The rise of QGIS has been significant in the last few years as this software, an open source project that started in 2002, has been developed by a broad community.
Back in 2005, the tool was mostly a visualization aid for spatial data. However, within a few short years it gained additional spatial analysis capabilities that benefited both raster and vector data approaches. In recent years, visualization has also greatly improved by the integration of time-based visuals and 3D capabilities.
The Power of QGIS
- QGIS, currently the QGIS 3.x series, is a leading open source tool that has become a powerful tool used by researchers, governments, and others.
- Allows a wide range of spatial analysis with hundreds of plugins to add additional capability. This includes popular plugins for model development, integration with Google Maps, and PostgreSQL.
- Software is rapidly evolving with new versions released every four months and a large user and developer community contributing to enhance features.
The evolution of QGIS has led to it become a common tool used for consulting and research. Developers now from major corporations are contributing to the project as they apply it for their own business applications.
One reason for this is that QGIS offers plugin support for development, with pyQGIS, a Python-based support system, used to help build plugins. Common plugins include the GDAL tool, which offers a GUI for various raster management functions. Another tool is the OGR conversion tool that allows vector layer conversion.
There are also popular plugins that allow interfaces with other GIS tools such as GRASS or use popular base maps such as OpenStreetMaps. Popularity of other tools such as Google Earth has led developers to want to integrate these tools within QGIS, leveraging popular free tools within QGIS.
While QGIS is evolving into effectively a diverse set of geospatial services, it still acts as a geospatial data editor at its core and can also be used as a server using the QGIS Server plugin, where it provides WMS, WFS, and WCS implementation.
Spatial databases are a key part of any geospatial stack and QGIS is easily connected to PostGIS, an extension of Postgre SQL, for powerful query and spatial database support.
Even emerging popular tools, such as the R statistical language, can now be applied directly within QGIS to aid with analyses and visualization. Python 3 has become the backbone of QGIS, where developers can contribute and upload their plugins to the ever growing list of plugins.
Perhaps the main reason QGIS became important was the fact it is an open source project, where students, once leaving university, found the prohibitive costs of Esri’s ArcGIS a powerful incentive to adapt to using QGIS.
This helped to increase the user community while also increasing interest for developers to contribute more geospatial capabilities and analyses. The wide range of uses and large user community has increased activity by developers to improve how QGIS can be used for spatial analysis, what might be called a type of democratization of GIS.
Open source tools are not always popular, often because they may not get much support or they have a high learning threshold and can be notoriously full of computer bugs. However, for QGIS, updates are constant and when a new update is given, it also becomes backwards compatible so that users do not have to download the latest release. Users can choose between downloading the long-term release or constantly updating to the newest release if they offer fixes to specific problems or updated functionality.
Either way, the backwards compatibility means that it is not necessary to update the QGIS projects they are currently working on.
Developers also learn from other features popular with users, such as Adobe Photoshop’s blending mode, where this feature can now be used in QGIS so that layers can be blended to each other in visualization.
Geometry generators also offer the capability to visualize different types of geometries. For instance, a polygon could be shown as a centroid. For some users familiar with Esri’s ArcGIS model builder, the QGIS model builder also provides a graphic interface that allows you to add data sources and processing algorithms, helps to automate spatial analyses, particular repetitive tasks. All of this can be exported for further development, if desired, using the Python code that the builder automatically builds for you.
Some features that may be in future development for QGIS include more development on animations, including in 3D, and using time sequences. Users also want increasing use of mesh data that integrates vector and raster data together. Finally, as development has happened rapidly, documentation has fallen behind so this is also a likely area that will require work so that users are better able in taking advantages of all the tools offered.
Mobile Data Applications
- An example of how QGIS can be a powerful tool is the application of open source mobile apps that can interface with QGIS, including QField and Input.
- Mobile apps can allow you to collect data in the field and even be able to, in real-time, update your QGIS database with data provided via the Cloud.
- Users can preset attributes that are either auto-populated or inputted.
- Apps can be used offline or online along with basemaps, with vector and raster support.
Perhaps an example of the growing power of QGIS is how mobile applications have been integrated with this tool in recent years.
Mobile applications are becoming popular in their use for data collection, particular in the field when researchers or data collectors are deployed to capture relevant geospatial data.
This was highlighted by Kurt Menke in another podcast.
These tools can now be integrated and work with QGIS as a way to interface with QGIS while you are on their mobile device.
Two popular tools that do this are QField, developed by OPENGIS.ch, and Input, developed by Lutra Consulting. These tools are very similar and both work off project files in QGIS so that they can work with and synchronize with a QGIS project. Both the tools are available on Android devices, while Input is also available in iOS.
In these tools, users can setup attributes and data columns that are then populated with different data. This includes date and time, names, spatial data, and even video and images. Formats for vector and raster are supported.
While existing data can be used, field collected data can be integrated. Some of the data could be automated, such as date and time, while others could be manually inputted.
Imagery can be given as links to the data files and comments and other meta-data could even be provided using the applications with the data marked up. Location data can be improved using third party GPS applications that connect to your Bluetooth, allowing more accurate location data to be collected.
There are offline and online versions for both QField and Input. MBTiles, for instance, can be used in the offline mode as a basemap. Input provides a plugin, called Mergin, that also allows you to use the Cloud to synchronize your data. You can also download and drag and drop data once you are back in the office and can use your QGIS database to update files.
What such tools show is that open sources tools such as QField and Input have become just as powerful as proprietary tools and can work in concert with QGIS. In the future, collaborative editing is another function that might be added and meta-data access and support to improve meta-data development are also areas these tools could develop next. What they now show is that fieldwork tools have arrived and make another powerful way in which to use QGIS by interfacing and working with it to make a more effective project and research.
Mobile applications can be integrated with QGIS to make it possible to do our work and update our data virtually anywhere.
 For more on QGIS, see: Menke, Kurt. Discover QGIS: The Workbook for the Award Winning GeoAcademy Curriculum. Chugiak, AK: Locate Press, 2016. For examples on the more recent QGIS 3.x, see: Menke, Kurt. Discover QGIS 3.X: A Workbook for the Classroom or Independent Study, 2019. (Amazon | Bookshop)
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