96 datasets found
  1. B

    Residential Schools Locations Dataset (Geodatabase)

    • borealisdata.ca
    • search.dataone.org
    Updated May 31, 2019
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    Rosa Orlandini (2019). Residential Schools Locations Dataset (Geodatabase) [Dataset]. http://doi.org/10.5683/SP2/JFQ1SZ
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 31, 2019
    Dataset provided by
    Borealis
    Authors
    Rosa Orlandini
    License

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

    Time period covered
    Jan 1, 1863 - Jun 30, 1998
    Area covered
    Canada
    Description

    The Residential Schools Locations Dataset in Geodatabase format (IRS_Locations.gbd) contains a feature layer "IRS_Locations" that contains the locations (latitude and longitude) of Residential Schools and student hostels operated by the federal government in Canada. All the residential schools and hostels that are listed in the Residential Schools Settlement Agreement are included in this dataset, as well as several Industrial schools and residential schools that were not part of the IRRSA. This version of the dataset doesn’t include the five schools under the Newfoundland and Labrador Residential Schools Settlement Agreement. The original school location data was created by the Truth and Reconciliation Commission, and was provided to the researcher (Rosa Orlandini) by the National Centre for Truth and Reconciliation in April 2017. The dataset was created by Rosa Orlandini, and builds upon and enhances the previous work of the Truth and Reconcilation Commission, Morgan Hite (creator of the Atlas of Indian Residential Schools in Canada that was produced for the Tk'emlups First Nation and Justice for Day Scholar's Initiative, and Stephanie Pyne (project lead for the Residential Schools Interactive Map). Each individual school location in this dataset is attributed either to RSIM, Morgan Hite, NCTR or Rosa Orlandini. Many schools/hostels had several locations throughout the history of the institution. If the school/hostel moved from its’ original location to another property, then the school is considered to have two unique locations in this dataset,the original location and the new location. For example, Lejac Indian Residential School had two locations while it was operating, Stuart Lake and Fraser Lake. If a new school building was constructed on the same property as the original school building, it isn't considered to be a new location, as is the case of Girouard Indian Residential School.When the precise location is known, the coordinates of the main building are provided, and when the precise location of the building isn’t known, an approximate location is provided. For each residential school institution location, the following information is provided: official names, alternative name, dates of operation, religious affiliation, latitude and longitude coordinates, community location, Indigenous community name, contributor (of the location coordinates), school/institution photo (when available), location point precision, type of school (hostel or residential school) and list of references used to determine the location of the main buildings or sites. Access Instructions: there are 47 files in this data package. Please download the entire data package by selecting all the 47 files and click on download. Two files will be downloaded, IRS_Locations.gbd.zip and IRS_LocFields.csv. Uncompress the IRS_Locations.gbd.zip. Use QGIS, ArcGIS Pro, and ArcMap to open the feature layer IRS_Locations that is contained within the IRS_Locations.gbd data package. The feature layer is in WGS 1984 coordinate system. There is also detailed file level metadata included in this feature layer file. The IRS_locations.csv provides the full description of the fields and codes used in this dataset.

  2. World Cities

    • hub.arcgis.com
    • data.lojic.org
    • +4more
    Updated Jun 30, 2013
    + more versions
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    Esri (2013). World Cities [Dataset]. https://hub.arcgis.com/datasets/esri::world-cities/explore
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    Dataset updated
    Jun 30, 2013
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This world cities layer presents the locations of many cities of the world, both major cities and many provincial capitals.Population estimates are provided for those cities listed in open source data from the United Nations and US Census.

  3. Trees

    • cacgeoportal.com
    • hub.arcgis.com
    Updated Feb 1, 2019
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    Esri (2019). Trees [Dataset]. https://www.cacgeoportal.com/datasets/esri::trees
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    Dataset updated
    Feb 1, 2019
    Dataset authored and provided by
    Esrihttp://esri.com/
    License

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

    Area covered
    Description

    This layer features special areas of interest (AOIs) that have been contributed to Esri Community Maps using the new Community Maps Editor app. The data that is accepted by Esri will be included in selected Esri basemaps, including our suite of Esri Vector Basemaps, and made available through this layer to export and use offline. Export DataThe contributed data is also available for contributors and other users to export (or extract) and re-use for their own purposes. Users can export the full layer from the ArcGIS Online item details page by clicking the Export Data button and selecting one of the supported formats (e.g. shapefile, or file geodatabase (FGDB)). User can extract selected layers for an area of interest by opening in Map Viewer, clicking the Analysis button, viewing the Manage Data tools, and using the Extract Data tool. To display this data with proper symbology and metadata in ArcGIS Pro, you can download and use this layer file.Data UsageThe data contributed through the Community Maps Editor app is primarily intended for use in the Esri Basemaps. Esri staff will periodically (e.g. weekly) review the contents of the contributed data and either accept or reject the data for use in the basemaps. Accepted features will be added to the Esri basemaps in a subsequent update and will remain in the app for the contributor or others to edit over time. Rejected features will be removed from the app.Esri Community Maps Contributors and other ArcGIS Online users can download accepted features from this layer for their internal use or map publishing, subject to the terms of use below.

