100+ datasets found
  1. BOGS Training Metrics

    • catalog.data.gov
    • s.cnmilf.com
    • +1more
    Updated May 9, 2025
    + more versions
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    Bureau of Indian Affairs (BIA) (2025). BOGS Training Metrics [Dataset]. https://catalog.data.gov/dataset/bogs-training-metrics
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    Dataset updated
    May 9, 2025
    Dataset provided by
    Bureau of Indian Affairshttp://www.bia.gov/
    Description

    Through the Department of the Interior-Bureau of Indian Affairs Enterprise License Agreement (DOI-BIA ELA) program, BIA employees and employees of federally-recognized Tribes may access a variety of geographic information systems (GIS) online courses and instructor-led training events throughout the year at no cost to them. These online GIS courses and instructor-led training events are hosted by the Branch of Geospatial Support (BOGS) or offered by BOGS in partnership with other organizations and federal agencies. Online courses are self-paced and available year-round, while instructor-led training events have limited capacity and require registration and attendance on specific dates. This dataset does not any training where the course was not completed by the participant or where training was cancelled or otherwise not able to be completed. Point locations depict BIA Office locations or Tribal Office Headquarters. For completed trainings where a participant location was not provided a point locations may not be available. For more information on the Branch of Geospatial Support Geospatial training program, please visit:https://www.bia.gov/service/geospatial-training.

  2. Open-Source GIScience Online Course

    • ckan.americaview.org
    Updated Nov 2, 2021
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    ckan.americaview.org (2021). Open-Source GIScience Online Course [Dataset]. https://ckan.americaview.org/dataset/open-source-giscience-online-course
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    Dataset updated
    Nov 2, 2021
    Dataset provided by
    CKANhttps://ckan.org/
    License

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

    Description

    In this course, you will explore a variety of open-source technologies for working with geosptial data, performing spatial analysis, and undertaking general data science. The first component of the class focuses on the use of QGIS and associated technologies (GDAL, PROJ, GRASS, SAGA, and Orfeo Toolbox). The second component of the class introduces Python and associated open-source libraries and modules (NumPy, Pandas, Matplotlib, Seaborn, GeoPandas, Rasterio, WhiteboxTools, and Scikit-Learn) used by geospatial scientists and data scientists. We also provide an introduction to Structured Query Language (SQL) for performing table and spatial queries. This course is designed for individuals that have a background in GIS, such as working in the ArcGIS environment, but no prior experience using open-source software and/or coding. You will be asked to work through a series of lecture modules and videos broken into several topic areas, as outlined below. Fourteen assignments and the required data have been provided as hands-on opportunites to work with data and the discussed technologies and methods. If you have any questions or suggestions, feel free to contact us. We hope to continue to update and improve this course. This course was produced by West Virginia View (http://www.wvview.org/) with support from AmericaView (https://americaview.org/). This material is based upon work supported by the U.S. Geological Survey under Grant/Cooperative Agreement No. G18AP00077. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the U.S. Geological Survey. Mention of trade names or commercial products does not constitute their endorsement by the U.S. Geological Survey. After completing this course you will be able to: apply QGIS to visualize, query, and analyze vector and raster spatial data. use available resources to further expand your knowledge of open-source technologies. describe and use a variety of open data formats. code in Python at an intermediate-level. read, summarize, visualize, and analyze data using open Python libraries. create spatial predictive models using Python and associated libraries. use SQL to perform table and spatial queries at an intermediate-level.

  3. Open Source GIS Training for Improved Protected Area Planning and Management...

    • rmi-data.sprep.org
    • pacific-data.sprep.org
    pdf, zip
    Updated Nov 2, 2022
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    Bradley Eichelberger, SPREP PIPAP GIS Consultant (2022). Open Source GIS Training for Improved Protected Area Planning and Management in the Republic of the Marshall Islands [Dataset]. https://rmi-data.sprep.org/dataset/open-source-gis-training-improved-protected-area-planning-and-management-republic-marshall
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    pdf(5213196), pdf(1167275), zip(151511128), pdf(3658659)Available download formats
    Dataset updated
    Nov 2, 2022
    Dataset provided by
    Pacific Regional Environment Programmehttps://www.sprep.org/
    Authors
    Bradley Eichelberger, SPREP PIPAP GIS Consultant
    License

    Public Domain Mark 1.0https://creativecommons.org/publicdomain/mark/1.0/
    License information was derived automatically

