71 datasets found
  1. U

    ArcGIS Desktop 10.8.2

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

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

    Description

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

  2. a

    ArcGIS Desktop 10.6.1

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

    Introduction to R Scripting with ArcGIS

    • edu.hub.arcgis.com
    Updated Jan 18, 2025
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    Education and Research (2025). Introduction to R Scripting with ArcGIS [Dataset]. https://edu.hub.arcgis.com/documents/baec6865ffbc4c1c869a594b9cad8bc0
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    Dataset updated
    Jan 18, 2025
    Dataset authored and provided by
    Education and Research
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    This resource was created by Esri Canada Education and Research. To browse our full collection of higher-education learning resources, please visit https://hed.esri.ca/resourcefinder/.This Tutorial consists of four tutorials that deal with integrating the statistical programming language R with ArcGIS for Desktop. Several concepts are covered which include configuring ArcGIS with R, writing basic R scripts, writing R scripts that work with ArcGIS data, and constructing R Tools for use within ArcGIS Pro. It is recommended that the tutorials are completed in sequential order. Each of the four tutorials (as well as a version of this document), can viewed directly from your Web browser by following the links below. However, you must obtain a complete copy of the tutorial files by downloading the latest release (or by cloning the tutorial repository on GitHub) if you wish to follow the tutorials interactively using ArcGIS and R software, along with pre-configured sample data.To download the tutorial documents and datasets, click the Open button to the top right. This will automatically download a ZIP file containing all files and data required.You can also clone the tutorial documents and datasets for this GitHub repo: https://github.com/highered-esricanada/r-arcgis-tutorials.gitSoftware & Solutions Used: ArcGIS Pro 3.4 Internet browser (e.g., Mozilla Firefox, Google Chrome, Safari) R Statistical Computing Language – version 4.3.3 R-ArcGIS Bindings – version 1.0.1.311RStudio Desktop – version 2024.09.0+375Time to Complete: 2.5 h (excludes installation time)File Size: 115 MBDate Created: November 2017Last Updated: December 2024

  4. 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.

  5. a

    OpenStreetMap

    • ethiopia.africageoportal.com
    • data.baltimorecity.gov
    • +32more
    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.

  6. W

    ESRI CS-W Client for ArcGIS

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

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

  7. a

    B CENSUS TRACTS 2010 CDC

    • uscssi.hub.arcgis.com
    Updated Mar 19, 2023
    + more versions
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    Spatial Sciences Institute (2023). B CENSUS TRACTS 2010 CDC [Dataset]. https://uscssi.hub.arcgis.com/maps/USCSSI::b-census-tracts-2010-cdc
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    Dataset updated
    Mar 19, 2023
    Dataset authored and provided by
    Spatial Sciences Institute
    Area covered
    Description

    What is unique about LA County’s data?It is clipped to the ocean boundary. Raw Census data includes a 3 mile buffer into the ocean, which impacts cartography.IMPORTANT! It has been updated to the 2012 Census Geography Update, which merged Tracts 1370.00 and 9304.01 into the combined tract 1370.00. So the CT10 field actually reflects the 2012 Census update, which is used for all population products 2012 and later.How was this data created?This data was downloaded from Census Bureau website: http://www.census.gov/cgi-bin/geo/shapefiles2010/file-download and clipped to the County Boundary using ESRI’s ArcGIS Desktop. Two new fields were added in census tract data – area in square feet and shape length in feet. This dataset has unique identifier field “GEOID10” for each record and the census tract number fields “CT10” and “LABEL” (6-digit number and 6-digit number with decimal point, respectively).