  4. d

    Grocery Store Locations

    • catalog.data.gov
    • ozmarketplace.dc.gov
    • +3more
    Updated May 21, 2025
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    Office of the Chief Technology Officer (2025). Grocery Store Locations [Dataset]. https://catalog.data.gov/dataset/grocery-store-locations
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    Dataset updated
    May 21, 2025
    Dataset provided by
    Office of the Chief Technology Officer
    Description

    To create this layer, OCTO staff used ABCA's definition of “Full-Service Grocery Stores” (https://abca.dc.gov/page/full-service-grocery-store#gsc.tab=0)– pulled from the Food System Assessment below), and using those criteria, determined locations that fulfilled the categories in section 1 of the definition.Then, staff reviewed the Office of Planning’s Food System Assessment (https://dcfoodpolicycouncilorg.files.wordpress.com/2019/06/2018-food-system-assessment-final-6.13.pdf) list in Appendix D, comparing that to the created from the ABCA definition, which led to the addition of a additional examples that meet, or come very close to, the full-service grocery store criteria. The explanation from Office of Planning regarding how the agency created their list:“To determine the number of grocery stores in the District, we analyzed existing business licenses in the Department of Consumer and Regulatory Affairs (2018) Business License Verification system (located at https://eservices.dcra.dc.gov/BBLV/Default.aspx). To distinguish grocery stores from convenience stores, we applied the Alcohol Beverage and Cannabis Administration’s (ABCA) definition of a full-service grocery store. This definition requires a store to be licensed as a grocery store, sell at least six different food categories, dedicate either 50% of the store’s total square feet or 6,000 square feet to selling food, and dedicate at least 5% of the selling area to each food category. This definition can be found at https://abca.dc.gov/page/full-service-grocery-store#gsc.tab=0. To distinguish small grocery stores from large grocery stores, we categorized large grocery stores as those 10,000 square feet or more. This analysis was conducted using data from the WDCEP’s Retail and Restaurants webpage (located at https://wdcep.com/dc-industries/retail/) and using ARCGIS Spatial Analysis tools when existing data was not available. Our final numbers differ slightly from existing reports like the DC Hunger Solutions’ Closing the Grocery Store Gap and WDCEP’s Grocery Store Opportunities Map; this difference likely comes from differences in our methodology and our exclusion of stores that have closed.”Staff also conducted a visual analysis of locations and relied on personal experience of visits to locations to determine whether they should be included in the list.

  5. 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.

  6. g

    Esri ArcGIS Server GEOPROCESSING SERVICE Esri ArcGIS Server - SkyLineGraph...

    • gimi9.com
    Updated Nov 2, 2016
    + more versions
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    (2016). Esri ArcGIS Server GEOPROCESSING SERVICE Esri ArcGIS Server - SkyLineGraph DMR 4G [Dataset]. https://gimi9.com/dataset/eu_cz-cuzk-gp_sky-dmr4g/
    Explore at:
    Dataset updated
    Nov 2, 2016
    License

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

    Description

    Geoprocessing service Esri ArcGIS Server - SkyLineGraph_DMR 4G is a public service intended for visibility analysis execution using the dataset Digital Terrain Model of the Czech Republic of the 4th generation (DMR 4G). Geoprocessing service enables to find out, which area is visible from chosen observer location to defined distance. When using the service is necessary to choose the observer location, specify oberver offset above the terrain and define the distance, in which the visibility analysis is demanded. The result of the analysis is visibility field (area) represented by polygons, which delimit visible parts of the terrain. The geoprocessing service is published as asynchronous. The result is passed on client throught Result Map Service Visibility_DMR 4G (MapService). The result can be downloaded from server and saved to a local disc as shapefile using URL, which is generated and sended by the geoprocessing service. URL for the result download throught a web client is published in running service record, that is sent from server to the client.

  7. e

    Esri ArcGIS Server GEOPROCESSING SERVICE Esri ArcGIS Server - Visibility DMP...

    • data.europa.eu
    esri_gp
    Updated Nov 2, 2016
    + more versions
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    (2016). Esri ArcGIS Server GEOPROCESSING SERVICE Esri ArcGIS Server - Visibility DMP 1G [Dataset]. https://data.europa.eu/data/datasets/cz-cuzk-gp_vis-dmp1g
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    esri_gpAvailable download formats
    Dataset updated
    Nov 2, 2016
    Description

    Geoprocessing service Esri ArcGIS Server - Visibility_DMP 1G is a public service intended for visibility analysis execution using the dataset Digital Surface Model of the Czech Republic of the 1st generation (DMP 1G). Geoprocessing service enables to find out, which area is visible from chosen observer location to defined distance. When using the service is necessary to choose the observer location, specify oberver offset above the terrain and define the distance, in which the visibility analysis is demanded. The result of the analysis is visibility field (area) represented by polygons, which delimit visible parts of the terrain.

    The geoprocessing service is published as asynchronous. The result is passed on client throught Result Map Service Visibility_DMP 1G (MapService). The result can be downloaded from server and saved to a local disc as shapefile using URL, which is generated and sended by the geoprocessing service. URL for the result download throught a web client is published in running service record, that is sent from server to the client.

