24 datasets found
  1. 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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    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.

  2. H

    GeoServer Tutorials

    • hydroshare.org
    • beta.hydroshare.org
    zip
    Updated Aug 4, 2022
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    Jacob Wise Calhoon (2022). GeoServer Tutorials [Dataset]. https://www.hydroshare.org/resource/753127b14dd443a1a4f2cf9634835d7a
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    zip(14.4 MB)Available download formats
    Dataset updated
    Aug 4, 2022
    Dataset provided by
    HydroShare
    Authors
    Jacob Wise Calhoon
    License

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

    Description

    This resources contains PDF files and Python notebook files that demonstrate how to create geospatial resources in HydroShare and how to use these resources through web services provided by the built-in HydroShare GeoServer instance. Geospatial resources can be consumed directly into ArcMap, ArcGIS, Story Maps, Quantum GIS (QGIS), Leaflet, and many other mapping environments. This provides HydroShare users with the ability to store data and retrieve it via services without needing to set up new data services. All tutorials cover how to add WMS and WFS connections. WCS connections are available for QGIS and are covered in the QGIS tutorial. The tutorials and examples provided here are intended to get the novice user up-to-speed with WMS and GeoServer, though we encourage users to read further on these topic using internet searches and other resources. Also included in this resource is a tutorial designed to that walk users through the process of creating a GeoServer connected resource.

    The current list of available tutorials: - Creating a Resource - ArcGIS Pro - ArcMap - ArcGIS Story Maps - QGIS - IpyLeaflet - Folium

  3. GISF2E: ArcGIS, QGIS, and python tools and Tutorial

    • figshare.com
    pdf
    Updated Jun 2, 2023
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    Urban Road Networks (2023). GISF2E: ArcGIS, QGIS, and python tools and Tutorial [Dataset]. http://doi.org/10.6084/m9.figshare.2065320.v3
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    pdfAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Urban Road Networks
    License

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

    Description

    ArcGIS tool and tutorial to convert the shapefiles into network format. The latest version of the tool is available at http://csun.uic.edu/codes/GISF2E.htmlUpdate: we now have added QGIS and python tools. To download them and learn more, visit http://csun.uic.edu/codes/GISF2E.htmlPlease cite: Karduni,A., Kermanshah, A., and Derrible, S., 2016, "A protocol to convert spatial polyline data to network formats and applications to world urban road networks", Scientific Data, 3:160046, Available at http://www.nature.com/articles/sdata201646

  4. a

    On-screen Digitizing Using QGIS

    • gulf-coast-geospatial-geo-project.hub.arcgis.com
    Updated Oct 25, 2024
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    GEOproject_admin (2024). On-screen Digitizing Using QGIS [Dataset]. https://gulf-coast-geospatial-geo-project.hub.arcgis.com/documents/4280d05a4fdc4dc9a446cb791b2d9f05
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    Dataset updated
    Oct 25, 2024
    Dataset authored and provided by
    GEOproject_admin
    Area covered
    Description

    Grala, K., McMillen, Randall D., & Cartwright, J. H. (2022). On-screen Digitizing Using QGIS. Mississippi State University: Geosystems Research Institute. [View Document]GEO TutorialNumber of Pages: 13Publication Date: 08/2022This work was supported through funding by the National Oceanic and Atmospheric Administration Regional Geospatial Modeling Grant, Award # NA19NOS4730207.

  5. a

    Hotspot Analysis in GIS

    • gulf-coast-geospatial-geo-project.hub.arcgis.com
    Updated Feb 6, 2025
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    GEOproject_admin (2025). Hotspot Analysis in GIS [Dataset]. https://gulf-coast-geospatial-geo-project.hub.arcgis.com/items/8233bff0e1e2488288e19beac3afb2b2
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    Dataset updated
    Feb 6, 2025
    Dataset authored and provided by
    GEOproject_admin
    Description

    Raczynski, K., Nagel, A., & Cartwright, J. H. (2025). GEO Tutorial: Hotspot Analysis in GIS. Mississippi State University: Geosystems Research Institute. [View Document] GEO TutorialNumber of Pages: 5Publication Date: 06/2025This work was supported through funding by the National Oceanic and Atmospheric Administration Regional Geospatial Modeling Grant, Award # NA19NOS4730207.

