As you probably know, QGIS support for raster data (both reading and writing) is based on the GDAL library. One of the essential parts of raster handling is support for raster creation options — parameters that control specific details of the created file. For example, the GeoTIFF driver has options to control compression and whether the file should be tiled.
QGIS already allows setting these options when exporting raster dataset, GDAL algorithms in Processing of course, also support them. And not that long ago, I have implemented a corresponding widget wrapper for Processing and updated most of the native raster algorithms to support raster creation options out of the box.
Raster creation options in a QGIS Processing algorithm
However, there are more places in QGIS that could benefit from the creation options support, and I have recently started working in this direction. First, as a part of the QGIS bugfixing efforts, I updated the grid writer class used by QGIS’s native interpolation code to use the QgsRasterFileWriter API instead of writing output in the ASCII Grid format. This change not only allowed interpolation results to be saved in any GDAL-supported format but also paved the way for support for creation options and custom NODATA value.
The next step was the georeferencer. While the original ticket, I was working on, was about support for the BIGTIFF option, I decided to implement a more comprehensive fix and added full support for creation options.
Raster creation options in the QGIS georeferencer
After that, now in my spare time, I continued to improve the support for creation options in various places in QGIS. With the QgsGridFileWriter using the proper API, it was not too hard to implement support for custom NODATA values and creation options. For now, this is still an API-only change, as the Processing algorithms using this class are written in Python and have some known issues. I would rather wait and expose new functionality when porting them to C++.
My latest contribution is related to the QGIS Raster Calculator. After adding API to set creation options and change the NODATA value, I have also exposed this functionality to the UI both in the native tool and Processing algorithm.
Raster creation options in QGIS raster calculator (left — native tool, right — Processing algorithm)
I hope all these changes will make your raster analysis workflows easier and more productive, and output files smaller and faster to load.
Do not hesitate to contact me if you have any suggestions related to raster creation options support in QGIS.
OpenLitterMap is a citizen science project that aims to create a comprehensive, open-access database of litter and plastic pollution around the world. The data collected by the project are freely available to anyone for any purpose, including research, analysis, and advocacy. However, in order to access the data, one must manually construct a request and query the server. This is where OpenLitterMap for Processing comes in. The plugin allows you to select an area of interest on a map, specify a year for which you want to download data, and get a result.
Conefor (previously known as Conefor Sensinode) is a tool to quantify the importance of habitat areas and links for the maintenance of connectivity. It is also used to evaluate the impacts on connectivity of habitat and landscape changes. Conefor is used to conduct a spatial ecology analysis and conservation planning. The Conefor for Processing plugin contains tools to prepare data and perform all types of analysis available in the Conefor.
The new plugin is a great addition to the Circuitscape provider I have developed before. Together, these plugins create a powerful set of tools for spatial ecology and conservation, allowing researchers from different fields to predict the movements of animals, evaluate the impact of climate change on range shifts, analyse the spread of invasive species or disease, understand how landscape patterns affect gene flow, and much more.
To be effective on the battlefield, make informed and timely decisions, the army needs to analyse tons of data. While all information comes from various sources and in different forms, it ends up being laid out on a map. There are many ways to represent it, and one of them is by using special symbols like the ones described by NATO APP-6D and DOD MIL-STD-2525D standards.
The release of QGIS 3.0 “Girona” has been announced.
QGIS is a free and open-source geographic information system (GIS) running on Linux, Unix, Mac OS X, Windows, and Android (QField project). This release is named after the city of Girona, where the 15th QGIS developer meeting and the 2nd QGIS User Conference took place in spring 2016.
As this is the first release in the 3.x series, it is marked as an “early adopter release” and is aimed at enthusiasts and advanced users. Of course, anyone can install it, but keep in mind that this version is not yet as stable and polished as the 2.x series. Also, note that QGIS 2.14 has reached its end of life and QGIS 2.18 is now LTR.
As QGIS 3.0 has entered the “hard freeze” phase, it is time to update the plugins. I decided to start with Processing providers, as they are the most relevant. As of today, all of them are updated and available for installation from my plugin repository:
Circuitscape for Processing — analysis of heterogeneous landscapes (for example, to model movement, gene flow of plants and animals, or to identify areas important for connectivity conservation)
WhiteboxTools provides a set of spatial analysis tools, primarily for raster data. It was developed as a response to numerous requests coming from users of the specialized GIS called Whitebox GAT. People wanted to use Whitebox GAT functionality in automated data processing workflows. At the time of this post, WhiteboxTools already contains more than 250 tools from Whitebox GAT and about the same number will be added in the near future. The WhiteboxTools for Processing plugin I have developed integrates these tools into QGIS.
The plugin is already available from my plugin repository. Only QGIS 3.0 (or newer) is supported. Currently, the plugin has an experimental status, so do not forget to enable experimental plugins in the QGIS Plugin Manager settings. In addition to the plugin, you should also download and install WhiteboxTools and specify their location in the Processing settings.
The release of QGIS 2.18 “Las Palmas” has been announced.
QGIS is a free and open-source geographic information system (GIS) running on Linux, Unix, Mac OS X and Windows. This release is named after the city of Las Palmas, where the QGIS developer meeting took place in November 2015.
This is the last release in the 2.x series. Development efforts are now focused on QGIS 3, which is scheduled for release at the end of the first quarter of 2017. QGIS 2.14.x remains the current release with long-term support and it will be maintained until the next LTR version based on QGIS 3 is released.
The second (and first for me) QGIS User Conference is over. More than 150 participants, 9 workshops in three parallel sessions, 18 presentations from people all over the world: two incredibly busy days flew really fast.
Workshops from QGIS core developers and the most experienced community members were interesting and useful for both beginners and those who have been using QGIS for a long time. Personally, I managed to attend four workshops:
From data model to QGIS project — Matthias Kuhn and Andreas Neumann were showing how to prepare data and setup QGIS to comfortably use datasets containing lots of interdependent tables with and without spatial information.
QGIS Cartography Tips and Tricks — Alexandre Neto demonstrated QGIS capabilities to create beautiful printed maps. The workshop was dedicated not only to the use of Print Composer and Atlas functionality but also highlighted powerful QGIS features for layer styling, labeling, using map themes, and multiple styles for a single layer.
Advanced Processing — actually, I attended this workshop not as an ordinary participant, but as a second mentor. Together with Victor Olaya we showed some “secret” features of Processing that could take analysis productivity to the next level.
Your first steps in Python with QGIS — led by Martin Dobias and targeted at beginners who want to automate their work by developing scripts and plugins. I attended this workshop to see how others talk about PyQGIS and maybe borrow some ideas for my own workshops.
18 presentations on a wide range of topics once again confirmed that QGIS turned from a “pet project” into a full-fledged competitor of such well-known products as ArcMap and MapInfo a long time ago. It was very interesting to listen to reports on the migration of government agencies to QGIS as well as on using QGIS in conservation and educational institutions. Presentations about new QGIS features, plugins, and other related developments, such as QGIS Server clients, were also captivating.
Many thanks to the organizers for their hospitality and impeccable organization of the conference.
