We would like to thank the developers, documenters, testers and all the many folks out there who volunteer their time and effort (or fund people to do so). From the QGIS community we hope you enjoy this release! If you wish to donate time, money or otherwise get involved in making QGIS more awesome, please wander along to qgis.org and lend a hand!
QGIS is supported by donors and sustaining members. A current list of donors who have made financial contributions large and small to the project can be seen on our donors list. If you would like to become a sustaining member, please visit our page for sustaining members for details. Your support helps us fund our six monthly developer meetings, maintain project infrastructure and fund bug fixing efforts.
QGIS is Free software and you are under no obligation to pay anything to use it – in fact we want to encourage people far and wide to use it regardless of what your financial or social status is – we believe empowering people with spatial decision making tools will result in a better society for all of humanity.
Be ready for the cold weather with a smooth coordinate search, filters in the value relation widget, fancy new QML and HTML widgets, enhanced geometry editing functionalities and an expandable legend. Right when Autumn starts, QField 1.7 Rockies hits the stage.
The days are getting shorter and the wind blows colder. It’s always good to be in a good company outside while getting your mapping work done. QField will be your reliable companion.
We know, QField 1.6 Qinling has only been out two months and with its amount of new features and stability improvements, it would have deserved a longer primetime. But we just couldn’t withhold you all the new great stuff we’ve been building lately.
So let’s welcome QField 1.7 Rockies. And yes, we mean THE Rockies, where QField is looking for plenty of new buddies.
Let’s have a look.
Merging features
Splitting of a feature has been possible for quite some time. Now the merging of features of multipolygon-layer is possible as well. Select them and merge them – easy like that. The first selected feature gets the new geometry and keeps its attributes.
Filters in the Value Relation Widget
The value relation widgets provide an easy selection of a related feature. Often it’s used for lookup tables but sometimes the related tables contain a lot of entries and the list of the possible values is long.
Using filters in the value relation drop-down can increase the efficiency in selecting the correct value. It can be configured by expressions in QGIS, so it’s possible to have the content of the drop down depend on the values entered previously in other fields.
In the screenshot above there is a Map Value Widget with “forest” and “meadow” as values. On selecting “forest”, only the trees appear in the Field “Plant Species”. On selecting “meadow” there would be listed flowers instead.
Go to coordinates in the Search
The search has not only been improved in its appearance, but it’s handling is much more comfortable with a button to clear the text and easy opening and closing.
Additionally, we added the possibility to jump to coordinates. Searching a place you know the coordinates of is now super simple. And this means that digitizing that precise geometry with known coordinates is finally possible.
QML and HTML Widget
You might remember when we introduced the QML widget in QGIS. Now it’s in QField as well. And it’s not alone. HTML widgets are supported too.
This provides a lot of possibilities to display information with texts, images and charts and it even allows you interaction. Do you need help setting up complex forms? Don’t hesitate to get in touch with us!
Expandable legend icons
The legend items are now expandable and collapsible.
Wait a minute… Wasn’t this possible before? Yes. It was possible in earlier versions. But why it’s announced here as a new feature?
Some technical background: As you may be aware QField uses QGIS under the hood and QGIS uses Qt under the hood. Qt is currently used in version 5. Qt 5 is not that young any more and has a lot of functionality which is no longer supported by Qt. The old legend was based on the tree view, a deprecated module. Using it had some implications like the suboptimal support of HiDPI. Furthermore, these deprecated modules will disappear in the soon-to-come Qt 6.
As you can see, keeping QField at the quality we and you expect requires a lot of maintenance work. It is of utmost importance and only possible thanks to sponsoring since paying for fixing already existing features is less attractive for most people.
What will the future bring
In the last weeks, we have been highly busy on coding, testing and promoting QFieldCloud and we are very happy to be able to announce it very soon. So be prepared.
QField is an open source project. This means that whatever is produced is available free of charge. To anyone. Forever. This also means that everyone has the chance to contribute. You can write code, but you don’t need to. You can also help translating the app to your language or help out writing documentation or case studies or by sponsoring a new feature.
And now…
… enjoy QField 1.7 Rockies and have a nice autumn!
In 2015 we have already published a blog on this topic, which has met with great response. In the meantime a lot has changed in the QGIS world and with QGIS3 the 2015 manual can no longer be adopted 1:1. So I decided to write a new, revised blog article on this topic.
A lot of people are using QGIS Cloud as a service with ready to use QGIS webclient. It’s very easy to publish data and share maps in this way.
The 2016 post More icons & symbols for QGIS still regularly makes it to the top 10 list of posts by visitors. I wouldn’t attribute this popularity to the quality of this particular post, however. Instead, it’s a pretty clear sign that QGIS users are actively searching for more styling resources to add to their installations.