  8. World Ocean Base

    • amerigeo.org
    • oceangis.esri.de
    • +15more
    Updated Feb 25, 2014
    + more versions
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    Esri (2014). World Ocean Base [Dataset]. https://www.amerigeo.org/datasets/esri::world-ocean-base
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    Dataset updated
    Feb 25, 2014
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    The map is designed to be used as a basemap by marine GIS professionals and as a reference map by anyone interested in ocean data. The basemap focuses on bathymetry. It also includes inland waters and roads, overlaid on land cover and shaded relief imagery.The Ocean Base map currently provides coverage for the world down to a scale of ~1:577k; coverage down to ~1:72k in United States coastal areas and various other areas; and coverage down to ~1:9k in limited regional areas.The World Ocean Reference is designed to be drawn on top of this map and provides selected city labels throughout the world. This web map lets you view the World Ocean Base with the Reference service drawn on top. Article in the Fall 2011 ArcUser about this basemap: "A Foundation for Ocean GIS".The map was compiled from a variety of best available sources from several data providers, including General Bathymetric Chart of the Oceans GEBCO_08 Grid version 20100927 and IHO-IOC GEBCO Gazetteer of Undersea Feature Names August 2010 version (https://www.gebco.net), National Oceanic and Atmospheric Administration (NOAA) and National Geographic for the oceans; and Garmin, and Esri for topographic content. You can contribute your bathymetric data to this service and have it served by Esri for the benefit of the Ocean GIS community. For details on the users who contributed bathymetric data for this map via the Community Maps Program, view the list of Contributors for the Ocean Basemap. The basemap was designed and developed by Esri. The GEBCO_08 Grid is largely based on a database of ship-track soundings with interpolation between soundings guided by satellite-derived gravity data. In some areas, data from existing grids are included. The GEBCO_08 Grid does not contain detailed information in shallower water areas, information concerning the generation of the grid can be found on GEBCO's website: https://www.gebco.net/data_and_products/gridded_bathymetry_data/. The GEBCO_08 Grid is accompanied by a Source Identifier (SID) Grid which indicates which cells in the GEBCO_08 Grid are based on soundings or existing grids and which have been interpolated. The latest version of both grids and accompanying documentation is available to download, on behalf of GEBCO, from the British Oceanographic Data Centre (BODC) https://www.bodc.ac.uk/data/online_delivery/gebco/.The names of the IHO (International Hydrographic Organization), IOC (intergovernmental Oceanographic Commission), GEBCO (General Bathymetric Chart of the Oceans), NERC (Natural Environment Research Council) or BODC (British Oceanographic Data Centre) may not be used in any way to imply, directly or otherwise, endorsement or support of either the Licensee or their mapping system.Tip: Here are some famous oceanic locations as they appear this map. Each URL launches this map at a particular location via parameters specified in the URL: Challenger Deep, Galapagos Islands, Hawaiian Islands, Maldive Islands, Mariana Trench, Tahiti, Queen Charlotte Sound, Notre Dame Bay, Labrador Trough, New York Bight, Massachusetts Bay, Mississippi Sound

  9. 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.

  10. e

    Esri ArcGIS Server GEOPROCESSING SERVICE Esri ArcGIS Server - Visibility DMR...

    • data.europa.eu
    • gimi9.com
    esri_gp
    Updated Nov 1, 2016
    + more versions
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    (2016). Esri ArcGIS Server GEOPROCESSING SERVICE Esri ArcGIS Server - Visibility DMR 5G [Dataset]. https://data.europa.eu/data/datasets/cz-cuzk-gp_vis-dmr5g
    Explore at:
    esri_gpAvailable download formats
    Dataset updated
    Nov 1, 2016
    Description

    Geoprocessing service Esri ArcGIS Server - Visibility_DMR 5G is a public service intended for visibility analysis execution using the dataset Digital Terrain Model of the Czech Republic of the 5th generation (DMR 5G). Geoprocessing service enables to find out, which area is visible from chosen observer location to defined distance. When using the service is necessary to choose the observer location, pecify oberver offset above the terrain and define the distance, in which the visibility analysis is demanded. The result of the analysis is visibility field (area) represented by polygons, which delimit visible parts of the terrain.

    The geoprocessing service is published as asynchronous. The result is passed on client throught Result Map Service Visibility_DMR 5G (MapService). The result can be downloaded from server and saved to a local disc as shapefile using URL, which is generated and sended by the geoprocessing service. URL for the result download throught a web client is published in running service record, that is sent from server to the client.

  11. C

    DSM2 Georeferenced Model Grid

    • data.cnra.ca.gov
    • data.ca.gov
    Updated Jun 2, 2025
    + more versions
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    California Department of Water Resources (2025). DSM2 Georeferenced Model Grid [Dataset]. https://data.cnra.ca.gov/dataset/dsm2-georeferenced-model-grid
    Explore at:
    pdf(22679496), arcgis desktop map package(300515), zip(158973), pdf(22669649), zip(159621), pdf(20463896), zip(228604), arcgis desktop map package(211110), arcgis pro map package(153901), zip(26881), pdf(25962387), pdf(1443441), zip(140121)Available download formats
    Dataset updated
    Jun 2, 2025
    Dataset authored and provided by
    California Department of Water Resources
    Description

    ArcGIS and QGIS map packages, with ESRI shapefiles for the DSM2 Model Grid. These are not finalized products. Locations in these shapefiles are approximate.

