51 datasets found
  1. a

    3D People ArcGIS Pro Style

    • hub.arcgis.com
    Updated Jun 7, 2022
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    ArcGIS Living Atlas Team (2022). 3D People ArcGIS Pro Style [Dataset]. https://hub.arcgis.com/content/5d79e5ace56d4aaaba1dbf9176b5effc
    Explore at:
    Dataset updated
    Jun 7, 2022
    Dataset authored and provided by
    ArcGIS Living Atlas Team
    Description

    A style containing 34 assorted 3D people models for use in large-scale visualizations, providing vertical context.To Match Layer Symbology to Style in ArcGIS Pro, populate a person_type text field to match the values shown below. Next, copy these values to a table, then join the height value(s) to the people points for use in pop-ups or charts. person_type name height_m height_feet height_inches

    Man 1 Gerald 1.7899 5 10.47

    Man 2 Ethan 1.8879 6 2.33

    Man 3 Cliff 1.7015 5 6.99

    Man 4 Dustin 1.7965 5 10.73

    Man 5 Jorge 1.8787 6 1.96

    Man 6 Phillip 1.6752 5 5.95

    Man 7 Dmitri 1.71 5 7.32

    Man 8 Luke 1.793 5 10.59

    Man 9 Carlos 1.7028 5 7.04

    Man 10 Jimmy 1.7625 5 9.39

    Man 11 Helmut 1.8331 6 0.17

    Man 12 Guy 1.812 5 11.34

    Man 13 Leon 1.8219 5 11.73

    Man 14 Matthias 1.753 5 9.02

    Man 15 Kendrick 1.8787 6 1.96

    Man 16 Seth 1.8272 5 11.94

    Man 17 Gomer 1.8982 6 2.73

    Man 18 Robert 1.7853 5 10.29

    Man 19 Jack 1.779 5 10.04

    Man 20 Andy 1.8794 6 1.99

    Man 21 Hamish 1.67 5 5.75

    Man 22 Felix 1.86 6 1.23

    Man 23 Adrian 1.75 5 8.90

    Woman 1 Greta 1.5371 5 0.52

    Woman 2 Simone 1.6366 5 4.43

    Woman 3 Alison 1.679 5 6.10

    Woman 4 Felicia 1.7433 5 8.63

    Woman 5 Jessica 1.7322 5 8.20

    Woman 6 Claire 1.6405 5 4.59

    Woman 7 Maude 1.7795 5 10.06

    Woman 8 Jenny 1.659 5 5.31

    Woman 9 Diane 1.67 5 5.75

    Woman 10 Carla 1.75 5 8.90

    Woman 11 Lauren 1.69 5 6.54

  2. M

    DNR QuickLayers for ArcGIS Pro 3

    • gisdata.mn.gov
    esri_addin
    Updated Jun 14, 2025
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    Natural Resources Department (2025). DNR QuickLayers for ArcGIS Pro 3 [Dataset]. https://gisdata.mn.gov/dataset/quick-layers-pro3
    Explore at:
    esri_addinAvailable download formats
    Dataset updated
    Jun 14, 2025
    Dataset provided by
    Natural Resources Department
    Description

    The way to access Layers Quickly.

    Quick Layers is an Add-In for ArcGIS Pro 3 that allows rapid access to the DNR's Geospatial Data Resource Site (GDRS). The GDRS is a data structure that serves core geospatial dataset and applications for not only DNR, but many state agencies, and supports the Minnesota Geospatial Commons. Data added from Quick Layers is pre-symbolized, helping to standardize visualization and map production. Current version: 3.11

    To use Quick Layers with the GDRS, there's no need to download QuickLayers from this location. Instead, download a full copy or a custom subset of the public GDRS (including Quick Layers for ArcGIS Pro 3) using GDRS Manager.

    Quick Layers also allows users to save and share their own pre-symbolized layers, thus increasing efficiency and consistency across the enterprise.

    Installation:

    After using GDRS Manager to create a GDRS, including Quick Layers, add the path to the Quick Layers addin to the list of shared folders:
    1. Open ArcGIS Pro
    2. Project -> Add-In Manager -> Options
    3. Click add folder, and enter the location of the Quick Layers Pro app. For example, if your GDRS is mapped to the V drive, the path would be V:\gdrs\apps\pub\us_mn_state_dnr\quick_layers_pro3
    4. After you do this, the Quick Layers ribbon will be available. To also add Quick Layers to the Quick Access Toolbar at the top, right click Quick Layers, and select Add to Quick Access Toolbar

    The link below is only for those who are using Quick Layers without a GDRS. To get the most functionality out of Quick Layers, don't install it separately, but instead download it as part of a GDRS build using GDRS Manager.

  3. Pen and Ink style for ArcGIS Pro

    • hub.arcgis.com
    Updated May 14, 2020
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    Esri Styles (2020). Pen and Ink style for ArcGIS Pro [Dataset]. https://hub.arcgis.com/content/236a170ca687438d83fef046297d243f
    Explore at:
    Dataset updated
    May 14, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri Styles
    Description

    Everybody just loves a pen and ink stipple effect. It’s charming, it’s warm, it’s handsome, it’s tactile. It says, say, want to sit on the couch and I’ll read to you from your well-worn copy of Where the Sidewalk Ends?I’ve tried out the stipple effect in maps (here and here) that I’ve hand-drawn (yes, and so should you!) as well as dipped my toe into creating a digital effect (here and here), and found that it gives a richness of clarity and depth. Then a few days ago I saw this wonderful hand stippled map drawn by Molly Elkins, on Twitter. The simple beauty of her map motivated me to go back to the inkwell and get an honest to goodness pen and ink style together for ArcGIS Pro.Here are some examples...Here's what's in the style...

