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.

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

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.

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

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.

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.

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

Study area

The Kalmthoutse Heide is a nature reserve situated north of Kalmthout, in the province of Antwerp, Flanders, Belgium. It is part of the Cross-Border Nature Park De Zoom - Kalmthoutse Heide in the Netherlands and Belgium. The Kalmthoutse Heide is managed by the Flemish Agency for Nature and Forest and consists of wet and dry heathlands, inland dunes, forests and moorland pools. In this area, there is particular interest in monitoring the encroachment of the heathlands by Molinia caerulea and Campylopus introflexus.

Data collection

Data were collected by the Research Institute for Nature and Forest (INBO) with a fixed wing drone Gatewing X100 in 2015 and 2016 (8 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.

Data processing

The raw data were processed to Digital Surface Models and orthophotos by the Flemish Institute for Technological Research (VITO) in 2017. Images with coarse GPS coordinates were imported and processed in Agisoft PhotoScan Pro 1.4.x, a structure-from-motion (SfM) based photogrammetry software program. After extraction and matching of tie points, a bundle adjustment leads to a sparse point cloud and a refined set of camera position and orientation values. Ground control points (either artificially installed markers on the terrain, or other photo-identifiable points, measured on the ground with RTK GNSS) were used to further refine the camera calibration and obtain a pixel-level georeferencing accuracy. From there, a point cloud densification and classification into ground and non-ground points was performed, leading to a rasterized digital surface model (DSM) and digital terrain model (DTM). Finally, a true orthomosaic was projected onto the DTM.

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_KH_x.zip).
• Processed data: Digital Surface Models (filename_DSM.tif) and orthophotos (filename_Ortho.tif) stitched together from the raw data. The included flights are indicated in the file name (e.g. 3 flights for 20150717_KH_1-3_DSM.tif).
• Ground control points: temporary ground control points were placed for the first flights on 2015-07-17 (visible in 20150717_KH_1-3_Ortho.tif). Coordinates for these are available in GCP_20150717_KH.tsv.

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.

• http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150717_KH_1-3_DSM.tif
• http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150717_KH_1-3_Ortho.tif RGB
• http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20151020_KH_1-2_DSM.tif
• http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20151020_KH_1-2_Ortho.tif RGB
• http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20151020_KH_3_DSM.tif
• http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20151020_KH_3_Ortho.tif RGB
• http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20160205_KH_1-2_DSM.tif
• http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20160205_KH_1-2_Ortho.tif RGB

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

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.

• http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150728_Bilzen_1_Ortho.tif RGB
• http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150728_Bilzen_2_DSM.tif
• http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150728_Bilzen_2_Ortho.tif CIR
• http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150728_Bilzen_1_DSM.tif

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

Study area

Averbode Bos & Heide is a nature reserve situated near the locality of Averbode, in the province of Flemish-Brabant, Flanders, Belgium. The area is managed by the nature conservation NGO Natuurpunt and consists of wet and dry heathlands, inland dunes, forests and moorland pools. In the years prior to the drone flights, large stands of mostly coniferous trees were cut to enable ecological restoration of heathlands and moorland pools. The drone flight was triggered by a particular interest to monitor the effects of this restoration.

Data collection

Data were collected by the Research Institute for Nature and Forest (INBO) with a fixed wing drone Gatewing X100 in 2015 and 2016 (6 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 the Flemish Institute for Technological Research (VITO) in 2017. Images with coarse GPS coordinates were imported and processed in Agisoft PhotoScan Pro 1.4.x, a structure-from-motion (SfM) based photogrammetry software program. After extraction and matching of tie points, a bundle adjustment leads to a sparse point cloud and a refined set of camera position and orientation values. From there, a point cloud densification and classification into ground and non-ground points was performed, leading to a rasterized digital surface model (DSM) and digital terrain model (DTM). Finally, a true orthomosaic was projected onto the DTM.

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_ABH_x.zip).

Processed data: Digital Surface Models (filename_DSM.tif) and orthophotos (filename_Ortho.tif) stitched together from the raw data. The included flights are indicated in the file name (e.g. 3 flights for 20150928_ABH_1-2_20151001_ABH_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.

http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150928_ABH_1-2_20151001_ABH_1_DSM.tif

http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20150928_ABH_1-2_20151001_ABH_1_Ortho.tif RGB

http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20151001_ABH_2_DSM.tif

http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20151001_ABH_2_Ortho.tif RGB

http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20160401_ABH_1_DSM.tif

http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20160401_ABH_1_Ortho.tif RGB

http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20160401_ABH_2_DSM.tif

http://s3-eu-west-1.amazonaws.com/lw-remote-sensing/cogeo/20160401_ABH_2_Ortho.tif CIR

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

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.html#technische_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.html#technische_details Link zur Seilaplan-Website: https://seilaplan.wsl.ch