    Monitoring Stations - shapefile with approximate locations of monitoring stations.

    DSM2 Grid 2025-05-28 Historical

    FC_2023.01

    DSM2 v8.2.0, calibrated version:

    • dsm2_8_2_grid_map_calibrated.mpkx - ArcGIS Pro map package containing all layers and symbology for the calibrated grid map.
    • dsm2_8_2_grid_map_calibrated.mpk - ArcGIS Desktop map package containing all layers and symbology for the calibrated grid map.
    • dsm2_8_2_0_calibrated_grid_map_qgis.zip - QGIS map package containing all layers and symbology for the calibrated grid map.
    • dsm2_8_2_0_calibrated_gridmap_shapefiles.zip - A zip file containing all the shapefiles used in the above map packages:
    • dsm2_8_2_0_calibrated_channels_centerlines - channel centerlines, follwing the path of CSDP centerlines
    • dsm2_8_2_0_calibrated_network_channels - channels represented by straight line segments which are connected the upstream and downstream nodes
    • dsm2_8_2_0_calibrated_nodes - DSM2 nodes
    • dsm2_8_2_0_calibrated_dcd_only_nodes - Nodes that are only used by DCD
    • dsm2_8_2_0_calibrated_and_dcd_nodes - Nodes that are shared by DSM2 and DCD
    • dsm2_8_2_0_calibrated_and_smcd_nodes - Nodes that are shared by DSM2 and SMCD
    • dsm2_8_2_0_calibrated_gates_actual_loc - The approximate actual locations of each gate in DSM2
    • dsm2_8_2_0_calibrated_gates_grid_loc - The locations of each gate in the DSM2 model grid
    • dsm2_8_2_0_calibrated_reservoirs - The approximate locations of the reservoirs in DSM2
    • dsm2_8_2_0_calibrated_reservoir_connections - Lines showing connections from reservoirs to nodes in DSM2

    DSM2 v8.2.1, historical version:

    • DSM2 v8.2.1, historical version grid map release notes (PDF), updated 7/12/2022
    • DSM2 v8.2.1, historical version grid map, single zoom level (PDF)
    • DSM2 v8.2.1, historical version grid map, multiple zoom levels (PDF) - PDF grid map designed to be printed on 3 foot wide plotter paper.
    • DSM2 v8.2.1, historical version map package for ArcGIS Desktop: A map package for ArcGIS Desktop containing the grid map layers with symbology.
    • DSM2 v8.2.1, historical version grid map shapefiles (zip): A zip file containing the shapefiles used in the grid map.

    Change Log

    7/12/2022: The document "DSM2 v8.2.1, historical version grid map release notes (PDF)" was corrected by removing section 4.4, which incorrectly stated that the grid included channels 710-714, representing the Toe Drain, and that the Yolo Flyway restoration area was included.

  12. World Transportation

    • wifire-data.sdsc.edu
    csv, esri rest +4
    Updated Jun 9, 2021
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    Esri (2021). World Transportation [Dataset]. https://wifire-data.sdsc.edu/dataset/world-transportation
    Explore at:
    geojson, kml, esri rest, csv, zip, htmlAvailable download formats
    Dataset updated
    Jun 9, 2021
    Dataset provided by
    Esrihttp://esri.com/
    Area covered
    World
    Description

    This map presents transportation data, including highways, roads, railroads, and airports for the world.

    The map was developed by Esri using Esri highway data; Garmin basemap layers; HERE street data for North America, Europe, Australia, New Zealand, South America and Central America, India, most of the Middle East and Asia, and select countries in Africa. Data for Pacific Island nations and the remaining countries of Africa was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view.

    You can add this layer on top of any imagery, such as the Esri World Imagery map service, to provide a useful reference overlay that also includes street labels at the largest scales. (At the largest scales, the line symbols representing the streets and roads are automatically hidden and only the labels showing the names of streets and roads are shown). Imagery With Labels basemap in the basemap dropdown in the ArcGIS web and mobile clients does not include this World Transportation map. If you use the Imagery With Labels basemap in your map and you want to have road and street names, simply add this World Transportation layer into your map. It is designed to be drawn underneath the labels in the Imagery With Labels basemap, and that is how it will be drawn if you manually add it into your web map.

  13. Landmarks and Government Buildings

    • hub.arcgis.com
    • gisnation-sdi.hub.arcgis.com
    Updated Jun 30, 2021
    + more versions
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    Esri U.S. Federal Datasets (2021). Landmarks and Government Buildings [Dataset]. https://hub.arcgis.com/maps/462b08b0811c4a77aa09afc36c4f4b73
    Explore at:
    Dataset updated
    Jun 30, 2021
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri U.S. Federal Datasets
    License