  6. a

    Spatial Predicates: Preparing Residential Dataset

    • gulf-coast-geospatial-geo-project.hub.arcgis.com
    Updated Feb 6, 2025
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    GEOproject_admin (2025). Spatial Predicates: Preparing Residential Dataset [Dataset]. https://gulf-coast-geospatial-geo-project.hub.arcgis.com/documents/d90ca56fa70a4f42a4039ea67b6db26c
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    Dataset updated
    Feb 6, 2025
    Dataset authored and provided by
    GEOproject_admin
    Description

    Raczynski, K., Grala, K., & Cartwright, J. H. (2025). GEO Tutorial: Dealing with Coastal Flooding series, part 2: Spatial Predicates: Preparing Residential Dataset. Mississippi State University: Geosystems Research Institute. [View Document] GEO TutorialNumber of Pages: 7Publication Date: 06/2025This work was supported through funding by the National Oceanic and Atmospheric Administration Regional Geospatial Modeling Grant, Award # NA19NOS4730207.

  7. a

    Enhancing Maps with Charts in QGIS

    • gulf-coast-geospatial-geo-project.hub.arcgis.com
    Updated Feb 5, 2025
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    GEOproject_admin (2025). Enhancing Maps with Charts in QGIS [Dataset]. https://gulf-coast-geospatial-geo-project.hub.arcgis.com/documents/0f0241f7b4d84f2d98fa3ac12a60c364
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    Dataset updated
    Feb 5, 2025
    Dataset authored and provided by
    GEOproject_admin
    Description

    Raczynski, K., Grala, K., & Cartwright, J. H. (2025). Enhancing Maps with Charts in QGIS. Mississippi State University: Geosystems Research Institute. [View Document]GEO Tutorial Number of Pages: 7 Publication Date: 02/2025 This work was supported through funding by the National Oceanic and Atmospheric Administration Regional Geospatial Modeling Grant, Award # NA19NOS4730207.

  8. d

    Test Resource for OGC Web Services

    • search.dataone.org
    • hydroshare.org
    • +1more
    Updated Apr 15, 2022
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    Jacob Wise Calhoon (2022). Test Resource for OGC Web Services [Dataset]. https://search.dataone.org/view/sha256%3A59bae29350865fc2ca6d4c4d3f5995a2a51b7b0ebb9cc8414122cf46a63846c0
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    Dataset updated
    Apr 15, 2022
    Dataset provided by
    Hydroshare
    Authors
    Jacob Wise Calhoon
    Time period covered
    Aug 6, 2020
    Area covered
    Description

    This resource contains the test data for the GeoServer OGC Web Services tutorials for various GIS applications including ArcGIS Pro, ArcMap, ArcGIS Story Maps, and QGIS. The contents of the data include a polygon shapefile, a polyline shapefile, a point shapefile, and a raster dataset; all of which pertain to the state of Utah, USA. The polygon shapefile is of every county in the state of Utah. The polyline is of every trail in the state of Utah. The point shapefile is the current list of GNIS place names in the state of Utah. The raster dataset covers a region in the center of the state of Utah. All datasets are projected to NAD 1983 Zone 12N.

  9. a

    Creating And Animating Timeseries

    • gulf-coast-geospatial-geo-project.hub.arcgis.com
    Updated Feb 6, 2025
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    GEOproject_admin (2025). Creating And Animating Timeseries [Dataset]. https://gulf-coast-geospatial-geo-project.hub.arcgis.com/documents/ed72db1beafd4cd081a6bee4b0ca8de5
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    Dataset updated
    Feb 6, 2025
    Dataset authored and provided by
    GEOproject_admin
    Description

    Raczynski, K., Babineaux, C., & Cartwright, J. H. (2025). GEO Tutorial: Dealing with Coastal Flooding series, part 9: Creating And Animating Timeseries. Mississippi State University: Geosystems Research Institute. [View Document] GEO TutorialNumber of Pages: 5Publication Date: 06/2025This work was supported through funding by the National Oceanic and Atmospheric Administration Regional Geospatial Modeling Grant, Award # NA19NOS4730207.