  8. 2016 CLRP Amendment, Data Download

    • rtdc-mwcog.opendata.arcgis.com
    Updated Nov 22, 2016
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    Metropolitan Washington Council of Governments (2016). 2016 CLRP Amendment, Data Download [Dataset]. https://rtdc-mwcog.opendata.arcgis.com/datasets/a5179f6c21464ea580de72f0991c1c11
    Explore at:
    Dataset updated
    Nov 22, 2016
    Dataset authored and provided by
    Metropolitan Washington Council of Governmentshttp://www.mwcog.org/
    Area covered
    Description
    • Click 'More' to view details on this dataset. Download data via the 'Download Dataset' button ** ** Download the ZIP file, not the spreadsheet (empty dataset) ****Data packaged as an ArcGIS Map Package; available for download and use in ArcGIS Desktop version 10.x**Download Map Package file:The dataset is shared as a ZIP file (2016CLRP_data.zip). Save this file in your preferred location. Unzip the downloaded file and you will see the Map Package, 2016CLRP_data.mpk. Adding GIS Data to ArcMap from a Map Package:To load the .mpk file if saved locally: From Windows Explorer1. Browse to the location of the .mpk file. 2. Double-click the file to launch ArcMap and unpack all the data in the package. From ArcCatalog1. Browse to the location of the .mpk file. 2. Right-click the file, and select Unpack. This action launches ArcMap and unpacks the data in the package. The process is the same if you are using ArcCatalog from within ArcMap.Note: The .mpk file cannot be opened within ArcMap.Regardless of where the .mpk file is stored originally, the data within the map package when unpacked saves on your hard drive in the Documents and Settings folder:C:\Documents_and_Settings\MyDocuments\ArcGIS\Packages*.gdbWhat is the CLRP?The CLRP identifies all of the regionally significant capital improvements to the region’s highway and transit systems that area transportation agencies expect to make and to be able to afford over the next 20 plus years. It also outlines all anticipated spending on operations and maintenance of the current and future transportation system over the same time frame. Over 500 projects are included, ranging from simple highway landscaping to billion-dollar highway and transit projects. Some of the projects will be completed in the near future, while others are only in the initial planning stage.For more information on the CLRP, visit the TPB's CLRP webpage.To see the latest CLRP news, click here.
  9. USGS Historical Topographic Map Explorer

    • data.amerigeoss.org
    • hub.arcgis.com
    Updated Oct 10, 2019
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    Esri (2019). USGS Historical Topographic Map Explorer [Dataset]. https://data.amerigeoss.org/dataset/usgs-historical-topographic-map-explorer1
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    html, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    Oct 10, 2019
    Dataset provided by
    Esrihttp://esri.com/
    Description

    The ArcGIS Online US Geological Survey (USGS) topographic map collection now contains over 177,000 historical quadrangle maps dating from 1882 to 2006. The USGS Historical Topographic Map Explorer app brings these maps to life through an interface that guides users through the steps for exploring the map collection:

    • Find a location of interest.
    • View the maps.
    • Compare the maps.
    • Download and share the maps or open them in ArcGIS Desktop (ArcGIS Pro or ArcMap) where places will appear in their correct geographic location.
    • Save the maps in an ArcGIS Online web map.

    Finding the maps of interest is simple. Users can see a footprint of the map in the map view before they decide to add it to the display, and thumbnails of the maps are shown in pop-ups on the timeline. The timeline also helps users find maps because they can zoom and pan, and maps at select scales can be turned on or off by using the legend boxes to the left of the timeline. Once maps have been added to the display, users can reorder them by dragging them. Users can also download maps as zipped GeoTIFF images. Users can also share the current state of the app through a hyperlink or social media. This ArcWatch article guides you through each of these steps: https://www.esri.com/esri-news/arcwatch/1014/envisioning-the-past.


    Once signed in, users can create a web map with the current map view and any maps they have selected. The web map will open in ArcGIS Online. The title of the web map will be the same as the top map on the side panel of the app. All historical maps that were selected in the app will appear in the Contents section of the web map with the earliest at the top and the latest at the bottom. Turning the historical maps on and off or setting the transparency on the layers allows users to compare the historical maps over time. Also, the web map can be opened in ArcGIS Desktop (ArcGIS Pro or ArcMap) and used for exploration or data capture.

    Users can find out more about the USGS topograhic map collection and the app by clicking on the information button at the upper right. This opens a pop-up with information about the maps and app. The pop-up includes a useful link to a USGS web page that provides access to documents with keys explaining the symbols on historic and current USGS topographic maps. The pop-up also has a link to send Esri questions or comments about the map collection or the app.

    We have shared the updated app on GitHub, so users can download it and configure it to work with their own map collections.