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

    Area covered
    Description

    Landmarks and Government BuildingsThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Geological Survey, displays Cemeteries, Post Offices, City/Town Halls, Courthouses, State Capitols, State Supreme Courts, The White House, U.S. Capitol, U.S. Supreme Court, Historic Sites/Points of Interest, and National Symbols/Monuments in the U.S. Per the USGS, "Structures data are designed to be used in general mapping and in the analysis of structure related activities using geographic information system technology. The National Map structures data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and transportation, to produce general reference base maps. The types of structures collected are largely determined by the needs of disaster planning and emergency response, and homeland security organizations."Supreme Court of WyomingData currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Landmarks & Government Buildings) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 135 (USGS National Structures Dataset - USGS National Map Downloadable Data Collection)OGC API Features Link: (Landmark Structures - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: The National MapFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Real Property Theme Community. Per the Federal Geospatial Data Committee (FGDC), Real Property is defined as "the spatial representation (location) of real property entities, typically consisting of one or more of the following: unimproved land, a building, a structure, site improvements and the underlying land. Complex real property entities (that is "facilities") are used for a broad spectrum of functions or missions. This theme focuses on spatial representation of real property assets only and does not seek to describe special purpose functions of real property such as those found in the Cultural Resources, Transportation, or Utilities themes."For other NGDA Content: Esri Federal Datasets

  14. Esri Data & Maps

    • datacore-gn.unepgrid.ch
    ogc:wms +1
    Updated Apr 30, 2011
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    International Boundaries Polygons Level 0 - ESRI (2011). Esri Data & Maps [Dataset]. https://datacore-gn.unepgrid.ch/geonetwork/srv/api/records/bf950e93-8157-4e8e-ab97-01ed6ca5fad5
    Explore at:
    www:link-1.0-http--link, ogc:wmsAvailable download formats
    Dataset updated
    Apr 30, 2011
    Dataset provided by
    Esrihttp://esri.com/
    Time period covered
    2014
    Area covered
    Description

    World Countries is a detailed dataset of country level boundaries which can be used at both large and small scales. It has been designed to be used as a basemap and includes an additional Disputed Boundaries layer that can be used to edit boundaries to fit a users needs and view of the political world.

    Included are attributes for local and official names and country codes, along with continent and display fields. Particularly useful are the Land_Type and Land_Rank fields which separate polygons based on their size. These attributes can be used for rendering at different scales by providing the ability to turn off small islands which may clutter small scale views.

  15. e

    Sentinel-2 Land Cover Explorer

    • climate.esri.ca
    • cacgeoportal.com
    • +3more
    Updated Feb 7, 2023
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    Esri (2023). Sentinel-2 Land Cover Explorer [Dataset]. https://climate.esri.ca/datasets/esri::sentinel-2-land-cover-explorer
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    Dataset updated
    Feb 7, 2023
    Dataset authored and provided by
    Esri
    License

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

    Description

    About the dataLand use land cover (LULC) maps are an increasingly important tool for decision-makers in many industry sectors and developing nations around the world. The information provided by these maps helps inform policy and land management decisions by better understanding and quantifying the impacts of earth processes and human activity.ArcGIS Living Atlas of the World provides a detailed, accurate, and timely LULC map of the world. The data is the result of a three-way collaboration among Esri, Impact Observatory, and Microsoft. For more information about the data, see Sentinel-2 10m Land Use/Land Cover Time Series.About the appOne of the foremost capabilities of this app is the dynamic change analysis. The app provides dynamic visual and statistical change by comparing annual slices of the Sentinel-2 10m Land Use/Land Cover data as you explore the map.Overview of capabilities:Visual change analysis with either 'Step Mode' or 'Swipe Mode'Dynamic statistical change analysis by year, map extent, and classFilter by selected land cover classRegional class statistics summarized by administrative boundariesImagery mode for visual investigation and validation of land coverSelect imagery renderings (e.g. SWIR to visualize forest burn scars)Data download for offline use

  16. M

    DNR QuickLayers for ArcGIS 10

    • gisdata.mn.gov
    • data.wu.ac.at
    esri_addin
    Updated Jul 2, 2025
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    Natural Resources Department (2025). DNR QuickLayers for ArcGIS 10 [Dataset]. https://gisdata.mn.gov/dataset/quick-layers
    Explore at:
    esri_addinAvailable download formats
    Dataset updated
    Jul 2, 2025
    Dataset provided by
    Natural Resources Department
    Description

    The way to access Layers Quickly.

    Quick Layers is an Add-In for ArcMap 10.6+ 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: 1.164

    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) 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 ArcMap
    2. Customize -> Add-In Manager… -> Options
    3. Click add folder, and enter the location of the Quick Layers 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
    4. After you do this, the Quick Layers toolbar will be available. To add it, go to Customize -> Toolbars and select DNR Quick Layers 10

    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.

  17. OpenStreetMap 3D Trees (Realistic)

    • hub.arcgis.com
    • cacgeoportal.com
    • +2more
    Updated Jun 10, 2022
    + more versions
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    Esri (2022). OpenStreetMap 3D Trees (Realistic) [Dataset]. https://hub.arcgis.com/maps/33383da8a75f4d24b4b6a0d0532abe6e
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    Dataset updated
    Jun 10, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    Important Note: This item is in mature support as of December 2024. See blog for more information.This 3D scene layer presents OpenStreetMap (OSM) trees data hosted by Esri. Esri created buildings and trees scene layers from the OSM Daylight map distribution, which is supported by Facebook and others. The Daylight map distribution has been sunsetted and data updates supporting this layer are no longer available. You can visit openstreetmap.maps.arcgis.com to explore a collection of maps, scenes, and layers featuring OpenStreetMap data in ArcGIS. You can review the 3D Scene Layers Documentation to learn more about how the building and tree features in OSM are modeled and rendered in the 3D scene layers, and see tagging recommendations to get the best results.OpenStreetMap 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.Note: This layer is supported in Scene Viewer and ArcGIS Pro 3.0 or higher.