    Area covered
    Marshall Islands, 176.18637084961 3.4531078732957)), 159.92660522461 16.662506225635, 176.18637084961 16.662506225635, POLYGON ((159.92660522461 3.4531078732957
    Description

    Dataset contains training material on using open source Geographic Information Systems (GIS) to improve protected area planning and management from a workshop that was conducted on August 17-21, 2020. Specifically, the dataset contains lectures on GIS fundamentals, QGIS 3.x, and global positioning system (GPS), as well as country-specific datasets and a workbook containing exercises for viewing data, editing/creating datasets, and creating map products in QGIS. Supplemental videos that narrate a step-by-step recap and overview of these processes are found in the Related Content section of this dataset.

    Funding for this workshop and material was funded by the Biodiversity and Protected Areas Management (BIOPAMA) programme. The BIOPAMA programme is an initiative of the Organisation of African, Caribbean and Pacific (ACP) Group of States financed by the European Union's 11th European Development Fund. BIOPAMA is jointly implemented by the International Union for Conservation of Nature {IUCN) and the Joint Research Centre of the European Commission (EC-JRC). In the Pacific region, BIOPAMA is implemented by IUCN's Oceania Regional Office (IUCN ORO) in partnership with the Secretariat of the Pacific Regional Environment Programme (SPREP). The overall objective of the BIOPAMA programme is to contribute to improving the long-term conservation and sustainable use of biodiversity and natural resources in the Pacific ACP region in protected areas and surrounding communities through better use and monitoring of information and capacity development on management and governance.

  4. a

    QGIS Training Tutorials: Using Spatial Data in Geographic Information...

    • catalogue.arctic-sdi.org
    • datasets.ai
    • +2more
    Updated Oct 28, 2019
    + more versions
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    (2019). QGIS Training Tutorials: Using Spatial Data in Geographic Information Systems [Dataset]. https://catalogue.arctic-sdi.org/geonetwork/srv/search?format=MOV
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    Dataset updated
    Oct 28, 2019
    Description

    Have you ever wanted to create your own maps, or integrate and visualize spatial datasets to examine changes in trends between locations and over time? Follow along with these training tutorials on QGIS, an open source geographic information system (GIS) and learn key concepts, procedures and skills for performing common GIS tasks – such as creating maps, as well as joining, overlaying and visualizing spatial datasets. These tutorials are geared towards new GIS users. We’ll start with foundational concepts, and build towards more advanced topics throughout – demonstrating how with a few relatively easy steps you can get quite a lot out of GIS. You can then extend these skills to datasets of thematic relevance to you in addressing tasks faced in your day-to-day work.

  5. Inform E-learning GIS Course

    • solomonislands-data.sprep.org
    • tonga-data.sprep.org
    • +13more
    pdf
    Updated Jul 16, 2025
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    SPREP (2025). Inform E-learning GIS Course [Dataset]. https://solomonislands-data.sprep.org/dataset/inform-e-learning-gis-course
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    pdf(587295), pdf(658923), pdf(501586), pdf(1335336)Available download formats
    Dataset updated
    Jul 16, 2025
    Dataset provided by
    Pacific Regional Environment Programmehttps://www.sprep.org/
    License

    Public Domain Mark 1.0https://creativecommons.org/publicdomain/mark/1.0/
    License information was derived automatically

    Area covered
    Pacific Region
    Description

    This dataset holds all materials for the Inform E-learning GIS course

  6. a

    ArcGIS Pro Fundamentals

    • hub.arcgis.com
    Updated May 3, 2019
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    State of Delaware (2019). ArcGIS Pro Fundamentals [Dataset]. https://hub.arcgis.com/documents/ccd396a41cc944258e0d3c0461c473ea
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    Dataset updated
    May 3, 2019
    Dataset authored and provided by
    State of Delaware
    Description

    Enroll in this plan to get familiar with the user interface, apply commonly used tools, and master the basics of mapping and analyzing data using ArcGIS Pro.Goals Install ArcGIS Pro and efficiently locate tools, options, and user interface elements. Add data to a map, symbolize map features to represent type, categories, or quantities; and optimize map display at various scales. Create a file geodatabase to organize and accurately maintain GIS data over time. Complete common mapping, editing, and analysis workflows.