When it comes to styling resources, the person to follow right now is clearly Klas Karlsson who’s been keeping a steady stream of styling-related posts coming to Twitter:
Created a style for manually placed measurements in #QGIS. This actually works better than expected. Turn on snapping. "click-click", and it's done. (well more or less…)https://t.co/x9JNloGPNkpic.twitter.com/w4xw0ctUio
Using aggregate() with 'collect' doesn't really aggregate all geometries… Am I missing something or should I file a bug report. (two layers, aggregate on green layer, not collecting all geometries in aggregate layer) pic.twitter.com/dYaLzQX51i
QGIS will drop 32-bit support on Windows after the QGIS 3.16 release when we update our Qt dependencies to Qt 5.15.
The Plan
QGIS will drop 32-bit Windows support in the next few months. QGIS 3.16 LTR will still be available for 32-bit systems. 32-bit support will be dropped during the process of updating Qt to version 5.15. Due to the complexity of the involved tasks, there is no fixed date for when this update will happen.
Reasoning
Over the last years, pretty much all new computers (including low-end machines) have been built with 64-bit processors. Our latest QGIS user survey (https://blog.qgis.org/2020/04/02/ltr-usage-survey/) confirmed that this move to 64-bit had been almost completed on the hardware side and only 7% of survey respondents indicated that they are still using 32-bit. Therefore, we have decided to phase out 32-bit support in QGIS since we have many libraries to update in the next months and we have only limited resources.
Further roadmap
The update to Qt 5.15 is an important step towards staying in sync with Qt developments. Qt 5.15 is the minimum version that will provide forward compatibility with Qt 6. By updating to 5.15, we, therefore, ensure that QGIS is future proof.
As a follow-up to the previous GRASS GIS 7.8.3 we have published the new release GRASS GIS 7.8.4 with more than 170 improvements. This minor release again focuses on wxGUI fixes, especially in the animation export, the layer management, 3D visualization and the data catalogue. Many display modules received fixes as well, and the vector digitizer now works as expected.
The Geographic Resources Analysis Support System (https://grass.osgeo.org/), commonly referred to as GRASS GIS, is an Open Source Geographic Information System providing powerful raster, vector and geospatial processing capabilities. It can be used either as a stand-alone application or as backend for other software packages such as QGIS and R geostatistics or in the cloud. It is distributed freely under the terms of the GNU General Public License (GPL). GRASS GIS is a founding member of the Open Source Geospatial Foundation (OSGeo).
QGIS more and more get’s to be installed ‘organisation wide’ by Windows Administrators (eg using SCCM, now Microsoft Endpoint Configuration Manager ), instead of personal installations by the GIS-people on their personal machines. I get more and more questions about this (eg here) So a short post about this. The good thing is that peeps […]
QGIS 3.16 on macOS coming with Proj6, GDAL3 and major fixes!
macOS packaging mechanism is completely reworked for QGIS 3.16.
This will bring QGIS on macOS on par with other platforms that already benefit from the new versions of
PROJ and GDAL libraries - especially the greatly improved reprojection support.
QGIS nightly and QGIS 3.16
If you want to try the new packages, download and install the QGIS from nightly builds.
There are still few weeks before QGIS 3.16 release for testing and bug-fixing, so make sure you report all your issues before the
23rd October 2020. Multiple packages now can be installed side-by-side, just rename or move the installed QGIS.app!
The earlier packages were based on Homebrew, but we didn’t have control over the versions of dependencies.
We switched to the new system where we have full control, which is important for good quality releases.
The package/installer is not yet notarized by Apple, so you need to right-click on the QGIS.app icon and open it to overcome the security control of
your macOS (only for 10.15+).
If you want to join the effort in testing and/or development of macOS packages, please drop me a mail on [email protected]
We have a dedicated Slack channel to discuss the maintenance of the macOS packages.
What is in the all-in-one bundle?
The goal is to have all advanced functionality of QGIS prepared and ready to use after simple one-click installation.