  10. NZ Bathymetry 250m Imagery/Raster layer

    • pacificgeoportal.com
    • sdgs.amerigeoss.org
    • +4more
    Updated Nov 7, 2017
    + more versions
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    National Institute of Water and Atmospheric Research (2017). NZ Bathymetry 250m Imagery/Raster layer [Dataset]. https://www.pacificgeoportal.com/datasets/NIWA::nz-bathymetry-250m-imagery-raster-layer/about
    Explore at:
    Dataset updated
    Nov 7, 2017
    Dataset authored and provided by
    National Institute of Water and Atmospheric Research
    License

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

    Area covered
    Description

    NIWA's bathymetry model of New Zealand at a 250m resolution. The 2016 model is a compilation of data digitised from published coastal charts, digital soundings archive, navy collector sheets and digital multibeam data sourced from surveys by NIWA, LINZ, as well as international surveys by vessels from United States of America, France, Germany, Australia, and Japan. All data used is held at NIWA.Image service can be used for analysis in ArcGIS Desktop or ArcGIS Online - no need to download the data, just stream using this service and classify, symbolise, mask, extract or apply map algebra - just like you would with local raster files. https://enterprise.arcgis.com/en/server/latest/publish-services/windows/key-concepts-for-image-services.htmMap information and metadata Offshore representation was generated from digital bathymetry at a grid resolution of 250m. Sun illumination is from an azimuth of 315° and 45° above the horizon.Projection Mercator 41 (WGS84 datum). EPSG: 3994Scale 1:5,000,000 at 41°S. Not to be used for navigational purposes Bibliographic reference Mitchell, J.S., Mackay, K.A., Neil, H.L., Mackay, E.J., Pallentin, A., Notman P., 2012. Undersea New Zealand, 1:5,000,000. NIWA Chart, Miscellaneous Series No. 92Further Information: https://www.niwa.co.nz/our-science/oceans/bathymetry/further-informationLicence: https://www.niwa.co.nz/environmental-information/licences/niwa-open-data-licence-by-nn-nc-sa-version-1_Item Page Created: 2017-11-01 00:55 Item Page Last Modified: 2025-04-05 18:48Owner: NIWA_OpenData

  11. World Surface Water

    • agriculture.africageoportal.com
    • iwmi.africageoportal.com
    • +4more
    Updated Dec 3, 2014
    + more versions
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    Esri (2014). World Surface Water [Dataset]. https://agriculture.africageoportal.com/datasets/ddfce15a8ccd4c8c88fb125cb4f23cc9
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    Dataset updated
    Dec 3, 2014
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    Water bodies are a key element in the landscape. This layer provides a global map of large water bodies for use inlandscape-scale analysis. Dataset Summary This layer provides access to a 250m cell-sized raster of surface water created by extracting pixels coded as water in theGlobal Lithological Mapand theGlobal Landcover Map. The layer was created by Esri in 2014.What can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop. This layer hasquery,identify, andexportimage services available. This layer is restricted to a maximum area of 16,000 x 16,000 pixels - an area 4,000 kilometerson a side or an area approximately the size of Europe. This layer is part of a larger collection oflandscape layersthat you can use to perform a wide variety of mapping and analysis tasks. TheLiving Atlas of the Worldprovides an easy way to explore the landscape layers and many otherbeautiful and authoritative maps on hundreds of topics. Geonetis a good resource for learning more aboutlandscape layers and the Living Atlas of the World. To get started see theLiving Atlas Discussion Group. TheEsri Insider Blogprovides an introduction to the Ecophysiographic Mapping project.

  12. c

    United States Wind Turbine Database - Legacy Versions (ver. 1.0 - ver. 7.2)

    • s.cnmilf.com
    • data.usgs.gov
    • +2more
    Updated Mar 11, 2025
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    U.S. Geological Survey (2025). United States Wind Turbine Database - Legacy Versions (ver. 1.0 - ver. 7.2) [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/united-states-wind-turbine-database-previous-versions
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    Dataset updated
    Mar 11, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    United States
    Description

    This data provides locations and technical specifications of legacy versions (ver. 1.0 - ver. X.X) of the United States Wind Turbines database. Each release, typically done quarterly, updates the database with newly installed wind turbines, removes wind turbines that have been identified as dismantled, and applies other verifications based on updated imagery and ongoing quality-control. Turbine data were gathered from the Federal Aviation Administration's (FAA) Digital Obstacle File (DOF) and Obstruction Evaluation Airport Airspace Analysis (OE-AAA), the American Wind Energy Association (AWEA), Lawrence Berkeley National Laboratory (LBNL), and the United States Geological Survey (USGS), and were merged and collapsed into a single data set. Verification of the turbine positions was done by visual interpretation using high-resolution aerial imagery in ESRI ArcGIS Desktop. A locational error of plus or minus 10 meters for turbine locations was tolerated. Technical specifications for turbines were assigned based on the wind turbine make and models as provided by manufacturers and project developers directly, and via FAA datasets, information on the wind project developer or turbine manufacturer websites, or other online sources. Some facility and turbine information on make and model did not exist or was difficult to obtain. Thus, uncertainty may exist for certain turbine specifications. Similarly, some turbines were not yet built, not built at all, or for other reasons cannot be verified visually. Location and turbine specifications data quality are rated and a confidence is recorded for both. None of the data are field verified. The current version is available for download at https://doi.org/10.5066/F7TX3DN0. The USWTDB Viewer, created by the USGS Energy Resources Program, lets you visualize, inspect, interact, and download the most current USWTDB version only, through a dynamic web application. https://eerscmap.usgs.gov/uswtdb/viewer/