  7. Open Source GIS Training for Improved Protected Area Planning and Management...

    • solomonislands-data.sprep.org
    • pacific-data.sprep.org
    pdf, zip
    Updated Feb 15, 2022
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    Bradley Eichelberger, SPREP PIPAP GIS Consultant (2022). Open Source GIS Training for Improved Protected Area Planning and Management in the Solomon Islands [Dataset]. https://solomonislands-data.sprep.org/dataset/open-source-gis-training-improved-protected-area-planning-and-management-solomon-islands
    Explore at:
    zip(702782472), pdf(3669473), pdf(969719), pdf(5434848)Available download formats
    Dataset updated
    Feb 15, 2022
    Dataset provided by
    Pacific Regional Environment Programmehttps://www.sprep.org/
    Authors
    Bradley Eichelberger, SPREP PIPAP GIS Consultant
    License

    Public Domain Mark 1.0https://creativecommons.org/publicdomain/mark/1.0/
    License information was derived automatically

    Area covered
    Solomon Islands, 168.10043334961 -4.0464671937446, POLYGON ((155.35629272461 -12.561265715616, 155.35629272461 -4.0464671937446, 168.10043334961 -12.561265715616))
    Description

    Dataset contains training material on using open source Geographic Information Systems (GIS) to improve protected area planning and management from a workshop that was conducted on October 19-23, 2020. Specifically, the dataset contains lectures on GIS fundamentals, QGIS 3.x, and global positioning system (GPS), as well as country-specific datasets and a workbook containing exercises for viewing data, editing/creating datasets, and creating map products in QGIS. Supplemental videos that narrate a step-by-step recap and overview of these processes are found in the Related Content section of this dataset.

    Funding for this workshop and material was funded by the Biodiversity and Protected Areas Management (BIOPAMA) programme. The BIOPAMA programme is an initiative of the Organisation of African, Caribbean and Pacific (ACP) Group of States financed by the European Union's 11th European Development Fund. BIOPAMA is jointly implemented by the International Union for Conservation of Nature {IUCN) and the Joint Research Centre of the European Commission (EC-JRC). In the Pacific region, BIOPAMA is implemented by IUCN's Oceania Regional Office (IUCN ORO) in partnership with the Secretariat of the Pacific Regional Environment Programme (SPREP). The overall objective of the BIOPAMA programme is to contribute to improving the long-term conservation and sustainable use of biodiversity and natural resources in the Pacific ACP region in protected areas and surrounding communities through better use and monitoring of information and capacity development on management and governance.

  8. Z

    Survey data for "Remote Sensing & GIS Training in Ecology and Conservation"

    • data.niaid.nih.gov
    • zenodo.org
    Updated Jan 24, 2020
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    Ulloa-Torrealba, Yrneh Z. (2020). Survey data for "Remote Sensing & GIS Training in Ecology and Conservation" [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_49870
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    Dataset updated
    Jan 24, 2020
    Dataset provided by
    Wohlfahrt, Christian
    Ortmann, Antonia
    Bell, Alexandra
    Ulloa-Torrealba, Yrneh Z.
    Braun, Daniela
    Bernd, Asja
    License

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

    Description

    This file provides the raw data of an online survey intended at gathering information regarding remote sensing (RS) and Geographical Information Systems (GIS) for conservation in academic education. The aim was to unfold best practices as well as gaps in teaching methods of remote sensing/GIS, and to help inform how these may be adapted and improved. A total of 73 people answered the survey, which was distributed through closed mailing lists of universities and conservation groups.

  9. Open Source GIS Training for Improved Protected Area Planning and Management...

    • samoa-data.sprep.org
    • pacific-data.sprep.org
    pdf, zip
    Updated Feb 15, 2022
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    Bradley Eichelberger, SPREP PIPAP GIS Consultant (2022). Open Source GIS Training for Improved Protected Area Planning and Management in Samoa [Dataset]. https://samoa-data.sprep.org/dataset/open-source-gis-training-improved-protected-area-planning-and-management-samoa
    Explore at:
    pdf(1016525), zip(791238585), pdf(4922394), pdf(3655929)Available download formats
    Dataset updated
    Feb 15, 2022
    Dataset provided by
    Pacific Regional Environment Programmehttps://www.sprep.org/
    Authors
    Bradley Eichelberger, SPREP PIPAP GIS Consultant
    License

    Public Domain Mark 1.0https://creativecommons.org/publicdomain/mark/1.0/
    License information was derived automatically

    Area covered
    Samoa, 188.90562057495 -14.517952072974)), POLYGON ((186.75230026245 -14.517952072974, 188.90562057495 -13.120440826626, 186.75230026245 -13.120440826626
    Description

    Dataset contains training material on using open source Geographic Information Systems (GIS) to improve protected area planning and management from workshops that were conducted on February 19-21 and October 6-7, 2020. Specifically, the dataset contains lectures on GIS fundamentals, QGIS 3.x, and global positioning system (GPS), as well as country-specific datasets and a workbook containing exercises for viewing data, editing/creating datasets, and creating map products in QGIS. Supplemental videos that narrate a step-by-step recap and overview of these processes are found in the Related Content section of this dataset.