  10. Supplementary material 5 from: Ryan Z, Clark E, Cundiff B, Nichols J,...

    • zenodo.org
    bin
    Updated Oct 16, 2024
    + more versions
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    Zoe Ryan; Emily Clark; Beatrice Cundiff; Joslyn Nichols; Maya Mahoney; Nkosi Evans; Thomas Campbell; Danny Kreider; Matt von Konrat; Zoe Ryan; Emily Clark; Beatrice Cundiff; Joslyn Nichols; Maya Mahoney; Nkosi Evans; Thomas Campbell; Danny Kreider; Matt von Konrat (2024). Supplementary material 5 from: Ryan Z, Clark E, Cundiff B, Nichols J, Mahoney M, Evans N, Campbell T, Kreider D, von Konrat M (2024) Open-source software integration: A tutorial on species distribution mapping and ecological niche modelling. Research Ideas and Outcomes 10: e129578. https://doi.org/10.3897/rio.10.e129578 [Dataset]. http://doi.org/10.3897/rio.10.e129578.suppl5
    Explore at:
    binAvailable download formats
    Dataset updated
    Oct 16, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Zoe Ryan; Emily Clark; Beatrice Cundiff; Joslyn Nichols; Maya Mahoney; Nkosi Evans; Thomas Campbell; Danny Kreider; Matt von Konrat; Zoe Ryan; Emily Clark; Beatrice Cundiff; Joslyn Nichols; Maya Mahoney; Nkosi Evans; Thomas Campbell; Danny Kreider; Matt von Konrat
    License

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

    Description

    QGIS Map Output Template (requires QGIS to open)

  11. a

    Joining Tables With Spatial Data

    • gulf-coast-geospatial-geo-project.hub.arcgis.com
    Updated Feb 6, 2025
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    GEOproject_admin (2025). Joining Tables With Spatial Data [Dataset]. https://gulf-coast-geospatial-geo-project.hub.arcgis.com/documents/dea76234848449c4a22965612572c441
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    Dataset updated
    Feb 6, 2025
    Dataset authored and provided by
    GEOproject_admin
    Description

    Raczynski, K., Xavier, F., & Cartwright, J. H. (2025). GEO Tutorial: Joining Tables With Spatial Data. Mississippi State University: Geosystems Research Institute. [View Document]

    GEO Tutorial Number of Pages: 6 Publication Date: 06/2025This work was supported through funding by the National Oceanic and Atmospheric Administration Regional Geospatial Modeling Grant, Award # NA19NOS4730207.

  12. a

    Calling Algorithms from Field Calculator in QGIS

    • gulf-coast-geospatial-geo-project.hub.arcgis.com
    Updated Nov 29, 2024
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    GEOproject_admin (2024). Calling Algorithms from Field Calculator in QGIS [Dataset]. https://gulf-coast-geospatial-geo-project.hub.arcgis.com/documents/2a92fb10e11843b88d480d1d6f6ac811
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    Dataset updated
    Nov 29, 2024
    Dataset authored and provided by
    GEOproject_admin
    Area covered
    Description

    Raczynski, K., Grala, K., & Cartwright, J. H. (2024). GEO Tutorial: Calling Algorithms from Field Calculator in QGIS. Mississippi State University: Geosystems Research Institute. [View Document]GEO TutorialNumber of Pages: 7Publication Date: 10/2024This work was supported through funding by the National Oceanic and Atmospheric Administration Regional Geospatial Modeling Grant, Award # NA19NOS4730207