QGIS and utilities
QGIS Desktop, of course, but also
QGIS server (try with /Applications/QGIS.app/Contents/MacOS/bin/qgis_mapserver)
QGIS process (try with /Applications/QGIS.app/Contents/MacOS/bin/qgis_process)
QtDesigner for custom forms (/Applications/QGIS.app/Contents/MacOS/bin/designer)
ogr2ogr and various other gdal utilities
FOSS4G libraries
Geos 3.8.1
Proj 6.3.2
GDAL 3.1.2
GRASS 7.8.3
SAGA 7.3.0
Python 3.7
with pip, so you can install the missing packages with command
/Applications/QGIS.app/Contents/MacOS/bin/pip3 install <your package>
but, many packages are already preinstalled for you!
pipenv
requests
plotly
matplotlib
scipy
numpy
shapely
geopandas
gdal
h5py
pyproj
pillow
QGIS Processing
GRASS processing tools
GDAL processing tools
SAGA processing tools
OTB processing tools (needs external installation of OTB)
Data Providers
All basic providers
GeoPackage
Spatialite
DB2
WCS/WFS/OWS/WMS/WMTS
Vector Tiles
XYZ Tiles
OGR/GDAL
PostgreSQL
MDAL
But also:
ECW
MrSID
MSSQL
OracleDB
Acknowledgments
In Spring 2020, we prototyped the building of FOSS macOS libraries in completely controlled environment.
Few weeks ago we have successfully finished the QGIS 2020 Grant “QGIS macOS Package Improvements”.
This wouldn’t be possible without support from QGIS.org and its sponsors. And without proper testing and reporting of issues from our macOS power-users.
QGIS for iOS
Do you want to see your QGIS projects and data from your iPhone and iPad? Check InputApp
It is with great pleasure that on behalf of the PSC and the whole QGIS community I’d like to extend the most heartfelt congratulations to Anita for receiving the Sol Katz Award.
Anita has been a pillar of the QGIS community since she joined her first hackfest in Vienna in 2009. Since then she has been pushing QGIS’ boundaries and has helped thousands of people to do so through all her publications, ideas and answers on her blog, stackexchange, on the QGIS documentation and in the 7(!) books she co-authored on QGIS. Anita is also the author of the hugely popular TimeManager QGIS plugin that was the precursor of the temporal manager added in QGIS 3.14.
Since 2013 Anita has been an irreplaceable member of the PSC. Dedicated, precise, and foremost always ready to lend a helping hand, Anita is a unique example of a passionate Open Source advocate.
Thanks for all you do Anita and congratulations, nobody deserved the Sol Katz award more than you!
The Sol Katz Award for Geospatial Free and Open Source Software (GFOSS) is awarded annually by OSGeo to individuals who have demonstrated leadership in the GFOSS community. Recipients of the award will have contributed significantly through their activities to advance open source ideals in the geospatial realm. The hope is that the award will both acknowledge the work of community members, and pay tribute to one of its founders, for years to come.
We have recently been working for the French Space Agency ( CNES ) who needed to store and visualize satellite rasters in a cloud platform. They want to access the image raw data, with no transformation, in order to fullfill deep analysis like instrument calibration. Using classic cartographic server standard like WMS or TMS is not an option because those services transform datasets in already rendered tiles.
We chose to use a quite recent format managed by GDAL, the COG (Cloud Optimize Geotiff) and target OVH cloud platform for it provides OpenStack, a open source cloud computing platform.
How it works
A COG file is a GEOTiff file which inner structure is tiled, meaning that the whole picture is divided in fixed size tile (256 x 256 pixels for instance) so you can efficiently retrieve parts of the raster. In addition to the HTTP/1.1 standard feature range request, it is possible to get specific tiles of an image through the network without downloading the entire raster.
We used a service provided by OpenStack, called Object Storage to serve the COG imagery. Object storage allows to store and retrieve file as objects using HTTP GET/POST requests.
Why not WCS ?
Web Coverage Service standard could have been an option. A WCS server can serve raw data according to a given geographic extent. It’s completely possible to deploy a container or a VPS (Virtual Private Server) running a WCS Server in a cloud plateform. The main advantages of the COG solution over WCS Server is that you don’t have to deal with the burden of deploying a server, like giving it ressources, configuring load balancing, handle updates, etc…
The beauty of COG solution is its simplicity. It is only HTTP requests, and everything else (rendering for instance) is done on the client side.
Step by step
Here are the different steps you’d have to go through if you’re willing to navigate in a big raster image directly from the cloud.
Install your openstack-client, it can be achieved easily with Python pip install command line
$ pip install python-openstackclient
Next, configure your openstack client in order to generate an athentification token. To do so you need to download your project specific openrc file to setup your environment)
$ source myproject-openrc.sh
Please enter your OpenStack Password for project myproject as user myuser:
**********
$ openstack token issue
+------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Field | Value |
+------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| expires | 2020-07-21T08:15:12+0000 |
| id | xxxx_my_token_xxxx
| project_id | 97e2e750f1904b41b76f80a50dabde0a |
| user_id | 18f7ccaf1a2d4344a4e35f0d84eb065e |
+------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
You are now good to push you COG file to the cloud instance
While panning in the map, QGIS will download only few tiles from the image in order to cover the view extent. The display latency that you could see in the video depends essentially on:
The number of band of your image
The pixel size
Your internet connection (mine, the one use for the video, is not an awesome one)
Note that the white flickering that you could see when you move in the map and the raster is refreshed should be removed in next version of QGIS according to this QEP.