    Funding for this workshop and material was funded by the Biodiversity and Protected Areas Management (BIOPAMA) programme. The BIOPAMA programme is an initiative of the Organisation of African, Caribbean and Pacific (ACP) Group of States financed by the European Union's 11th European Development Fund. BIOPAMA is jointly implemented by the International Union for Conservation of Nature {IUCN) and the Joint Research Centre of the European Commission (EC-JRC). In the Pacific region, BIOPAMA is implemented by IUCN's Oceania Regional Office (IUCN ORO) in partnership with the Secretariat of the Pacific Regional Environment Programme (SPREP). The overall objective of the BIOPAMA programme is to contribute to improving the long-term conservation and sustainable use of biodiversity and natural resources in the Pacific ACP region in protected areas and surrounding communities through better use and monitoring of information and capacity development on management and governance.

  10. g

    WWDC GIS Standards - Training Webinar

    • data.geospatialhub.org
    • hub.arcgis.com
    Updated Feb 1, 2018
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    wrds_wdo (2018). WWDC GIS Standards - Training Webinar [Dataset]. https://data.geospatialhub.org/documents/e98e6ddb9f074f9f94256b080a7ee509
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    Dataset updated
    Feb 1, 2018
    Dataset authored and provided by
    wrds_wdo
    Description

    Bear River Data Model GIS Standards Training Webinar (Nov. 15, 2017)

  11. a

    13.3 Distance Analysis Using ArcGIS

    • training-iowadot.opendata.arcgis.com
    • hub.arcgis.com
    Updated Mar 4, 2017
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    Iowa Department of Transportation (2017). 13.3 Distance Analysis Using ArcGIS [Dataset]. https://training-iowadot.opendata.arcgis.com/documents/f15a91d0e1d54ffbbf3761660755d391
    Explore at:
    Dataset updated
    Mar 4, 2017
    Dataset authored and provided by
    Iowa Department of Transportation
    License

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

    Description

    One important reason for performing GIS analysis is to determine proximity. Often, this type of analysis is done using vector data and possibly the Buffer or Near tools. In this course, you will learn how to calculate distance using raster datasets as inputs in order to assign cells a value based on distance to the nearest source (e.g., city, campground). You will also learn how to allocate cells to a particular source and to determine the compass direction from a cell in a raster to a source.What if you don't want to just measure the straight line from one place to another? What if you need to determine the best route to a destination, taking speed limits, slope, terrain, and road conditions into consideration? In cases like this, you could use the cost distance tools in order to assign a cost (such as time) to each raster cell based on factors like slope and speed limit. From these calculations, you could create a least-cost path from one place to another. Because these tools account for variables that could affect travel, they can help you determine that the shortest path may not always be the best path.After completing this course, you will be able to:Create straight-line distance, direction, and allocation surfaces.Determine when to use Euclidean and weighted distance tools.Perform a least-cost path analysis.

  12. w

    Dataset of books called Learning GIS using open source software : an applied...

    • workwithdata.com
    Updated Apr 17, 2025
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    Work With Data (2025). Dataset of books called Learning GIS using open source software : an applied guide for geo-spatial analysis [Dataset]. https://www.workwithdata.com/datasets/books?f=1&fcol0=book&fop0=%3D&fval0=Learning+GIS+using+open+source+software+%3A+an+applied+guide+for+geo-spatial+analysis
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    Dataset updated
    Apr 17, 2025
    Dataset authored and provided by
    Work With Data
    License

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

    Description

    This dataset is about books. It has 1 row and is filtered where the book is Learning GIS using open source software : an applied guide for geo-spatial analysis. It features 7 columns including author, publication date, language, and book publisher.