  4. d

    Tax Parcel Fabric Data

    • catalog.data.gov
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +1more
    Updated Mar 22, 2025
    + more versions
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    Lake County Illinois GIS (2025). Tax Parcel Fabric Data [Dataset]. https://catalog.data.gov/dataset/tax-parcel-fabric-data-460e8
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    Dataset updated
    Mar 22, 2025
    Dataset provided by
    Lake County Illinois GIS
    Description

    Download In State Plane Projection Here The 2024 Parcel Fabric Data is a copy of the Lake County Chief Assessor's Office spatial dataset, consisting of separate layers which represent the boundaries for Tax Parcels, Lots, Units, Subs, Condos, Rights of Way, and Encumbrance parcels, along with points, lines, and PLSS townships for reference, which have all been captured for the 2024 Tax Year.This data is spatial in nature and does not include extensive fields of attributes to which each layer may be associated. This data is provided for use to individuals or entities with an understanding of Esri's ArcGIS Pro (specifically the Parcel Fabric), and those with access to ArcGIS Pro, which is necessary to view or manipulate the data.Casual users can find the standalone Tax Parcel Boundary Data here and Parcel Attribute Data here. Update Frequency: This dataset is updated on a yearly basis.

  5. a

    Sample ETL for NG911GIS Upload Script

    • hub.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Sep 15, 2022
    + more versions
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    Virginia Geographic Information Network (2022). Sample ETL for NG911GIS Upload Script [Dataset]. https://hub.arcgis.com/content/fdf0e48f40c84c5a8e7acb57f16a4df3
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    Dataset updated
    Sep 15, 2022
    Dataset authored and provided by
    Virginia Geographic Information Network
    Description

    Example extract, transform, and load (ETL) framework with comments and print statements to develop a script using the "run tools in Pro and copy script to a file" method to assist in NG911 transition by transforming and loading local addresses and road centerlines into the NENA Next Generation 9-1-1 GIS Data Model Schema. Created on 20220915 as a supplement to a "Supporting Extract, Transform, and Load Development for Next Generation 9-1-1" presentation delivered at GIS Pro 2022. Originally developed by Matt Gerike, Virginia Geographic Information Network, September 2022.Parity logic contributed by Charles Grant, City of Salem, Virginia, March 2021.See here for resources and context about using the NG9-1-1 GIS data model templates.Additional resources and recommendations on GIS related topics are available on the VGIN 9-1-1 & GIS page.

  6. e

    Geospatial Data from the Alpine Treeline Warming Experiment (ATWE) on Niwot...

    • knb.ecoinformatics.org
    • data.ess-dive.lbl.gov
    • +2more
    Updated Jun 26, 2023
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    Fabian Zuest; Cristina Castanha; Nicole Lau; Lara M. Kueppers (2023). Geospatial Data from the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA [Dataset]. http://doi.org/10.15485/1804896
    Explore at:
    Dataset updated
    Jun 26, 2023
    Dataset provided by
    ESS-DIVE
    Authors
    Fabian Zuest; Cristina Castanha; Nicole Lau; Lara M. Kueppers
    Time period covered
    Jan 1, 2008 - Jan 1, 2012
    Area covered
    Description

    This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive. As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.

  7. W

    USA Flood Hazard Areas

    • wifire-data.sdsc.edu
    • gis-calema.opendata.arcgis.com
    • +1more
    csv, esri rest +4
    Updated Jul 14, 2020
    + more versions
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    CA Governor's Office of Emergency Services (2020). USA Flood Hazard Areas [Dataset]. https://wifire-data.sdsc.edu/dataset/usa-flood-hazard-areas
    Explore at:
    geojson, csv, kml, esri rest, html, zipAvailable download formats
    Dataset updated
    Jul 14, 2020
    Dataset provided by
    CA Governor's Office of Emergency Services
    License

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

    Area covered
    United States
    Description
    The Federal Emergency Management Agency (FEMA) produces Flood Insurance Rate maps and identifies Special Flood Hazard Areas as part of the National Flood Insurance Program's floodplain management. Special Flood Hazard Areas have regulations that include the mandatory purchase of flood insurance.

    Dataset Summary

    Phenomenon Mapped: Flood Hazard Areas
    Coordinate System: Web Mercator Auxiliary Sphere
    Extent: 50 United States plus Puerto Rico, the US Virgin Islands, Guam, the Northern Mariana Islands and American Samoa
    Visible Scale: The layer is limited to scales of 1:1,000,000 and larger. Use the USA Flood Hazard Areas imagery layer for smaller scales.
    Publication Date: April 1, 2019

    This layer is derived from the April 1, 2019 version of the National Flood Hazard Layer feature class S_Fld_Haz_Ar. The data were aggregated into eight classes to produce the Esri Symbology field based on symbology provided by FEMA. All other layer attributes are derived from the National Flood Hazard Layer. The layer was projected to Web Mercator Auxiliary Sphere and the resolution set to 1 meter.