  13. a

    Generating Viewsheds: a Visibility Analysis

    • gulf-coast-geospatial-geo-project.hub.arcgis.com
    Updated Feb 6, 2025
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    GEOproject_admin (2025). Generating Viewsheds: a Visibility Analysis [Dataset]. https://gulf-coast-geospatial-geo-project.hub.arcgis.com/documents/5f04d11488d84c7c9f8d2ebf314a9feb
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    Dataset updated
    Feb 6, 2025
    Dataset authored and provided by
    GEOproject_admin
    Description

    Raczynski, K., Grala, K., Raczynska, J., & Cartwright, J. H. (2025). GEO Tutorial: Generating Viewsheds: a Visibility Analysis. Mississippi State University: Geosystems Research Institute. [View Document] GEO TutorialNumber of Pages: 6Publication Date: 06/2025This work was supported through funding by the National Oceanic and Atmospheric Administration Regional Geospatial Modeling Grant, Award # NA19NOS4730207.

  14. Seilaplan Tutorial: DTM download from swisstopo website

    • envidat.ch
    mp4, not available
    Updated Jun 7, 2025
    + more versions
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    Laura Ramstein; Lioba Rath; Stephan Böhm; Pierre Simon; Christian Kanzian; Janine Schweier; Leo Gallus Bont (2025). Seilaplan Tutorial: DTM download from swisstopo website [Dataset]. http://doi.org/10.16904/envidat.343
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    mp4, not availableAvailable download formats
    Dataset updated
    Jun 7, 2025
    Dataset provided by
    Swiss Federal Institute for Forest, Snow and Landscape Research
    BOKU
    Authors
    Laura Ramstein; Lioba Rath; Stephan Böhm; Pierre Simon; Christian Kanzian; Janine Schweier; Leo Gallus Bont
    License

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

    Area covered
    Switzerland
    Dataset funded by
    WSL
    Bundesministerium für Landwirtschaft, Regionen und Tourismus Österreich
    Kooperationsplattform Forst Holz Papier
    Description

    In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. As an alternative to using the ‘Swiss Geo Downloader’ plugin, the DTM can be obtained directly from Swisstopo. In this tutorial we explain step by step how to download the necessary DTM from the Swisstopo Website, and how to use it in QGIS for the digital planning of a cable line using the plugin ‘Seilaplan’. Please note that the tutorial language is German! Link to the elevation model on the swisstopo website: https://www.swisstopo.admin.ch/de/geodata/height/alti3d.htmltechnische_details Link to the rope map website: https://seilaplan.wsl.ch

    Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. Als Alternative zum Swiss Geo Downloader erklären wir in diesem Tutorial Schritt für Schritt, wie man das nötige Höhenmodell von der Swisstopo Webseite herunterladen und in QGIS zur Seillinienplanung verwenden kann. Link zum Höhenmodell auf der swisstopo Webseite: https://www.swisstopo.admin.ch/de/geodata/height/alti3d.htmltechnische_details Link zur Seilaplan-Website: https://seilaplan.wsl.ch

  15. a

    Using Unsupervised Machine Learning For Land Use Land Cover Classification

    • gulf-coast-geospatial-geo-project.hub.arcgis.com
    Updated Feb 6, 2025
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    GEOproject_admin (2025). Using Unsupervised Machine Learning For Land Use Land Cover Classification [Dataset]. https://gulf-coast-geospatial-geo-project.hub.arcgis.com/items/9b48d400cc77474e89f2e804e7dd4f4d
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    Dataset updated
    Feb 6, 2025
    Dataset authored and provided by
    GEOproject_admin
    Description

    Raczynski, K., Xavier, F., & Cartwright, J. H. (2025). GEO Tutorial: Dealing with Coastal Flooding series, part 3A: Using Unsupervised Machine Learning For Land Use Land Cover Classification. Mississippi State University: Geosystems Research Institute. [View Document] GEO TutorialNumber of Pages: 5Publication Date: 06/2025This work was supported through funding by the National Oceanic and Atmospheric Administration Regional Geospatial Modeling Grant, Award # NA19NOS4730207.