What’s next ?
Thanks so much to the GDAL and QGIS contributors for adding such a nice feature ! It brings lots of possibilities for organizations that have to deal with great number of big raster and just want to explore part of it.
We are already thinking about further improvments (ease authentification, better integration with processing…), so if you’re willing to fund them or just want to know more about QGIS, feel free to contact us at [email protected]. And please have a look at our support offering for QGIS.
As people working in open source projects, we are constantly reminded that we are all standing on the shoulders of giants. However, particularly this year, we also see just how important small personal connections are. For me, my involvement with open source communities really took off when I joined the QGIS hackfest in Vienna in 2009 and I felt that my participation was really appreciated and welcome. I couldn’t imagine being without these connections anymore.
Thank you to the whole QGIS community, particularly my fellow PSC members both current and former: Tim, Andreas, Jürgen, Richard, Paolo, Otto, Marco Hugentobler, Alessandro, our new chair Marco Bernasocchi, and of course QGIS founder Gary Sherman for starting this awesome project and for still being around and actively promoting geospatial open source by publishing so many great books covering multiple different OSGeo projects.
I’d also like to thank my partner and my family for being incredibly understanding whenever I’m spend my time geeking out over a new programming project, data analysis, forum question, or conference talk.
Thank you also to my friends, colleagues and fellow members of the larger OSGeo community for sharing ideas, providing valuable feedback, and spreading the word about all the great work that’s going on all around us.
I’m constantly amazed by all the innovation happening to nourish and grow our community. And I’m looking forward to continue being a part of these efforts.
If you’re a follower of North Road’s social media accounts, it probably comes as no surprise to hear that we love sharing regular tips and useful suggestions about working with spatial data on these channels. Recently, we realised we were close to a new milestone of 4k followers of our Twitter stream. This milestone gave us the perfect excuse to give something back to all these followers! So we ran a little promo, where we promised that if we hit 4k followers we’d implement a new feature in QGIS, as determined by a popular vote:
*GIVE AWAY* We’re nearly at 4K followers! ? We love you guys, so as a thank-you to our wonderful community for sharing and liking our tweets we want to give YOU something! Vote for your favourite #QGIS feature below and we’ll add the most popular when we hit 4,000 followers!
Given we’ve now reached the target milestone, it was our turn to deliver! So we’re proud to introduce a new feature coming in QGIS 3.16: the ability to control exactly where labels are positioned along line feature! Let’s take a look!…
In previous QGIS releases, whenever labels are enabled for a line layer these labels will automatically gravitate towards the center of the line features:
In certain situations, it’s desirable for these labels to be positioned in specific positions along these line features (e.g. at the start of lines, or at the end of lines). With this new feature gift to the community, QGIS users have to option to precisely control the label placement for these lines:
There’s new options for placing the labels at the start of lines, end of lines, or at a custom offset along the line.
This option can be super-handy when combined with Rule Based Labelling, as it allows you to have different labels at the start versus end of lines:
So there we go! Another great QGIS cartography enhancement, heading your way in QGIS 3.16, and just a little thank you back to the community for all your support of North Road.
And if you’re not following us on social media yet, it’s a great to start… because who knows when our next little giveaway will be?!
QWAT est une application open source de gestion des réseaux d’eau potable émanant des collectivités de Pully, le SIGE à Vevey, Morges et Lausanne. QGEP est son homologue dédiée à la gestion des eaux usées et pluviales, initiée par le groupe utilisateur QGIS Suisse.
L’échange de données entre institutions est une pierre angulaire des politiques de l’eau. Ces échanges se basent sur des formats d’échanges standardisés. Ainsi les Cantons de Fribourg (format aquaFRI) ou de Vaud (format SIRE) conditionnent certaines subventions publiques à la transmission des données selon des formats pré-définis et permettent à ces échelons administratifs d’avoir une vision globale des réseaux humides.
Oslandia a été mandaté pour mettre en œuvre des instances de QWAT et QGEP, réaliser les extensions RAEPA pour chacun de ces outils, et aider Charente Eaux à charger les données des collectivités membres de ce syndicat mixte.