    To improve performance Flood Zone values "Area Not Included", "Open Water", "D", "NP", and No Data were removed from the layer. Areas with Flood Zone value "X" subtype "Area of Minimal Flood Hazard" were also removed. An imagery layer created from this dataset provides access to the full set of records in the National Flood Hazard Layer.

    A web map featuring this layer is available for you to use.

    What can you do with this Feature Layer?

    Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.

    ArcGIS Online
    • Add this layer to a map in the map viewer. The layer is limited to scales of approximately 1:1,000,000 or larger but an imagery layer created from the same data can be used at smaller scales to produce a webmap that displays across the full range of scales. The layer or a map containing it can be used in an application.
    • Change the layer’s transparency and set its visibility range
    • Open the layer’s attribute table and make selections and apply filters. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.
    • Change the layer’s style and filter the data. For example, you could change the symbology field to Special Flood Hazard Area and set a filter for = “T” to create a map of only the special flood hazard areas.
    • Add labels and set their properties
    • Customize the pop-up
    ArcGIS Pro
    • Add this layer to a 2d or 3d map. The same scale limit as Online applies in Pro
    • Use as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class. Areas up to 1,000-2,000 features can be exported successfully.
    • Change the symbology and the attribute field used to symbolize the data
    • Open table and make interactive selections with the map
    • Modify the pop-ups
    • Apply Definition Queries to create sub-sets of the layer
    This layer is part of the Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.
  8. a

    maina rosemary ke universities-Copy

    • africageoportal.com
    Updated Feb 10, 2023
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    Africa GeoPortal (2023). maina rosemary ke universities-Copy [Dataset]. https://www.africageoportal.com/maps/f3281df76f0d4fe1901694e20b1581ce
    Explore at:
    Dataset updated
    Feb 10, 2023
    Dataset authored and provided by
    Africa GeoPortal
    License

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

    Area covered
    Description

    This map references the OpenStreetMap tile layer hosted by Esri. This tile layer presents a new vector basemap of OpenStreetMap (OSM) data created and hosted by Esri, now in beta release. Esri produced this vector tile basemap in ArcGIS Pro from a live replica of OSM data, hosted by Esri, that was rendered using OSM cartography. The vector tiles are updated every few weeks; refer to the OpenStreetMap tile layer for details on when it was last updated. When fully released, this vector basemap will be freely available for any user or developer to build into their web map or web mapping apps.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 and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site: www.OpenStreetMap.org. Esri is a supporter of the OSM project and is excited to make this new vector basemap available available to the OSM, GIS, and Developer communities.

  9. Regression Model Map

    • anrgeodata.vermont.gov
    Updated May 10, 2019
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    Esri Tutorials (2019). Regression Model Map [Dataset]. https://anrgeodata.vermont.gov/content/50b4195ee6b04a8bb2b3a78899ccd710
    Explore at:
    Dataset updated
    May 10, 2019
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri Tutorials
    Area covered
    Description

    Explore time-discrete statistical climate downscaling using regression tools and a Jupyter notebook with Python to automate temperature predictions and build a time-series mosaic. This has been created for the Learn ArcGIS lesson Downscale climate data with machine learning.This is an archived copy of the tutorial data and will no longer be updated. For an up-to-date version, available only in English, please see Regression Analysis: Building a Regression Model Using ArcGIS Pro, Regression Analysis: Performing Random Forest Regression Using ArcGIS Pro, and Downscaling a Prediction Model Using ArcGIS Notebooks and ArcGIS Pro.

  10. a

    RoadNameAlias

    • share-open-data-njtpa.hub.arcgis.com
    • njogis-newjersey.opendata.arcgis.com
    • +1more
    Updated Jun 23, 2025
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    New Jersey Office of GIS (2025). RoadNameAlias [Dataset]. https://share-open-data-njtpa.hub.arcgis.com/datasets/newjersey::roadnamealias
    Explore at:
    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    New Jersey Office of GIS
    Area covered
    Description

    Statewide Download (FGDB) (SHP)Users can also download smaller geographic areas of this feature service in ArcGIS Pro using the Copy Features geoprocessing tool. The address service contains statewide address points and related landmark name alias table and street name alias table.The New Jersey Office of Information Technology, Office of GIS (NJOGIS), in partnership with several local GIS and public safety agencies, has built a comprehensive statewide NG9-1-1 database meeting and exceeding the requirements of the National Emergency Number Association (NENA) 2018 NG9-1-1 GIS Data Standard (NENA-STA-006.1-2018). The existing New Jersey Statewide Address Point data last published in 2016 has been transformed in the NENA data model to create this new address point data.The initial address points were processed from statewide parcel records joined with the statewide Tax Assessor's (MOD-IV) database in 2015. Address points supplied by Monmouth County, Sussex County, Morris County and Montgomery Township in Somerset County were incorporated into the statewide address points using customized Extract, Transform and Load (ETL) procedures.The previous version of the address points was loaded into New Jersey's version of the NENA NG9-1-1 data model using Extract, Transform and Load (ETL) procedures created with Esri's Data Interoperability Extension. Subsequent manual and bulk processing corrections and additions have been made, and are ongoing.***NOTE*** For users who incorporate NJOGIS services into web maps and/or web applications, please sign up for the NJ Geospatial Forum discussion listserv for early notification of service changes. Visit https://nj.gov/njgf/about/listserv/ for more information.