  18. N

    School Point Locations

    • data.cityofnewyork.us
    • s.cnmilf.com
    • +3more
    application/rdfxml +5
    Updated Sep 22, 2011
    + more versions
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    Department of Education (DOE) (2011). School Point Locations [Dataset]. https://data.cityofnewyork.us/Education/School-Point-Locations/jfju-ynrr
    Explore at:
    tsv, application/rssxml, xml, csv, application/rdfxml, jsonAvailable download formats
    Dataset updated
    Sep 22, 2011
    Dataset authored and provided by
    Department of Education (DOE)
    Description

    This is an ESRI shape file of school point locations based on the official address. It includes some additional basic and pertinent information needed to link to other data sources. It also includes some basic school information such as Name, Address, Principal, and Principal’s contact information.

  19. BOEM BSEE Marine Cadastre Layers National Scale - OCS Oil & Gas Pipelines

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Nov 16, 2016
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    US Bureau of Ocean Energy Management (BOEM) (2016). BOEM BSEE Marine Cadastre Layers National Scale - OCS Oil & Gas Pipelines [Dataset]. https://koordinates.com/layer/15435-boem-bsee-marine-cadastre-layers-national-scale-ocs-oil-gas-pipelines/
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    dwg, kml, mapinfo tab, geopackage / sqlite, mapinfo mif, geodatabase, shapefile, csv, pdfAvailable download formats
    Dataset updated
    Nov 16, 2016
    Dataset provided by
    Bureau of Ocean Energy Managementhttp://www.boem.gov/
    Federal government of the United Stateshttp://www.usa.gov/
    Authors
    US Bureau of Ocean Energy Management (BOEM)
    Area covered
    Description

    This dataset is a compilation of available oil and gas pipeline data and is maintained by BSEE. Pipelines are used to transport and monitor oil and/or gas from wells within the outer continental shelf (OCS) to resource collection locations. Currently, pipelines managed by BSEE are found in Gulf of Mexico and southern California waters.

    © MarineCadastre.gov This layer is a component of BOEMRE Layers.

    This Map Service contains many of the primary data types created by both the Bureau of Ocean Energy Management (BOEM) and the Bureau of Safety and Environmental Enforcement (BSEE) within the Department of Interior (DOI) for the purpose of managing offshore federal real estate leases for oil, gas, minerals, renewable energy, sand and gravel. These data layers are being made available as REST mapping services for the purpose of web viewing and map overlay viewing in GIS systems. Due to re-projection issues which occur when converting multiple UTM zone data to a single national or regional projected space, and line type changes that occur when converting from UTM to geographic projections, these data layers should not be used for official or legal purposes. Only the original data found within BOEM/BSEE’s official internal database, federal register notices or official paper or pdf map products may be considered as the official information or mapping products used by BOEM or BSEE. A variety of data layers are represented within this REST service are described further below. These and other cadastre information the BOEM and BSEE produces are generated in accordance with 30 Code of Federal Regulations (CFR) 256.8 to support Federal land ownership and mineral resource management.

    For more information – Contact: Branch Chief, Mapping and Boundary Branch, BOEM, 381 Elden Street, Herndon, VA 20170. Telephone (703) 787-1312; Email: mapping.boundary.branch@boem.gov

    The REST services for National Level Data can be found here: http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE/MMC_Layers/MapServer

    REST services for regional level data can be found by clicking on the region of interest from the following URL: http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE

    Individual Regional Data or in depth metadata for download can be obtained in ESRI Shape file format by clicking on the region of interest from the following URL: http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx

    Currently the following layers are available from this REST location:

    OCS Drilling Platforms -Locations of structures at and beneath the water surface used for the purpose of exploration and resource extraction. Only platforms in federal Outer Continental Shelf (OCS) waters are included. A database of platforms and rigs is maintained by BSEE.

    OCS Oil and Natural Gas Wells -Existing wells drilled for exploration or extraction of oil and/or gas products. Additional information includes the lease number, well name, spud date, the well class, surface area/block number, and statistics on well status summary. Only wells found in federal Outer Continental Shelf (OCS) waters are included. Wells information is updated daily. Additional files are available on well completions and well tests. A database of wells is maintained by BSEE.

    OCS Oil & Gas Pipelines -This dataset is a compilation of available oil and gas pipeline data and is maintained by BSEE. Pipelines are used to transport and monitor oil and/or gas from wells within the outer continental shelf (OCS) to resource collection locations. Currently, pipelines managed by BSEE are found in Gulf of Mexico and southern California waters.

    Unofficial State Lateral Boundaries - The approximate location of the boundary between two states seaward of the coastline and terminating at the Submerged Lands Act Boundary. Because most State boundary locations have not been officially described beyond the coast, are disputed between states or in some cases the coastal land boundary description is not available, these lines serve as an approximation that was used to determine a starting point for creation of BOEM’s OCS Administrative Boundaries. GIS files are not available for this layer due to its unofficial status.