  13. a

    GIS – Great Lakes Sediment Budget – Technical Methodology – Buffline...

    • glri-usace.hub.arcgis.com
    Updated Sep 28, 2021
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    usace_sam_rd3 (2021). GIS – Great Lakes Sediment Budget – Technical Methodology – Buffline Digitization [Dataset]. https://glri-usace.hub.arcgis.com/documents/e16113ca62f244559475bacbf4bef03c
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    Dataset updated
    Sep 28, 2021
    Dataset authored and provided by
    usace_sam_rd3
    Area covered
    The Great Lakes
    Description

    GIS – Great Lakes Sediment Budget – Technical Methodology – Buffline Digitization Madeleine Dewey EIT1 , Cedric Wrobel EIT1 1United States Army Corps of Engineers Great Lakes and Ohio River Division, Buffalo District Department of Coastal and Geotechnical Design Editor and Senior Reviewer: Weston Cross PG1 Published: September 2021 Abstract: This document is intended for use as a reference guide to complete bluffline digitization work for the Great Lakes Sediment Budget, a project of the Great Lakes Restoration Initiative. Digitization work consists of manually drawing polylines along the lakeshore to delineate where the bluffline, or more broadly, the line of significance, exists. This reference can be used for both historic, and contemporary blufflines. In addition, this guide outlines what datasets, ESRI ArcGIS tools, and strategies should be employed. The manual for ESRI ArcMap 10.7, the version of ArcGIS used to create this guide, can be found at: https://support.esri.com/en/products/desktop/arcgis‐desktop/arcmap/10‐7‐1