  11. a

    FAO Locust Map-Copy

    • africageoportal.com
    Updated Oct 23, 2020
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    Africa GeoPortal (2020). FAO Locust Map-Copy [Dataset]. https://www.africageoportal.com/maps/d6d88775757e47909f3cddd7bbffe427
    Explore at:
    Dataset updated
    Oct 23, 2020
    Dataset authored and provided by
    Africa GeoPortal
    License

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

    Area covered
    Description

    This vector webmap presents a new vector basemap of OpenStreetMap (OSM) data created and hosted by Esri. Esri produced this vector tile basemap in ArcGIS Pro from a live replica of OSM data, hosted by Esri. It provides a detailed base layer for the world featuring a light neutral style with minimal colors, OpenStreetMap (Light Gray Canvas Base - WGS84) and also an overlaying reference layer, OpenStreetMap (Light Gray Canvas Reference - WGS84). The vector tiles will be updated quarterly with the latest OSM data. This vector basemap is freely available for any user or developer to build into their web map or web mapping apps.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 and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site: www.OpenStreetMap.org. Esri is a supporter of the OSM project and is excited to make this new vector basemap available available to the OSM, GIS, and Developer communities.Precise Tile Registration: The tile layer uses the improved tiling scheme “WGS84 Geographic, Version 2” to ensure proper tile positioning at higher resolutions (neighborhood level and beyond). The new tiling scheme is much more precise than tiling schemes of the legacy basemaps Esri released years ago. We recommend that you start using this new basemap for any new web maps in WGS84 that you plan to author. Due to the number of differences between the old and new tiling schemes, some web clients will not be able to overlay tile layers in the old and new tiling schemes in one web map.

  12. W

    Wildfire Perimeters (NIFC)

    • wifire-data.sdsc.edu
    csv, esri rest +4
    Updated Jun 22, 2020
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    CA Governor's Office of Emergency Services (2020). Wildfire Perimeters (NIFC) [Dataset]. https://wifire-data.sdsc.edu/dataset/wildfire-perimeters-nifc
    Explore at:
    kml, html, esri rest, geojson, csv, zipAvailable download formats
    Dataset updated
    Jun 22, 2020
    Dataset provided by
    CA Governor's Office of Emergency Services
    License

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

    Description

    This ArcGIS Online hosted feature service displays perimeters from the National Incident Feature Service (NIFS) that meet ALL of the following criteria:

    • FeatureCategory = 'Wildfire Daily Fire Perimeter'
    • IsVisible = 'Yes'
    • FeatureAccess = 'Public'
    • FeatureStatus = 'Approved'.

    This dataset is made up of current, active wildfires. On a weekly basis, fires meeting specific criteria are removed from the source service. After removal, those perimeters can be found in the associated "Archived Wildfire Perimeters" service. Criteria include:
    • Perimeters are identified with an IRWIN ID that has non-null values in IRWIN for ContainmentDateTime, ControlDateTime, or FireOutDateTime
    • The most recent controlled/contained/fire out date is greater than 14 days old
    • No IRWIN ID
    • Last edit (based on DateCurrent) is greater than 30 days old
    This hosted feature service is not "live", but is updated every 5 minutes to reflect changes to perimeters posted to the National Incident Feature Service. It is updated from operational data and may not reflect current conditions on the ground. For a better understanding of the workflows involved in mapping and sharing fire perimeter data, see the NWCG Geographic Information System Standard Operating Procedures On Incidents (GSTOP) and most recent addendums: https://www.nwcg.gov/publications/936.

    To use this service from the Open Data site in a web map, click the APIs down arrow, copy the GeoService URL (remove the /query? statement) or just copy and paste this URL and add it to a web map (Add > Add Layer from Web): https://services3.arcgis.com/T4QMspbfLg3qTGWY/arcgis/rest/services/Public_Wildfire_Perimeters_View/FeatureServer

    From within ArcGIS Online, open this feature service in a new web map by clicking Open in Map Viewer.

    Once this service has been added to a web map, the features can be filtered by incident name, GACC, Create Date, or Current Date, keeping in mind that not all perimeters are fully attributed. Not all data are editable through this service and delete is disabled. To delete features, open in ArcGIS Pro or ArcMap.

    If your perimeter is not found in the Current Wildfire Perimeters, check in the Archived dataset: https://nifc.maps.arcgis.com/home/item.html?id=090a23c0470d4ef9a27142ee9b200023

  13. a

    Environment Map-Copy-Copy

    • africageoportal.com
    Updated Feb 27, 2025
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    Africa GeoPortal (2025). Environment Map-Copy-Copy [Dataset]. https://www.africageoportal.com/maps/67761d833a964cae91e2f3563db56a18
    Explore at:
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Africa GeoPortal
    Area covered
    Description

    This web map consists of vector tile layers that form a detailed basemap for the world, featuring a neutral style with content adjusted to support environment, landscape, natural resources, hydrologic and physical geography layers. The layers in this map provide unique capabilities for customization, high-resolution display and offline use in mobile devices. They are built using the same data sources used for other Esri basemaps.This web map consists of 4 vector tile layers: A vector tile reference layer for the world with administrative boundaries and labels; populated places with names; ocean names; topographic features; and rail, road, park, school, and hospital labels. A vector tile surface water layer for the world with rivers, lakes, streams, and canals with respective labels. A vector tile watersheds boundaries. A vector tile base layer for the world with vegetation, parks, farming areas, open space, indigenous lands, military bases, bathymetry, large scale contours, elevation values, airports, zoos, golf courses, cemeteries, hospitals, schools, urban areas, and building footprints. Designed by Emily Meriam, this map can be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. Fully display the content of this multisource map using Map Viewer, or current versions of Runtime and ArcGIS Pro. Customize this MapCustomize vector tile layers in this map using the Vector Tile Style Editor to change style, content, symbology, and fonts. Additional details are available in ArcGIS Online Blogs and the Esri Vector Basemaps Reference Document.