An overview of benthic habitat surveys in Western Australia, combining surveys from multiple State Government agencies, research institutions and Universities. Disclaimer: The map is in development and does not show real or comprehensive survey data until this message disappears. Contributing data Attendees of the Managing Coastal Vulnerability workshop can: Register your account and contact us. We will give you write permission by making you admin or editor of your organisation, and member of the Habitat Sampling Initiative Group. Add metadata for your data by creating a dataset, attach a GeoJSON (QGIS video tutorial, save as CRS EPSG 4326/WGS84) or KML file of your surveyed transects (including survey date or period in site attributes if possible) as resources, and add the dataset to the group Habitat Sampling Initiative. Add the link to your access-restricted data on Pawsey as another resource to the dataset. Add any other public data resource here if and when appropriate. Use the CKAN API to upload metadata from your existing catalogues following these examples. Discovering data The following resources give an interactive overview of all Habitat Sampling Initiative datasets:

An overview of benthic habitat surveys in Western Australia, combining surveys from multiple State Government agencies, research institutions and Universities. Disclaimer: The map is in development …Show full descriptionAn overview of benthic habitat surveys in Western Australia, combining surveys from multiple State Government agencies, research institutions and Universities. Disclaimer: The map is in development and does not show real or comprehensive survey data until this message disappears. Contributing data Attendees of the Managing Coastal Vulnerability workshop can: Register your account and contact us. We will give you write permission by making you admin or editor of your organisation, and member of the Habitat Sampling Initiative Group. Add metadata for your data by creating a dataset, attach a GeoJSON (QGIS video tutorial, save as CRS EPSG 4326/WGS84) or KML file of your surveyed transects (including survey date or period in site attributes if possible) as resources, and add the dataset to the group Habitat Sampling Initiative. Add the link to your access-restricted data on Pawsey as another resource to the dataset. Add any other public data resource here if and when appropriate. Use the CKAN API to upload metadata from your existing catalogues following these examples. Discovering data The following resources give an interactive overview of all Habitat Sampling Initiative datasets:

Elenco di 144 tutorial del canale Youtube TutorielGeo: https://www.youtube.com/user/tutorielgeo/featured Più di 200 video tutorial gratuiti su Qgis, Postgis, Geoserver, Pentaho, Talend, Google Earth Pro... così come le tecnologie di webmapping e la gestione dei database: Oracle, Mysql, SQL Server. Ecco il link al negozio: https://play.google.com/store/apps/details?id=com.tutorielgeo.mobileapps

Ecco il link al sito: https://tutorielgeo.com

Ecco il link di Youtube channel:https://www.youtube.com/user/tutorielgeo

Ecco il link alla pagina facebook: https://www.facebook.com/Tutorielgeo-Geomatic-Tutorial-GIS-Tutorial-Webmapping-Tutorial-325658277554574/

Ecco il link all'account Twitter: https://twitter.com/TutorielGeo

Ecco il link alla pagina Google Plus: https://plus.google.com/b/117203987416263637144/+tutorielgeo/posts

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

Προκειμένου να χρησιμοποιηθεί το πρόσθετο QGIS «Seilaplan» για τον ψηφιακό σχεδιασμό καλωδίων, απαιτείται ένα ψηφιακό μοντέλο εδάφους (DTM). Σε αυτό το βίντεο εκμάθησης, δείχνουμε πώς να συγχωνεύσουμε πολλαπλά πλακίδια DTM raster σε ένα αρχείο, χρησιμοποιώντας το εργαλείο QGIS «Virtual Raster». Αυτό απλοποιεί τον ψηφιακό σχεδιασμό μιας καλωδιακής γραμμής χρησιμοποιώντας το πρόσθετο QGIS «Seilaplan». Παρακαλείστε να σημειώσετε ότι η γλώσσα διδασκαλίας είναι η γερμανική! Σύνδεσμος προς την ιστοσελίδα της Seilaplan: 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 einzigen Rasterfile zusammenfügen und abspeichern kann. Θα ήθελα να σας πω ότι δεν μπορώ να κάνω κάτι τέτοιο, αλλά δεν μπορώ να το κάνω αυτό. Σύνδεσμος zur Seilaplan-Ιστοσελίδα: https://seilaplan.wsl.ch Παρακαλείστε να σημειώσετε ότι η γλώσσα διδασκαλίας είναι η γερμανική!

Σύνδεσμος προς την ιστοσελίδα της Seilaplan: 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 einzigen Rasterfile zusammenfügen und abspeichern kann. Θα ήθελα να σας πω ότι δεν μπορώ να κάνω κάτι τέτοιο, αλλά δεν μπορώ να το κάνω αυτό.

Σύνδεσμος zur Seilaplan-Ιστοσελίδα: https://seilaplan.wsl.ch