Department
    Description

    The City of Norfolk Open GIS Data Site. This site contains various spatial data that can be used by anyone with an interest in geographic information systems (GIS) data for their applications. The City’s datasets are updated regularly and can be downloaded or accessed for free from this site. If you don’t see a particular dataset you are looking for, please check back often, as we will be providing additional data to the site in the future.

  20. C

    GIS Mapping files

    • data.birminghamal.gov
    geojson, html, shp
    Updated Jan 9, 2019
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    Birmingham Planning & Engineering (2019). GIS Mapping files [Dataset]. https://data.birminghamal.gov/dataset/gis-mapping-files
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    html, shp, geojson, geojson(1853069), geojson(1539369), shp(444998), shp(377381)Available download formats
    Dataset updated
    Jan 9, 2019
    Dataset authored and provided by
    Birmingham Planning & Engineering
    License

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

    Description

    Planning, Engineering & Permitting - GIS Mapping files

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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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30 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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