  14. National Hydrography Dataset Plus High Resolution

    • hub.arcgis.com
    Updated Mar 16, 2023
    + more versions
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    Esri (2023). National Hydrography Dataset Plus High Resolution [Dataset]. https://hub.arcgis.com/maps/f1f45a3ba37a4f03a5f48d7454e4b654
    Explore at:
    Dataset updated
    Mar 16, 2023
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    The National Hydrography Dataset Plus High Resolution (NHDplus High Resolution) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US Geological Survey, NHDPlus High Resolution provides mean annual flow and velocity estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses.For more information on the NHDPlus High Resolution dataset see the User’s Guide for the National Hydrography Dataset Plus (NHDPlus) High Resolution.Dataset SummaryPhenomenon Mapped: Surface waters and related features of the United States and associated territoriesGeographic Extent: The Contiguous United States, Hawaii, portions of Alaska, Puerto Rico, Guam, US Virgin Islands, Northern Marianas Islands, and American SamoaProjection: Web Mercator Auxiliary Sphere Visible Scale: Visible at all scales but layer draws best at scales larger than 1:1,000,000Source: USGSUpdate Frequency: AnnualPublication Date: July 2022This layer was symbolized in the ArcGIS Map Viewer and while the features will draw in the Classic Map Viewer the advanced symbology will not. Prior to publication, the network and non-network flowline feature classes were combined into a single flowline layer. Similarly, the Area and Waterbody feature classes were merged under a single schema.Attribute fields were added to the flowline and waterbody layers to simplify symbology and enhance the layer's pop-ups. Fields added include Pop-up Title, Pop-up Subtitle, Esri Symbology (waterbodies only), and Feature Code Description. All other attributes are from the original dataset. No data values -9999 and -9998 were converted to Null values.What can you do with this layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer or a map containing it can be used in an application. Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Apply filters. For example you can set a filter to show larger streams and rivers using the mean annual flow attribute or the stream order attribute.Change the layer’s style and symbologyAdd labels and set their propertiesCustomize the pop-upUse as an input to the ArcGIS Online analysis tools. This layer works well as a reference layer with the trace downstream and watershed tools. The buffer tool can be used to draw protective boundaries around streams and the extract data tool can be used to create copies of portions of the data.ArcGIS ProAdd this layer to a 2d or 3d map.Use as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class.Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of the ArcGIS Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

  15. g

    Tax Parcel Fabric Data | gimi9.com

    • gimi9.com
    Updated Apr 1, 2025
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    (2025). Tax Parcel Fabric Data | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_tax-parcel-fabric-data-460e8/
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    Dataset updated
    Apr 1, 2025
    Description

    The 2023 Parcel Fabric Data is a copy of the Lake County Chief Assessor's Office spatial dataset, consisting of separate layers which represent the boundaries for Tax Parcels, Lots, Units, Subs, Condos, Rights of Way, and Encumbrance parcels, along with points, lines, and PLSS townships for reference, which have all been captured for the 2023 Tax Year.This data is spatial in nature and does not include extensive fields of attributes to which each layer may be associated. This data is provided for use to individuals or entities with an understanding of Esri's ArcGIS Pro (specifically the Parcel Fabric), and those with access to ArcGIS Pro, which is necessary to view or manipulate the data.Casual users can find the standalone Tax Parcel Boundary Data here and Parcel Attribute Data here. Update Frequency: This dataset is updated on a yearly basis.