  13. Esri Maps for Public Policy

    • climate-center-lincolninstitute.hub.arcgis.com
    • babbitt-center-lincolninstitute.hub.arcgis.com
    • +3more
    Updated Oct 1, 2019
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    Esri (2019). Esri Maps for Public Policy [Dataset]. https://climate-center-lincolninstitute.hub.arcgis.com/datasets/esri::esri-maps-for-public-policy
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    Dataset updated
    Oct 1, 2019
    Dataset authored and provided by
    Esrihttp://esri.com/
    Description

    OVERVIEWThis site is dedicated to raising the level of spatial and data literacy used in public policy. We invite you to explore curated content, training, best practices, and datasets that can provide a baseline for your research, analysis, and policy recommendations. Learn about emerging policy questions and how GIS can be used to help come up with solutions to those questions.EXPLOREGo to your area of interest and explore hundreds of maps about various topics such as social equity, economic opportunity, public safety, and more. Browse and view the maps, or collect them and share via a simple URL. Sharing a collection of maps is an easy way to use maps as a tool for understanding. Help policymakers and stakeholders use data as a driving factor for policy decisions in your area.ISSUESBrowse different categories to find data layers, maps, and tools. Use this set of content as a driving force for your GIS workflows related to policy. RESOURCESTo maximize your experience with the Policy Maps, we’ve assembled education, training, best practices, and industry perspectives that help raise your data literacy, provide you with models, and connect you with the work of your peers.

  14. BOOK: Learning from COVID-19: GIS for Pandemics

    • coronavirus-resources.esri.com
    • arcgis.com
    • +1more
    Updated Oct 24, 2022
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    Esri’s Disaster Response Program (2022). BOOK: Learning from COVID-19: GIS for Pandemics [Dataset]. https://coronavirus-resources.esri.com/documents/78dcf5a3860a4cdea5482dac94f9c6b6
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    Dataset updated
    Oct 24, 2022
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri’s Disaster Response Program
    Description

    Needing to answer the question of “where” sat at the forefront of everyone’s mind, and using a geographic information system (GIS) for real-time surveillance transformed possibly overwhelming data into location intelligence that provided agencies and civic leaders with valuable insights.This book highlights best practices, key GIS capabilities, and lessons learned during the COVID-19 response that can help communities prepare for the next crisis.GIS has empowered:Organizations to use human mobility data to estimate the adherence to social distancing guidelinesCommunities to monitor their health care systems’ capacity through spatially enabled surge toolsGovernments to use location-allocation methods to site new resources (i.e., testing sites and augmented care sites) in ways that account for at-risk and vulnerable populationsCommunities to use maps and spatial analysis to review case trends at local levels to support reopening of economiesOrganizations to think spatially as they consider “back-to-the-workplace” plans that account for physical distancing and employee safety needsLearning from COVID-19 also includes a “next steps” section that provides ideas, strategies, tools, and actions to help jump-start your own use of GIS, either as a citizen scientist or a health professional. A collection of online resources, including additional stories, videos, new ideas and concepts, and downloadable tools and content, complements this book.Now is the time to use science and data to make informed decisions for our future, and this book shows us how we can do it.Dr. Este GeraghtyDr. Este Geraghty is the chief medical officer and health solutions director at Esri where she leads business development for the Health and Human Services sector.Matt ArtzMatt Artz is a content strategist for Esri Press. He brings a wide breadth of experience in environmental science, technology, and marketing.

  15. Z

    2021 UN Open GIS Challenge 1 - Training on Satellite Data Analysis and...

    • data.niaid.nih.gov
    Updated Sep 30, 2021
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    Patrick Happ (2021). 2021 UN Open GIS Challenge 1 - Training on Satellite Data Analysis and Machine Learning with QGIS (Satellite_QGIS) [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_5507080
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    Dataset updated
    Sep 30, 2021
    Dataset authored and provided by
    Patrick Happ
    License

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

    Area covered
    United Nations
    Description

    This dataset is part of the 2021 UN Open GIS Challenge 1 - Training on Satellite Data Analysis and Machine Learning with QGIS (Satellite_QGIS), Exercise 1: Supervised Change Detection: Monitoring deglaciation in Huascaran, Peru.

    The folder structure is the following:

    Clip: clipped images to the region of interest

    Images: original images from Landsat 8, Sentinel-1 and Sentinel-2 satellites.

    Preprocess: pre-processed images.

    Reports: classification reports of the generated masks.

    Results: classification maps.

    RGB_Compositions: true color RGB compositions.

    Stacks: multiband rasters with all bands stacked from Landsat 8 satellite.