  14. Sentinel-2 Imagery: NDVI Colormap

    • hub.arcgis.com
    • sdgs.amerigeoss.org
    • +3more
    Updated May 2, 2018
    + more versions
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    Esri (2018). Sentinel-2 Imagery: NDVI Colormap [Dataset]. https://hub.arcgis.com/datasets/dccafe125bbe4e2bb3315393acbd4701
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    Dataset updated
    May 2, 2018
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    Sentinel-2, 10m Multispectral 13-band imagery, rendered on-the-fly. Available for visualization and analytics, this Imagery Layer pulls directly from the Sentinel-2 on AWS collection and is updated daily with new imagery.This imagery layer can be used for multiple purposes including but not limited to vegetation, land cover, plant health, deforestation and environmental monitoring.Geographic CoverageGlobalContinental land masses from 65.4° South to 72.1° North, with these special guidelines:All coastal waters up to 20 km from the shoreAll islands greater than 100 km2All EU islandsAll closed seas (e.g. Caspian Sea)The Mediterranean SeaNote: Areas of interest going beyond the Mission baseline (as laid out in the Mission Requirements Document) will be assessed, and may be added to the baseline if sufficient resources are identified.Temporal CoverageThe revisit time for each point on Earth is every 5 days.This layer is updated daily with new imagery.This imagery layer is designed to include imagery collected within the past 14 months. Custom Image Services can be created for access to images older than 14 months.The number of images available will vary depending on location.Image Selection/FilteringThe most recent and cloud free image, for any location, is displayed by default.Any image available, within the past 14 months, can be displayed via custom filtering.Filtering can be done based on Acquisition Date, Estimated Cloud Cover, and Tile ID.Tile_ID is computed as [year][month][day]T[hours][minutes][seconds]_[UTMcode][latitudeband][square]_[sequence]. More…NOTE: Not using filters, and loading the entire archive, may affect performance.Analysis ReadyThis imagery layer is analysis ready with TOA correction applied.Visual RenderingDefault rendering is NDVI Colormap (Normalized Difference vegetation index with colormap) computed as NIR(Band8)-Red(Band4)/NIR(Band8)+Red(Band4) . The raw version of this layer is NDVI-Raw.Green represents vigorous vegetation and brown represents sparse vegetation.Rendering (or display) of band combinations and calculated indices is done on-the-fly from the source images via Raster Functions.Various pre-defined Raster Functions can be selected or custom functions created.Available renderings include: Agriculture with DRA, Bathymetric with DRA, Color-Infrared with DRA, Natural Color with DRA, Short-wave Infrared with DRA, Geology with DRA, NDMI Colorized, Normalized Difference Built-Up Index (NDBI), NDWI Raw, NDWI - with VRE Raw, NDVI – with VRE Raw (NDRE), NDVI - VRE only Raw, NDVI Raw, Normalized Burn RatioMultispectral BandsBandDescriptionWavelength (µm)Resolution (m)1Coastal aerosol0.433 - 0.453602Blue0.458 - 0.523103Green0.543 - 0.578104Red0.650 - 0.680105Vegetation Red Edge0.698 - 0.713206Vegetation Red Edge0.733 - 0.748207Vegetation Red Edge0.773 - 0.793208NIR0.785 - 0.900108ANarrow NIR0.855 - 0.875209Water vapour0.935 - 0.9556010SWIR – Cirrus1.365 - 1.3856011SWIR-11.565 - 1.6552012SWIR-22.100 - 2.28020Additional NotesOverviews exist with a spatial resolution of 150m and are updated every quarter based on the best and latest imagery available at that time.To work with source images at all scales, the ‘Lock Raster’ functionality is available.NOTE: ‘Lock Raster’ should only be used on the layer for short periods of time, as the imagery and associated record Object IDs may change daily.This ArcGIS Server dynamic imagery layer can be used in Web Maps and ArcGIS Desktop as well as Web and Mobile applications using the REST based Image services API.Images can be exported up to a maximum of 4,000 columns x 4,000 rows per request.Data SourceSentinel-2 imagery is the result of close collaboration between the (European Space Agency) ESA, the European Commission and USGS. Data is hosted by the Amazon Web Services as part of their Registry of Open Data. Users can access the imagery from Sentinel-2 on AWS , or alternatively access Sentinel2Look Viewer, EarthExplorer or the Copernicus Open Access Hub to download the scenes.For information on Sentinel-2 imagery, see Sentinel-2.

  15. USA Detailed Streams

    • prep-response-portal-napsg.hub.arcgis.com
    • prep-response-portal.napsgfoundation.org
    • +4more
    Updated Apr 21, 2014
    + more versions
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    Esri (2014). USA Detailed Streams [Dataset]. https://prep-response-portal-napsg.hub.arcgis.com/datasets/esri::usa-detailed-streams
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    Dataset updated
    Apr 21, 2014
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    U.S. Rivers and Streams represents detailed rivers and streams in the United States. Due to the very large number of features in this dataset, it has a minimum draw scale of 1:400,000.To download the data for this layer as a layer package for use in ArcGIS desktop applications, refer to USA Detailed Rivers and Streams.

  16. USA Water Bodies

    • data.lojic.org
    • anrgeodata.vermont.gov
    • +1more
    Updated Apr 22, 2014
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    Esri (2014). USA Water Bodies [Dataset]. https://data.lojic.org/datasets/esri::usa-water-bodies/api
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    Dataset updated
    Apr 22, 2014
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer presents the water feature areas of the United States. It provides the water bodies for geographic display and analysis at regional levels.To download the data for this layer as a layer package for use in ArcGIS desktop applications, refer to USA National Atlas Water Feature Areas - Water Bodies.

  17. h

    Heat Severity - USA 2021

    • heat.gov
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Jan 6, 2022
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    The Trust for Public Land (2022). Heat Severity - USA 2021 [Dataset]. https://www.heat.gov/datasets/cdd2ffd5a2fc414ca1a5e676f5fce3e3
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    Dataset updated
    Jan 6, 2022
    Dataset authored and provided by
    The Trust for Public Land
    Area covered
    United States,
    Description