  16. USA Protected Areas - GAP Status Code (Mature Support)

    • cgs-topics-lincolninstitute.hub.arcgis.com
    • resilience.climate.gov
    • +1more
    Updated Aug 16, 2022
    + more versions
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    Esri (2022). USA Protected Areas - GAP Status Code (Mature Support) [Dataset]. https://cgs-topics-lincolninstitute.hub.arcgis.com/datasets/esri::usa-protected-areas-gap-status-code-mature-support-1
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    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    Important Note: This item is in mature support as of September 2023 and will be retired in December 2025. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.The USGS Protected Areas Database of the United States (PAD-US) is the official inventory of public parks and other protected open space. The spatial data in PAD-US represents public lands held in trust by thousands of national, state and regional/local governments, as well as non-profit conservation organizations.GAP 1 and 2 areas are primarily managed for biodiversity, GAP 3 are managed for multiple uses including conservation and extraction, GAP 4 no known mandate for biodiversity protection. Provides a general overview of protection status including management designations. PAD-US is published by the U.S. Geological Survey (USGS) Science Analytics and Synthesis (SAS), Gap Analysis Project (GAP). GAP produces data and tools that help meet critical national challenges such as biodiversity conservation, recreation, public health, climate change adaptation, and infrastructure investment. See the GAP webpage for more information about GAP and other GAP data including species and land cover.The USGS Protected Areas Database of the United States (PAD-US) classifies lands into four GAP Status classes:GAP Status 1 - Areas managed for biodiversity where natural disturbances are allowed to proceedGAP Status 2 - Areas managed for biodiversity where natural disturbance is suppressedGAP Status 3 - Areas protected from land cover conversion but subject to extractive uses such as logging and miningGAP Status 4 - Areas with no known mandate for protectionIn the United States, areas that are protected from development and managed for biodiversity conservation include Wilderness Areas, National Parks, National Wildlife Refuges, and Wild & Scenic Rivers. Understanding the geographic distribution of these protected areas and their level of protection is an important part of landscape-scale planning. Dataset SummaryPhenomenon Mapped: Areas protected from development and managed to maintain biodiversity Coordinate System: Web Mercator Auxiliary SphereExtent: 50 United States plus Puerto Rico, the US Virgin Islands, the Northern Mariana Islands and other Pacific Ocean IslandsVisible Scale: 1:1,000,000 and largerSource: USGS Science Analytics and Synthesis (SAS), Gap Analysis Project (GAP) PAD-US version 3.0Publication Date: July 2022Attributes included in this layer are: CategoryOwner TypeOwner NameLocal OwnerManager TypeManager NameLocal ManagerDesignation TypeLocal DesignationUnit NameLocal NameSourcePublic AccessGAP Status - Status 1, 2, or 3GAP Status DescriptionInternational Union for Conservation of Nature (IUCN) Description - I: Strict Nature Reserve, II: National Park, III: Natural Monument or Feature, IV: Habitat/Species Management Area, V: Protected Landscape/Seascape, VI: Protected area with sustainable use of natural resources, Other conservation area, UnassignedDate of EstablishmentThe source data for this layer are available here. What can you do with this Feature Layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer is limited to scales of approximately 1:1,000,000 or larger but a vector tile layer created from the same data can be used at smaller scales to produce a webmap that displays across the full range of scales. The layer or a map containing it can be used in an application.Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections and apply filters. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Change the layer’s style and filter the data. For example, you could set a filter for Gap Status Code = 3 to create a map of only the GAP Status 3 areas.Add labels and set their propertiesCustomize the pop-upArcGIS ProAdd this layer to a 2d or 3d map. The same scale limit as Online applies in ProUse as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class. Note that many features in the PAD-US database overlap. For example wilderness area designations overlap US Forest Service and other federal lands. Any analysis should take this into consideration. An imagery layer created from the same data set can be used for geoprocessing analysis with larger extents and eliminates some of the complications arising from overlapping polygons.Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of the Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

  17. d

    Toronto Land Use Spatial Data - parcel-level - (2019-2021)

    • dataone.org
    • borealisdata.ca
    Updated Dec 28, 2023
    + more versions
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    Fortin, Marcel (2023). Toronto Land Use Spatial Data - parcel-level - (2019-2021) [Dataset]. http://doi.org/10.5683/SP3/1VMJAG
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    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Fortin, Marcel
    Area covered
    Toronto
    Description