    BOEM OCS Administrative Boundaries - Outer Continental Shelf (OCS) Administrative Boundaries Extending from the Submerged Lands Act Boundary seaward to the Limit of the United States OCS (The U.S. 200 nautical mile Limit, or other marine boundary)For additional details please see the January 3, 2006 Federal Register Notice.

    BOEM Limit of OCSLA ‘8(g)’ zone - The Outer Continental Shelf Lands Act '8(g) Zone' lies between the Submerged Lands Act (SLA) boundary line and a line projected 3 nautical miles seaward of the SLA boundary line. Within this zone, oil and gas revenues are shared with the coastal state(s). The official version of the ‘8(g)’ Boundaries can only be found on the BOEM Official Protraction Diagrams (OPDs) or Supplemental Official Protraction described below.

    Submerged Lands Act Boundary - The SLA boundary defines the seaward limit of a state's submerged lands and the landward boundary of federally managed OCS lands. The official version of the SLA Boundaries can only be found on the BOEM Official Protraction Diagrams (OPDs) or Supplemental Official Protraction Diagrams described below.

    Atlantic Wildlife Survey Tracklines(2005-2012) - These data depict tracklines of wildlife surveys conducted in the Mid-Atlantic region since 2005. The tracklines are comprised of aerial and shipboard surveys. These data are intended to be used as a working compendium to inform the diverse number of groups that conduct surveys in the Mid-Atlantic region.The tracklines as depicted in this dataset have been derived from source tracklines and transects. The tracklines have been simplified (modified from their original form) due to the large size of the Mid-Atlantic region and the limited ability to map all areas simultaneously.The tracklines are to be used as a general reference and should not be considered definitive or authoritative. This data can be downloaded from http://www.boem.gov/uploadedFiles/BOEM/Renewable_Energy_Program/Mapping_and_Data/ATL_WILDLIFE_SURVEYS.zip

    BOEM OCS Protraction Diagrams & Leasing Maps - This data set contains a national scale spatial footprint of the outer boundaries of the Bureau of Ocean Energy Management’s (BOEM’s) Official Protraction Diagrams (OPDs) and Leasing Maps (LMs). It is updated as needed. OPDs and LMs are mapping products produced and used by the BOEM to delimit areas available for potential offshore mineral leases, determine the State/Federal offshore boundaries, and determine the limits of revenue sharing and other boundaries to be considered for leasing offshore waters. This dataset shows only the outline of the maps that are available from BOEM.Only the most recently published paper or pdf versions of the OPDs or LMs should be used for official or legal purposes. The pdf maps can be found by going to the following link and selecting the appropriate region of interest. http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx Both OPDs and LMs are further subdivided into individual Outer Continental Shelf(OCS) blocks which are available as a separate layer. Some OCS blocks that also contain other boundary information are known as Supplemental Official Block Diagrams (SOBDs.) Further information on the historic development of OPD's can be found in OCS Report MMS 99-0006: Boundary Development on the Outer Continental Shelf: http://www.boemre.gov/itd/pubs/1999/99-0006.PDF Also see the metadata for each of the individual GIS data layers available for download. The Official Protraction Diagrams (OPDs) and Supplemental Official Block Diagrams (SOBDs), serve as the legal definition for BOEM offshore boundary coordinates and area descriptions.

    BOEM OCS Lease Blocks - Outer Continental Shelf (OCS) lease blocks serve as the legal definition for BOEM offshore boundary coordinates used to define small geographic areas within an Official Protraction Diagram (OPD) for leasing and administrative purposes. OCS blocks relate back to individual Official Protraction Diagrams and are not uniquely numbered. Only the most recently published paper or pdf

  20. e

    Geodatabase for the Baltimore Ecosystem Study Spatial Data

    • portal.edirepository.org
    • search.dataone.org
    application/vnd.rar
    Updated May 4, 2012
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    Jarlath O'Neal-Dunne; Morgan Grove (2012). Geodatabase for the Baltimore Ecosystem Study Spatial Data [Dataset]. http://doi.org/10.6073/pasta/377da686246f06554f7e517de596cd2b
    Explore at:
    application/vnd.rar(29574980 kilobyte)Available download formats
    Dataset updated
    May 4, 2012
    Dataset provided by
    EDI
    Authors
    Jarlath O'Neal-Dunne; Morgan Grove
    Time period covered
    Jan 1, 1999 - Jun 1, 2014
    Area covered
    Description

    The establishment of a BES Multi-User Geodatabase (BES-MUG) allows for the storage, management, and distribution of geospatial data associated with the Baltimore Ecosystem Study. At present, BES data is distributed over the internet via the BES website. While having geospatial data available for download is a vast improvement over having the data housed at individual research institutions, it still suffers from some limitations. BES-MUG overcomes these limitations; improving the quality of the geospatial data available to BES researches, thereby leading to more informed decision-making.

       BES-MUG builds on Environmental Systems Research Institute's (ESRI) ArcGIS and ArcSDE technology. ESRI was selected because its geospatial software offers robust capabilities. ArcGIS is implemented agency-wide within the USDA and is the predominant geospatial software package used by collaborating institutions.
    