    Notice: this is not the latest Heat Island Severity image service. For 2023 data, visit https://tpl.maps.arcgis.com/home/item.html?id=db5bdb0f0c8c4b85b8270ec67448a0b6. This layer contains the relative heat severity for every pixel for every city in the contiguous United States. This 30-meter raster was derived from Landsat 8 imagery band 10 (ground-level thermal sensor) from the summer of 2021, patched with data from 2020 where necessary.Federal statistics over a 30-year period show extreme heat is the leading cause of weather-related deaths in the United States. Extreme heat exacerbated by urban heat islands can lead to increased respiratory difficulties, heat exhaustion, and heat stroke. These heat impacts significantly affect the most vulnerable—children, the elderly, and those with preexisting conditions.The purpose of this layer is to show where certain areas of cities are hotter than the average temperature for that same city as a whole. Severity is measured on a scale of 1 to 5, with 1 being a relatively mild heat area (slightly above the mean for the city), and 5 being a severe heat area (significantly above the mean for the city). The absolute heat above mean values are classified into these 5 classes using the Jenks Natural Breaks classification method, which seeks to reduce the variance within classes and maximize the variance between classes. Knowing where areas of high heat are located can help a city government plan for mitigation strategies.This dataset represents a snapshot in time. It will be updated yearly, but is static between updates. It does not take into account changes in heat during a single day, for example, from building shadows moving. The thermal readings detected by the Landsat 8 sensor are surface-level, whether that surface is the ground or the top of a building. Although there is strong correlation between surface temperature and air temperature, they are not the same. We believe that this is useful at the national level, and for cities that don’t have the ability to conduct their own hyper local temperature survey. Where local data is available, it may be more accurate than this dataset. Dataset SummaryThis dataset was developed using proprietary Python code developed at The Trust for Public Land, running on the Descartes Labs platform through the Descartes Labs API for Python. The Descartes Labs platform allows for extremely fast retrieval and processing of imagery, which makes it possible to produce heat island data for all cities in the United States in a relatively short amount of time.What can you do with this layer?This layer has query, identify, and export image services available. Since it is served as an image service, it is not necessary to download the data; the service itself is data that can be used directly in any Esri geoprocessing tool that accepts raster data as input.In order to click on the image service and see the raw pixel values in a map viewer, you must be signed in to ArcGIS Online, then Enable Pop-Ups and Configure Pop-Ups.Using the Urban Heat Island (UHI) Image ServicesThe data is made available as an image service. There is a processing template applied that supplies the yellow-to-red or blue-to-red color ramp, but once this processing template is removed (you can do this in ArcGIS Pro or ArcGIS Desktop, or in QGIS), the actual data values come through the service and can be used directly in a geoprocessing tool (for example, to extract an area of interest). Following are instructions for doing this in Pro.In ArcGIS Pro, in a Map view, in the Catalog window, click on Portal. In the Portal window, click on the far-right icon representing Living Atlas. Search on the acronyms “tpl” and “uhi”. The results returned will be the UHI image services. Right click on a result and select “Add to current map” from the context menu. When the image service is added to the map, right-click on it in the map view, and select Properties. In the Properties window, select Processing Templates. On the drop-down menu at the top of the window, the default Processing Template is either a yellow-to-red ramp or a blue-to-red ramp. Click the drop-down, and select “None”, then “OK”. Now you will have the actual pixel values displayed in the map, and available to any geoprocessing tool that takes a raster as input. Below is a screenshot of ArcGIS Pro with a UHI image service loaded, color ramp removed, and symbology changed back to a yellow-to-red ramp (a classified renderer can also be used): Other Sources of Heat Island InformationPlease see these websites for valuable information on heat islands and to learn about exciting new heat island research being led by scientists across the country:EPA’s Heat Island Resource CenterDr. Ladd Keith, University of ArizonaDr. Ben McMahan, University of Arizona Dr. Jeremy Hoffman, Science Museum of Virginia Dr. Hunter Jones, NOAA Daphne Lundi, Senior Policy Advisor, NYC Mayor's Office of Recovery and ResiliencyDisclaimer/FeedbackWith nearly 14,000 cities represented, checking each city's heat island raster for quality assurance would be prohibitively time-consuming, so The Trust for Public Land checked a statistically significant sample size for data quality. The sample passed all quality checks, with about 98.5% of the output cities error-free, but there could be instances where the user finds errors in the data. These errors will most likely take the form of a line of discontinuity where there is no city boundary; this type of error is caused by large temperature differences in two adjacent Landsat scenes, so the discontinuity occurs along scene boundaries (see figure below). The Trust for Public Land would appreciate feedback on these errors so that version 2 of the national UHI dataset can be improved. Contact Dale.Watt@tpl.org with feedback.