  16. T

    GIS dataset

    • dataverse-training.tdl.org
    • dataverse-dev.tdl.org
    bin, tiff
    Updated Oct 18, 2016
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    Kristi Park; Kristi Park (2016). GIS dataset [Dataset]. https://dataverse-training.tdl.org/dataset.xhtml?persistentId=doi:10.5072/FK2/AZCLXJ
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    tiff(13275561), bin(216), bin(387)Available download formats
    Dataset updated
    Oct 18, 2016
    Dataset provided by
    Texas Data Repository ***TRAINING*** Dataverse
    Authors
    Kristi Park; Kristi Park
    License

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

    Description

    GIS dataset with TIFFs and tsw files

  17. U

    Introduction to Planetary Image Analysis and Geologic Mapping in ArcGIS Pro

    • data.usgs.gov
    • s.cnmilf.com
    • +1more
    Updated Mar 28, 2023
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    Sarah Black (2023). Introduction to Planetary Image Analysis and Geologic Mapping in ArcGIS Pro [Dataset]. http://doi.org/10.5066/P9RGW46K
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    Dataset updated
    Mar 28, 2023
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Sarah Black
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Time period covered
    Dec 2, 2020
    Description

    GIS project files and imagery data required to complete the Introduction to Planetary Image Analysis and Geologic Mapping in ArcGIS Pro tutorial. These data cover the area in and around Jezero crater, Mars.

  18. Military Training Routes

    • catalog.data.gov
    • gimi9.com
    • +2more
    Updated Oct 31, 2024
    + more versions
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    NOAA Office for Coastal Management (Point of Contact) (2024). Military Training Routes [Dataset]. https://catalog.data.gov/dataset/military-training-routes1
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    Dataset updated
    Oct 31, 2024
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Description

    Training Areas are geographic areas that provide a safe and realistic environment for training Sailors and testing systems. The MarineCadastre.gov team worked with the Navy to provide this data, which is a subset of the Navy's Common Operating Picture for ocean planning purposes.

  19. r

    GIS-material for the archaeological project: Kvarn military training area

    • researchdata.se
    Updated Jul 7, 2016
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    Swedish National Heritage Board, UV Öst (2016). GIS-material for the archaeological project: Kvarn military training area [Dataset]. http://doi.org/10.5878/001853
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    (29567), (1591558), (72435)Available download formats
    Dataset updated
    Jul 7, 2016
    Dataset provided by
    Uppsala University
    Authors
    Swedish National Heritage Board, UV Öst
    Time period covered
    1050 - 2000
    Area covered
    Kristberg Parish, Motala Municipality, Sweden
    Description

    The ZIP file consist of GIS files and an Access database with information about the excavations, findings and other metadata about the archaeological survey.

  20. b

    Public Training

    • newgis.brla.gov
    Updated Jul 9, 2020
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    East Baton Rouge GIS Map Portal (2020). Public Training [Dataset]. https://newgis.brla.gov/feedback/surveys/cd1f065e745d4e27bca7111a4ffb7b26
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    Dataset updated
    Jul 9, 2020
    Dataset authored and provided by
    East Baton Rouge GIS Map Portal
    Area covered
    Description

    This survey is intended to solicit feedback from the general public for developing free training sessions utilizing data and maps in the EBRGIS Portal.

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Bureau of Indian Affairs (BIA) (2025). BOGS Training Metrics [Dataset]. https://catalog.data.gov/dataset/bogs-training-metrics
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BOGS Training Metrics

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Dataset updated
May 9, 2025
Dataset provided by
Bureau of Indian Affairshttp://www.bia.gov/
Description

Through the Department of the Interior-Bureau of Indian Affairs Enterprise License Agreement (DOI-BIA ELA) program, BIA employees and employees of federally-recognized Tribes may access a variety of geographic information systems (GIS) online courses and instructor-led training events throughout the year at no cost to them. These online GIS courses and instructor-led training events are hosted by the Branch of Geospatial Support (BOGS) or offered by BOGS in partnership with other organizations and federal agencies. Online courses are self-paced and available year-round, while instructor-led training events have limited capacity and require registration and attendance on specific dates. This dataset does not any training where the course was not completed by the participant or where training was cancelled or otherwise not able to be completed. Point locations depict BIA Office locations or Tribal Office Headquarters. For completed trainings where a participant location was not provided a point locations may not be available. For more information on the Branch of Geospatial Support Geospatial training program, please visit:https://www.bia.gov/service/geospatial-training.

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