  16. a

    3D Map Animations

    • gulf-coast-geospatial-geo-project.hub.arcgis.com
    Updated Feb 6, 2025
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    GEOproject_admin (2025). 3D Map Animations [Dataset]. https://gulf-coast-geospatial-geo-project.hub.arcgis.com/documents/781e1b7ec2c446bf92be59ed815fa87e
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    Dataset updated
    Feb 6, 2025
    Dataset authored and provided by
    GEOproject_admin
    Description

    Raczynski, K., Babineaux, C., & Cartwright, J. H. (2025). GEO Tutorial: Dealing with Coastal Flooding series, part 8: 3D Map Animations. Mississippi State University: Geosystems Research Institute. [View Document] GEO TutorialNumber of Pages: 5Publication Date: 06/2025This work was supported through funding by the National Oceanic and Atmospheric Administration Regional Geospatial Modeling Grant, Award # NA19NOS4730207.

  17. g

    Seilaplan Tutorial: Merge DTM tiles | gimi9.com

    • gimi9.com
    Updated Aug 30, 2022
    + more versions
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    (2022). Seilaplan Tutorial: Merge DTM tiles | gimi9.com [Dataset]. https://gimi9.com/dataset/eu_15cd0733-843f-4491-9998-f437b4cc1df4-envidat
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    Dataset updated
    Aug 30, 2022
    Description

    In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. In this tutorial video, we show how to merge multiple DTM raster tiles into one file, using the QGIS tool ‘Virtual Raster’. This simplifies the digital planning of a cable line using the QGIS plugin ‘Seilaplan’. Please note that the tutorial language is German! Link to Seilaplan website: https://seilaplan.wsl.ch *************************** Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. In diesem Tutorialvideo zeigen wir, wie man mit dem QGIS-Plugin Virtuelles Raster mehrere DHM-Kacheln zu einem einzigen Rasterfile zusammenfügen und abspeichern kann. Für die Seillinienplanung mit Seilaplan muss nun nur noch eine Datei, mein neues virtuelles Raster, ausgewählt werden. Link zur Seilaplan-Website: https://seilaplan.wsl.ch

  18. Orthophotos and DSMs derived from RPAS flights over wild boar damaged fields...

    • zenodo.org
    • data.niaid.nih.gov
    tiff, zip
    Updated Jul 23, 2024
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    Jeroen Vanden Borre; Jeroen Vanden Borre; Stijn Van Hoey; Stijn Van Hoey; Jeroen De Reu; Jeroen De Reu; Peter Desmet; Peter Desmet (2024). Orthophotos and DSMs derived from RPAS flights over wild boar damaged fields in Eigenbilzen in Flanders, Belgium [Dataset]. http://doi.org/10.5281/zenodo.3095763
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    tiff, zipAvailable download formats
    Dataset updated
    Jul 23, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Jeroen Vanden Borre; Jeroen Vanden Borre; Stijn Van Hoey; Stijn Van Hoey; Jeroen De Reu; Jeroen De Reu; Peter Desmet; Peter Desmet
    License

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

    Area covered
    Flanders, Belgium, Eigenbilzen
    Description

    Study area

    The study area in Eigenbilzen is situated in the agricultural zone east of the locality of Eigenbilzen, in the province of Limburg, Flanders, Belgium. The flights picture a wheat field where damage by wild boar is apparent.

    Data collection

    Data were collected by the Research Institute for Nature and Forest (INBO) with a fixed wing drone Gatewing X100 in 2015 (2 flights). RGB data were acquired using an off-the-shelf Ricoh GR Digital IV camera, with the following image bands: 1: red, 2: green, 3: blue, 4: alpha channel. CIR (color-infrared) data were acquired using a NIR-enabled Ricoh GR Digital IV camera, with the following info bands: 1: NIR, 2: red, 3: green, 4: alpha channel.

    Data processing

    The raw data were processed to Digital Surface Models and orthophotos by INBO in 2015 using Agisoft PhotoScan Pro 1.0.4, a structure-from-motion (SfM) based photogrammetry software program.

    Coordinate reference system

    All geospatial data have the coordinate reference system EPSG:31370 - Belgian Lambert 72.