    Please note that this dataset is not an official City of Toronto land use dataset. It was created for personal and academic use using City of Toronto Land Use Maps (2019) found on the City of Toronto Official Plan website at https://www.toronto.ca/city-government/planning-development/official-plan-guidelines/official-plan/official-plan-maps-copy, along with the City of Toronto parcel fabric (Property Boundaries) found at https://open.toronto.ca/dataset/property-boundaries/ and Statistics Canada Census Dissemination Blocks level boundary files (2016). The property boundaries used were dated November 11, 2021. Further detail about the City of Toronto's Official Plan, consolidation of the information presented in its online form, and considerations for its interpretation can be found at https://www.toronto.ca/city-government/planning-development/official-plan-guidelines/official-plan/ Data Creation Documentation and Procedures Software Used The spatial vector data were created using ArcGIS Pro 2.9.0 in December 2021. PDF File Conversions Using Adobe Acrobat Pro DC software, the following downloaded PDF map images were converted to TIF format. 9028-cp-official-plan-Map-14_LandUse_AODA.pdf 9042-cp-official-plan-Map-22_LandUse_AODA.pdf 9070-cp-official-plan-Map-20_LandUse_AODA.pdf 908a-cp-official-plan-Map-13_LandUse_AODA.pdf 978e-cp-official-plan-Map-17_LandUse_AODA.pdf 97cc-cp-official-plan-Map-15_LandUse_AODA.pdf 97d4-cp-official-plan-Map-23_LandUse_AODA.pdf 97f2-cp-official-plan-Map-19_LandUse_AODA.pdf 97fe-cp-official-plan-Map-18_LandUse_AODA.pdf 9811-cp-official-plan-Map-16_LandUse_AODA.pdf 982d-cp-official-plan-Map-21_LandUse_AODA.pdf Georeferencing and Reprojecting Data Files The original projection of the PDF maps is unknown but were most likely published using MTM Zone 10 EPSG 2019 as per many of the City of Toronto's many datasets. They could also have possibly been published in UTM Zone 17 EPSG 26917 The TIF images were georeferenced in ArcGIS Pro using this projection with very good results. The images were matched against the City of Toronto's Centreline dataset found here The resulting TIF files and their supporting spatial files include: TOLandUseMap13.tfwx TOLandUseMap13.tif TOLandUseMap13.tif.aux.xml TOLandUseMap13.tif.ovr TOLandUseMap14.tfwx TOLandUseMap14.tif TOLandUseMap14.tif.aux.xml TOLandUseMap14.tif.ovr TOLandUseMap15.tfwx TOLandUseMap15.tif TOLandUseMap15.tif.aux.xml TOLandUseMap15.tif.ovr TOLandUseMap16.tfwx TOLandUseMap16.tif TOLandUseMap16.tif.aux.xml TOLandUseMap16.tif.ovr TOLandUseMap17.tfwx TOLandUseMap17.tif TOLandUseMap17.tif.aux.xml TOLandUseMap17.tif.ovr TOLandUseMap18.tfwx TOLandUseMap18.tif TOLandUseMap18.tif.aux.xml TOLandUseMap18.tif.ovr TOLandUseMap19.tif TOLandUseMap19.tif.aux.xml TOLandUseMap19.tif.ovr TOLandUseMap20.tfwx TOLandUseMap20.tif TOLandUseMap20.tif.aux.xml TOLandUseMap20.tif.ovr TOLandUseMap21.tfwx TOLandUseMap21.tif TOLandUseMap21.tif.aux.xml TOLandUseMap21.tif.ovr TOLandUseMap22.tfwx TOLandUseMap22.tif TOLandUseMap22.tif.aux.xml TOLandUseMap22.tif.ovr TOLandUseMap23.tfwx TOLandUseMap23.tif TOLandUseMap23.tif.aux.xml TOLandUseMap23.tif.ov Ground control points were saved for all georeferenced images. The files are the following: map13.txt map14.txt map15.txt map16.txt map17.txt map18.txt map19.txt map21.txt map22.txt map23.txt The City of Toronto's Property Boundaries shapefile, "property_bnds_gcc_wgs84.zip" were unzipped and also reprojected to EPSG 26917 (UTM Zone 17) into a new shapefile, "Property_Boundaries_UTM.shp" Mosaicing Images Once georeferenced, all images were then mosaiced into one image file, "LandUseMosaic20211220v01", within the project-generated Geodatabase, "Landuse.gdb" and exported TIF, "LandUseMosaic20211220.tif" Reclassifying Images Because the original images were of low quality and the conversion to TIF made the image colours even more inconsistent, a method was required to reclassify the images so that different land use classes could be identified. Using Deep learning Objects, the images were re-classified into useful consistent colours. Deep Learning Objects and Training The resulting mosaic was then prepared for reclassification using the Label Objects for Deep Learning tool in ArcGIS Pro. A training sample, "LandUseTrainingSamples20211220", was created in the geodatabase for all land use types as follows: Neighbourhoods Insitutional Natural Areas Core Employment Areas Mixed Use Areas Apartment Neighbourhoods Parks Roads Utility Corridors Other Open Spaces General Employment Areas Regeneration Areas Lettering (not a land use type, but an image colour (black), used to label streets). By identifying the letters, it then made the reclassification and vectorization results easier to clean up of unnecessary clutter caused by the labels of streets. Reclassification Once the... Visit https://dataone.org/datasets/sha256%3A3e3f055bf6281f979484f847d0ed5eeb96143a369592149328c370fe5776742b for complete metadata about this dataset.

  18. M

    GDRS Manager

    • gisdata.mn.gov
    • data.wu.ac.at
    windows_app
    Updated Dec 5, 2024
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    Natural Resources Department (2024). GDRS Manager [Dataset]. https://gisdata.mn.gov/dataset/gdrsmanager
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    windows_appAvailable download formats
    Dataset updated
    Dec 5, 2024
    Dataset provided by
    Natural Resources Department
    Description

    A Geospatial Data Resource Site (GDRS) is a structured collection of GIS apps and data used as the data structure that supports the Minnesota Geospatial Commons (MGC) and MNDNR Quick Layers (for ArcGIS Pro and ArcMap). The GDRS Manager application allows anyone to create their own local GDRS, either to be shared on an organization's network drive or to use offline. There is no installation for the GDRSManager. Simply download the application and double-click the executable file to run it. Current version: 1.0.0.44

    Use https://resources.gisdata.mn.gov/pub/gdrs as the source GDRS to access the full public data from the MGC. Copy everything or select which datasets you want to copy to a local GDRS destination. If you have disk space or download speed limiations, sorting the resources by size and unselecting the largest resources is a quick way to reduce the size of a the GDRS but still have access to most of the resources.

    Once you have a GDRS set up, run the application again whenever you want to update existing datasets or add additional datasets. You can even keep your data current by scheduling automatic updates to run gdrsmanager.exe through a bat file. For your reference, a template bat file gdrsmanager_console.bat is included in the application download. Just make sure to update the bat file to include the path to your copy of GDRS Manager, and schedule the bat file to run as desired.