    
       Commercially available enterprise database packages (DB2, Oracle, SQL) provide an efficient means to store, manage, and share large datasets. However, standard database capabilities are limited with respect to geographic datasets because they lack the ability to deal with complex spatial relationships. By using ESRI's ArcSDE (Spatial Database Engine) in conjunction with database software, geospatial data can be handled much more effectively through the implementation of the Geodatabase model. Through ArcSDE and the Geodatabase model the database's capabilities are expanded, allowing for multiuser editing, intelligent feature types, and the establishment of rules and relationships. ArcSDE also allows users to connect to the database using ArcGIS software without being burdened by the intricacies of the database itself.
    
    
       For an example of how BES-MUG will help improve the quality and timeless of BES geospatial data consider a census block group layer that is in need of updating. Rather than the researcher downloading the dataset, editing it, and resubmitting to through ORS, access rules will allow the authorized user to edit the dataset over the network. Established rules will ensure that the attribute and topological integrity is maintained, so that key fields are not left blank and that the block group boundaries stay within tract boundaries. Metadata will automatically be updated showing who edited the dataset and when they did in the event any questions arise.
    
    
       Currently, a functioning prototype Multi-User Database has been developed for BES at the University of Vermont Spatial Analysis Lab, using Arc SDE and IBM's DB2 Enterprise Database as a back end architecture. This database, which is currently only accessible to those on the UVM campus network, will shortly be migrated to a Linux server where it will be accessible for database connections over the Internet. Passwords can then be handed out to all interested researchers on the project, who will be able to make a database connection through the Geographic Information Systems software interface on their desktop computer. 
    
    
       This database will include a very large number of thematic layers. Those layers are currently divided into biophysical, socio-economic and imagery categories. Biophysical includes data on topography, soils, forest cover, habitat areas, hydrology and toxics. Socio-economics includes political and administrative boundaries, transportation and infrastructure networks, property data, census data, household survey data, parks, protected areas, land use/land cover, zoning, public health and historic land use change. Imagery includes a variety of aerial and satellite imagery.
    
    
       See the readme: http://96.56.36.108/geodatabase_SAL/readme.txt
    
    
       See the file listing: http://96.56.36.108/geodatabase_SAL/diroutput.txt
    
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Rosa Orlandini (2019). Residential Schools Locations Dataset (Geodatabase) [Dataset]. http://doi.org/10.5683/SP2/JFQ1SZ

Residential Schools Locations Dataset (Geodatabase)

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
May 31, 2019
Dataset provided by
Borealis
Authors
Rosa Orlandini
License

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

Time period covered
Jan 1, 1863 - Jun 30, 1998
Area covered
Canada
Description

The Residential Schools Locations Dataset in Geodatabase format (IRS_Locations.gbd) contains a feature layer "IRS_Locations" that contains the locations (latitude and longitude) of Residential Schools and student hostels operated by the federal government in Canada. All the residential schools and hostels that are listed in the Residential Schools Settlement Agreement are included in this dataset, as well as several Industrial schools and residential schools that were not part of the IRRSA. This version of the dataset doesn’t include the five schools under the Newfoundland and Labrador Residential Schools Settlement Agreement. The original school location data was created by the Truth and Reconciliation Commission, and was provided to the researcher (Rosa Orlandini) by the National Centre for Truth and Reconciliation in April 2017. The dataset was created by Rosa Orlandini, and builds upon and enhances the previous work of the Truth and Reconcilation Commission, Morgan Hite (creator of the Atlas of Indian Residential Schools in Canada that was produced for the Tk'emlups First Nation and Justice for Day Scholar's Initiative, and Stephanie Pyne (project lead for the Residential Schools Interactive Map). Each individual school location in this dataset is attributed either to RSIM, Morgan Hite, NCTR or Rosa Orlandini. Many schools/hostels had several locations throughout the history of the institution. If the school/hostel moved from its’ original location to another property, then the school is considered to have two unique locations in this dataset,the original location and the new location. For example, Lejac Indian Residential School had two locations while it was operating, Stuart Lake and Fraser Lake. If a new school building was constructed on the same property as the original school building, it isn't considered to be a new location, as is the case of Girouard Indian Residential School.When the precise location is known, the coordinates of the main building are provided, and when the precise location of the building isn’t known, an approximate location is provided. For each residential school institution location, the following information is provided: official names, alternative name, dates of operation, religious affiliation, latitude and longitude coordinates, community location, Indigenous community name, contributor (of the location coordinates), school/institution photo (when available), location point precision, type of school (hostel or residential school) and list of references used to determine the location of the main buildings or sites. Access Instructions: there are 47 files in this data package. Please download the entire data package by selecting all the 47 files and click on download. Two files will be downloaded, IRS_Locations.gbd.zip and IRS_LocFields.csv. Uncompress the IRS_Locations.gbd.zip. Use QGIS, ArcGIS Pro, and ArcMap to open the feature layer IRS_Locations that is contained within the IRS_Locations.gbd data package. The feature layer is in WGS 1984 coordinate system. There is also detailed file level metadata included in this feature layer file. The IRS_locations.csv provides the full description of the fields and codes used in this dataset.

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