    Files

    • Raw flight data: images and logs collected by the drone during flight. These files are zipped per flight, with the date (yyyymmdd) and flight number (x) indicated in the file name (flight_yyyymmdd_Bilzen_x.zip).
    • Processed data: Digital Surface Models (filename_DSM.tif) and orthophotos (filename_Ortho.tif) stitched together from the raw data. The included flight is indicated in the file name (e.g. 20150728_Bilzen_1_DSM.tif).
    • Ground control points: not applicable for this dataset.

    Cloud Optimized GeoTIFF

    The most efficient way to explore the processed data is by loading the Cloud Optimized GeoTIFFs we created for each processed file. Copy one of the file URLs below and follow e.g. the QGIS tutorial to load this type of file.

    See this page for an overview of public INBO RPAS data.

  19. e

    Seilaplan Tutorial: DTM download with SwissGeoDownloader

    • data.europa.eu
    unknown
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    EnviDat, Seilaplan Tutorial: DTM download with SwissGeoDownloader [Dataset]. https://data.europa.eu/data/datasets/659dc637-e0ca-4393-9f07-13b04290d6ec-envidat?locale=mt
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    unknown(429428137), unknownAvailable download formats
    Dataset authored and provided by
    EnviDat
    License

    http://dcat-ap.ch/vocabulary/licenses/terms_byhttp://dcat-ap.ch/vocabulary/licenses/terms_by

    Description

    In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. The plugin ‘Swiss Geo Downloader’, which is available for the open source geoinformation software QGIS, allows freely available Swiss geodata to be downloaded and displayed directly within QGIS. It was developed in 2021 by Patricia Moll in collaboration with the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. In this tutorial we describe how to download the high accuracy elevation model ‘swissALTI3D’ with the help of the ‘Swiss Geo Downloader’ and how to use it for digital planning of a cable line with the plugin ‘Seilaplan’. Please note that the tutorial language is German!

    Link to the Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader

    Link to Seilaplan website: https://seilaplan.wsl.ch

    Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. Das Plugin Swiss Geo Downloader, welches für das Open Source Geoinformationssystem QGIS zur Verfügung steht, ermöglicht frei verfügbare Schweizer Geodaten direkt innerhalb von QGIS herunterzuladen und anzuzeigen. Es wurde 2021 von Patricia Moll in Zusammenarbeit mit der eidgenössischen Forschungsanstalt Wald, Schnee und Landschaft WSL entwickelt. In diesem Tutorial beschreiben wir, wie man mit Hilfe des Swiss Geo Downloaders das hochgenaue Höhenmodell swissALTI3D herunterladen und für die Seillinienplanung mit dem Plugin Seilaplan verwenden kann.

    Link zum Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader

    Link zur Seilaplan-Webseite: https://seilaplan.wsl.ch

  20. a

    Calculating Spatial Statistics Of Inundated Areas

    • gulf-coast-geospatial-geo-project.hub.arcgis.com
    Updated Feb 6, 2025
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    GEOproject_admin (2025). Calculating Spatial Statistics Of Inundated Areas [Dataset]. https://gulf-coast-geospatial-geo-project.hub.arcgis.com/documents/95b427ded02743cd9c30c996d47cf5c9
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    Dataset updated
    Feb 6, 2025
    Dataset authored and provided by
    GEOproject_admin
    Description

    Raczynski, K., Nagel, A., & Cartwright, J. H. (2025). GEO Tutorial: Dealing with Coastal Flooding series, part 6: Calculating Spatial Statistics Of Inundated Areas. Mississippi State University: Geosystems Research Institute. [View Document] GEO TutorialNumber of Pages: 5Publication Date: 06/2025This work was supported through funding by the National Oceanic and Atmospheric Administration Regional Geospatial Modeling Grant, Award # NA19NOS4730207.

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QGIS Training Tutorials: Using Spatial Data in Geographic Information Systems [Dataset]. https://catalogue.arctic-sdi.org/geonetwork/srv/search?format=MOV

QGIS Training Tutorials: Using Spatial Data in Geographic Information Systems

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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.

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