  18. c

    Caribbean Landsat Imagery

    • caribbeangeoportal.com
    Updated Mar 20, 2020
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    Caribbean GeoPortal (2020). Caribbean Landsat Imagery [Dataset]. https://www.caribbeangeoportal.com/maps/0ee1dca67c9744169f8f1c0607923454
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    Dataset updated
    Mar 20, 2020
    Dataset authored and provided by
    Caribbean GeoPortal
    Area covered
    Description

    This map contains a number of world-wide dynamic image services providing access to various Landsat scenes covering the landmass of the World for visual interpretation. Landsat 8 collects new scenes for each location on Earth every 16 days, assuming limited cloud coverage. Newest and near cloud-free scenes are displayed by default on top. Most scenes collected since 1st January 2015 are included. The service also includes scenes from the Global Land Survey* (circa 2010, 2005, 2000, 1990, 1975).The service contains a range of different predefined renderers for Multispectral, Panchromatic as well as Pansharpened scenes. The layers in the service can be time-enabled so that the applications can restrict the displayed scenes to a specific date range. This ArcGIS Server dynamic service can be used in Web Maps and ArcGIS Desktop, Web and Mobile applications using the REST based image services API. Users can also export images, but the exported area is limited to maximum of 2,000 columns x 2,000 rows per request.Data Source: The imagery in these services is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). The data for these services reside on the Landsat Public Datasets hosted on the Amazon Web Service cloud. Users can access full scenes from https://github.com/landsat-pds/landsat_ingestor/wiki/Accessing-Landsat-on-AWS, or alternatively access http://landsatlook.usgs.gov to review and download full scenes from the complete USGS archive.For more information on Landsat 8 images, see http://landsat.usgs.gov/landsat8.php.*The Global Land Survey includes images from Landsat 1 through Landsat 7. Band numbers and band combinations differ from those of Landsat 8, but have been mapped to the most appropriate band as in the above table. For more information about the Global Land Survey, visit http://landsat.usgs.gov/science_GLS.php.For more information on each of the individual layers, see http://www.arcgis.com/home/item.html?id=d9b466d6a9e647ce8d1dd5fe12eb434b ; http://www.arcgis.com/home/item.html?id=6b003010cbe64d5d8fd3ce00332593bf ; http://www.arcgis.com/home/item.html?id=a7412d0c33be4de698ad981c8ba471e6

  19. Data from: Chlorophyll-a

    • catalog.data.gov
    • fisheries.noaa.gov
    Updated Oct 31, 2024
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    NOAA Office for Coastal Management (Point of Contact) (2024). Chlorophyll-a [Dataset]. https://catalog.data.gov/dataset/chlorophyll-a1
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    Dataset updated
    Oct 31, 2024
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Description

    This algorithm returns the near-surface concentration of chlorophyll-a (chlor_a) in mg m-3, calculated using an empirical relationship derived from in situ measurements of chlor_a and remote sensing reflectances (Rrs) in the blue-to-green region of the visible spectrum. The implementation is contingent on the availability three or more sensor bands spanning the 440 - 670 nm spectral regime. The algorithm is applicable to all current ocean color sensors. The chlor_a product is included as part of the standard Level-2 OC product suite and the Level-3 CHL product suite. The data represents monthly mean climatologies on a monthly data time scale for a ten-year period between 2007 and 2016. These climatologies were created using the 'Create Climatological Rasters for NASA OceanColor L3 SMI Product' in the Marine Geospatial Ecology Toolbox for ArcGIS Desktop 10.1-10.6. Available for download here: http://mgel2011-kvm.env.duke.edu/mget/download/.