    The application download includes a comprehensive help document, which you can also access separately here:
    gdrsmanager_quicklayers_Pro_help.pdf
    gdrsmanager_quicklayers_help.pdf (ArcMap)

  19. a

    LandmarkNameAlias

    • hub.arcgis.com
    Updated Jun 23, 2025
    + more versions
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    New Jersey Office of GIS (2025). LandmarkNameAlias [Dataset]. https://hub.arcgis.com/datasets/newjersey::landmarknamealias-1/explore
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    New Jersey Office of GIS
    Area covered
    Description

    Statewide Download (FGDB) (SHP)Users can also download smaller geographic areas of this feature service in ArcGIS Pro using the Copy Features geoprocessing tool. The address service contains statewide address points and related landmark name alias table and street name alias table.The New Jersey Office of Information Technology, Office of GIS (NJOGIS), in partnership with several local GIS and public safety agencies, has built a comprehensive statewide NG9-1-1 database meeting and exceeding the requirements of the National Emergency Number Association (NENA) 2018 NG9-1-1 GIS Data Standard (NENA-STA-006.1-2018). The existing New Jersey Statewide Address Point data last published in 2016 has been transformed in the NENA data model to create this new address point data.The initial address points were processed from statewide parcel records joined with the statewide Tax Assessor's (MOD-IV) database in 2015. Address points supplied by Monmouth County, Sussex County, Morris County and Montgomery Township in Somerset County were incorporated into the statewide address points using customized Extract, Transform and Load (ETL) procedures.The previous version of the address points was loaded into New Jersey's version of the NENA NG9-1-1 data model using Extract, Transform and Load (ETL) procedures created with Esri's Data Interoperability Extension. Subsequent manual and bulk processing corrections and additions have been made, and are ongoing.***NOTE*** For users who incorporate NJOGIS services into web maps and/or web applications, please sign up for the NJ Geospatial Forum discussion listserv for early notification of service changes. Visit https://nj.gov/njgf/about/listserv/ for more information.

  20. h

    Affordable Rental Housing Inventory - HHFDC

    • geoportal.hawaii.gov
    • opendata.hawaii.gov
    Updated Mar 21, 2023
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    Hawaii Statewide GIS Program (2023). Affordable Rental Housing Inventory - HHFDC [Dataset]. https://geoportal.hawaii.gov/datasets/affordable-rental-housing-inventory-hhfdc
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    Dataset updated
    Mar 21, 2023
    Dataset authored and provided by
    Hawaii Statewide GIS Program
    Area covered
    Description

    [Metadata] Inventory of the State of Hawaii’s affordable housing projects as of February 2023. The list includes affordable housing projects owned by private, non-profit, or governmental entities, developed with funding or support from federal, state or county resources. Data was downloaded from the HHFDC website (https://dbedt.hawaii.gov/hhfdc/affordable-housing-inventory/affordable-rental-housing-inventory/) in PDF format by Hawaii Statewide GIS Program staff, converted to Excel and geocoded in ArcGIS Pro. Projects with no addresses were not included. Data updates are posted periodically on the HHFDC website; users should check the site for the latest copy of the PDF file. For more information, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/Afford_Rent_Hsng_Inv_HHFDC.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

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ArcGIS Living Atlas Team (2022). 3D People ArcGIS Pro Style [Dataset]. https://hub.arcgis.com/content/5d79e5ace56d4aaaba1dbf9176b5effc

3D People ArcGIS Pro Style

Explore at:
Dataset updated
Jun 7, 2022
Dataset authored and provided by
ArcGIS Living Atlas Team
Description

A style containing 34 assorted 3D people models for use in large-scale visualizations, providing vertical context.To Match Layer Symbology to Style in ArcGIS Pro, populate a person_type text field to match the values shown below. Next, copy these values to a table, then join the height value(s) to the people points for use in pop-ups or charts. person_type name height_m height_feet height_inches

Man 1 Gerald 1.7899 5 10.47

Man 2 Ethan 1.8879 6 2.33

Man 3 Cliff 1.7015 5 6.99

Man 4 Dustin 1.7965 5 10.73

Man 5 Jorge 1.8787 6 1.96

Man 6 Phillip 1.6752 5 5.95

Man 7 Dmitri 1.71 5 7.32

Man 8 Luke 1.793 5 10.59

Man 9 Carlos 1.7028 5 7.04

Man 10 Jimmy 1.7625 5 9.39

Man 11 Helmut 1.8331 6 0.17

Man 12 Guy 1.812 5 11.34

Man 13 Leon 1.8219 5 11.73

Man 14 Matthias 1.753 5 9.02

Man 15 Kendrick 1.8787 6 1.96

Man 16 Seth 1.8272 5 11.94

Man 17 Gomer 1.8982 6 2.73

Man 18 Robert 1.7853 5 10.29

Man 19 Jack 1.779 5 10.04

Man 20 Andy 1.8794 6 1.99

Man 21 Hamish 1.67 5 5.75

Man 22 Felix 1.86 6 1.23

Man 23 Adrian 1.75 5 8.90

Woman 1 Greta 1.5371 5 0.52

Woman 2 Simone 1.6366 5 4.43

Woman 3 Alison 1.679 5 6.10

Woman 4 Felicia 1.7433 5 8.63

Woman 5 Jessica 1.7322 5 8.20

Woman 6 Claire 1.6405 5 4.59

Woman 7 Maude 1.7795 5 10.06

Woman 8 Jenny 1.659 5 5.31

Woman 9 Diane 1.67 5 5.75

Woman 10 Carla 1.75 5 8.90

Woman 11 Lauren 1.69 5 6.54

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