  20. USA NLCD Impervious Surface Time Series

    • colorado-river-portal.usgs.gov
    • community-climatesolutions.hub.arcgis.com
    Updated Sep 26, 2019
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    Esri (2019). USA NLCD Impervious Surface Time Series [Dataset]. https://colorado-river-portal.usgs.gov/datasets/1fdbb561c58b45c58f8f966c00c78ae6
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    Dataset updated
    Sep 26, 2019
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    Impervious surfaces are surfaces that do not allow water to pass through. Examples of these surfaces include highways, parking lots, rooftops, and airport runways. Instead of allowing rain to pass into the soil, impervious surfaces cause water to collect at the surface, then run off. An increase in impervious surface area causes an increase of water volume which needs to be managed by stormwater systems. With the flow come pollutants, which collect on impervious surfaces then discharge with the runoff into streams and the ocean. Runoff water does not enter the water table, and that can cause other management issues, such as interruptions in baseline stream flow.The NLCD imperviousness layer represents urban impervious surfaces as a percentage of developed surface over every 30-meter pixel in the United States. Phenomenon Mapped: The proportion of the landscape that is impervious to water.Time Extent: 2001, 2004, 2006, 2008, 2011, 2013, 2016, 2019, and 2021 for the lower 48 conterminous US states. A small portion of Alaska around Anchorage displays a time series of 2001, 2011, and 2016. Hawaii, Puerto Rico, and the US Virgin Islands unfortunately only have data for 2001 so there is only one image in the series. This information may be used in conjunction with the USA NLCD Land Cover layer.Units: PercentCell Size: 30 metersSource Type: DiscretePixel Type: Unsigned integerData Coordinate System: North America Albers Equal Area Conic (102008)Mosaic Projection: North America Albers Equal Area Conic (102008)Extent: CONUS, Hawaii, A portion of Alaska around Anchorage, District of Columbia, Puerto RicoNoData Value: 127Source: Multi-Resolution Land Characteristics ConsortiumPublication Date: June 30, 2023ArcGIS Server URL: https://landscape10.arcgis.com/arcgis/Time SeriesBy default, this layer will appear in your client with a time slider which allows you to play the series as an animation. The animation will advance year by year, but the layer only changes appearance every few years in the lower 48 states, in 2001, 2004, 2006, 2008, 2011, 2013, 2016, 2019, and 2021. To select just one year in the series, first turn the time series off on the time slider, then create a definition query on the layer which selects only the desired year.Time Series DescriptorMRLC issued a set of companion rasters with this impervious surface layer showing the reason why each pixel is impervious. This companion layer, called the Developed Imperviousness Descriptor, is not currently available in this map service. The descriptor layer identifies types of roads, core urban areas, and energy production sites for each impervious pixel to allow deeper analysis of developed features. The descriptor layer may be downloaded directly from MRLC and added to ArcGIS Pro.Alaska, Hawaii, and Puerto RicoAt this time Alaska, Hawaii, and Puerto Rico are produced with a different methodology, and are not set up to be directly compared the way the CONUS time series is. To analyze change between the latest two data years for this portion of Alaska, be sure to use the NLCD 2011 to 2016 Developed Impervious Change raster. For Hawaii and Puerto Rico, only the year 2001 is available for download at the MRLC.North America Albers ProjectionAll NLCD layers in the Living Atlas are projected into the North America Albers Projection before serving in the Living Atlas. This allows the coterminous USA, Puerto Rico, Hawaii, and Alaska to be served from a common projection and analyzed together. In tests performed by esri, the NLCD land cover classes after projection to North America Albers had the exact same number of pixels in input as output, but pixels had been slightly rearranged after projection. Processing TemplatesThis layer comes with two color schemes, cool and warm. The default is a cool gray color scheme, designed to look good on light and dark gray web maps. To choose a warm color scheme which was the default until 2021, change the processing template to the Impervious Surface Warm Renderer in your map client.Dataset SummaryThe National Land Cover Database products are created through a cooperative project conducted by the Multi-Resolution Land Characteristics Consortium (MRLC). The MRLC Consortium is a partnership of federal agencies, consisting of the U.S. Geological Survey, the National Oceanic and Atmospheric Administration, the U.S. Environmental Protection Agency, the U.S. Department of Agriculture, the U.S. Forest Service, the National Park Service, the U.S. Fish and Wildlife Service, the Bureau of Land Management and the USDA Natural Resources Conservation Service.What can you do with this layer?This layer can be used to create maps and to visualize the underlying data. This layer can be used as an analytic input in ArcGIS Desktop.This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

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ZHIYUAN YAO; ZHIYUAN YAO (2022). ArcGIS Desktop 10.8.2 [Dataset]. http://doi.org/10.25346/S6/UMGDRS

ArcGIS Desktop 10.8.2

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exe(1111667672)Available download formats
Dataset updated
Oct 24, 2022
Dataset provided by
UCLA Dataverse
Authors
ZHIYUAN YAO; ZHIYUAN YAO
License

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

Description

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

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