Le travail a été publié pour QWAT sous forme d’une extension standardisée dans le dépôt l’organisation QWAT https://github.com/qwat/extension_fr_raepa/
Pour QGEP, il n’existe pas encore de fonctionnalité pour gérer d’extension, le dépôt https://gitlab.com/Oslandia/qgep_extension_raepa/ contient donc les définitions de données et de vues à rajouter manuellement au modèle de données.
La compatibilité des modèles de données a été évaluée et le choix a été fait de ne faire que des vues dédiées à l’export de données. Il est techniquement possible de faire des vues éditables pour permettre le chargement de données via ces vues depuis des fichiers suivant le gabarit de données RAEPA. Le niveau de simplification et d’agrégation des listes de valeurs rend ce travail peu générique dans l’état actuel du géostandard (v1.1), il est donc plus pertinent à ce stade de réaliser des scripts de chargement sans passer par ce pivot dans le cas de Charente-Eaux
With the recent advancements in LiDAR survey technology and photogrammetry there has been a huge demand in capturing and storing point cloud data. Point cloud data are vector in nature, but are usually orders of magnitude larger than a standard vector layer. Typical vector datasets range from thousands to millions of features, while point clouds range from millions to billions or even trillions of points. Due to this sheer number of points a completely different approach to visualise, analyse and store point clouds is needed in a GIS platform.
Integrating a point cloud viewer in a desktop GIS application adds a lot of value for users compared to a specialised and dedicated point cloud viewer:
Point cloud data can be visualised, compared, and analysed alongside other types of spatial data (including vector, raster and mesh layers)
A familiar user interface and workflows
Integration with analytical tools to quickly create derived datasets
Despite these benefits, current versions of the QGIS desktop application do not support visualisation of point cloud data. With our partners at Lutra Consulting and Hobu, we have decided to bridge this missing gap and add point cloud support in QGIS, and are launching a new crowdfunding campaign to fund this work!
Head on over to the official crowd funding page here for the full details of the campaign, and for details on how you can contribute and make this work a reality.
We are delighted to announce that in collaboration with North Road and Hobu, we are running a crowdfunding campaign to implement native support for point cloud data in QGIS.
With the proposed changes, you will be able to load, style and visualise your point cloud data in QGIS in 2D and 3D map views.
The work will be carried out by the trusted and highly skilled developers across PDAL and QGIS community (Lutra Consulting, North Road and Hobu) who have been at the forefront of some of the exciting features in Open Source projects.
If you or your organisation are point cloud data users, this is your chance to bring native support for your data in QGIS. With this work, you will be able to overlay your point cloud data to your other data (vector/raster). The addition of native support for point cloud data in QGIS will pave the way to support analytical tools for point cloud data in future.
The target amount is 49,000 € and the campaign will be active until 15 October 2020.
Rendering large sets of trajectory lines gets messy fast. Different aggregation approaches have been developed to address this issue. However, most approaches, such as mobility graphs or generalized flow maps, cannot handle large input datasets. Building on M³ prototypes, the following approach can be used in distributed computing environments to extracts flows from large datasets.
This flow extraction is based on a two-step process, conceptually similar to Andrienko flow maps: first, we extract M³ prototypes from the movement data. In the second step, we determine flows between these prototypes, including information about: distribution of travel speeds and number of observed transitions. The resulting flows can be visualized, for example, to explore the popularity of different paths of movement:
After the prototypes have been computed, the flow algorithm computes transitions between pairs of prototypes. An object moving from prototype A to prototype B triggers an update of the corresponding flow. To allow for distributed processing, each node in the distributed computing environment needs a copy of the previously computed prototypes. Additionally, the raw movement data records need to be converted into trajectories. Afterwards, each trajectory is processed independently, going through its records in chronological order:
Find the best matching prototype for the current record
Ensure that the distance to the match is below the distance threshold and that the matched prototype is different from the previous prototype
Get or create the flow between the two prototypes
Ensure that the prototype and flow directions are a good match for the current record’s direction
Update the flow properties: travel speed and number of transitions, as well as the previous prototype reference
This approach scales to large datasets since only the prototypes, the (intermediate) flow results, and the trajectory currently being worked on have to be kept in memory for each iteration. However, this algorithm does not allow for continuous updates. Flows would have to be recomputed (at least locally) whenever prototypes changed. Therefore, the algorithm does not support exploration of continuous data streams. However, it can be used to explore large historical datasets:
2020, as we all know, has been an unusual year. In addition to all the other issues we have all faced, we also had to cancel our beloved hackfests. Since we first started holding bi-annual hackfests in 2009, this will be the first year without an in-person event where our friendly community can meet.
That can’t be! We are a modern and thriving community based on exchange, discussion and collaboration and should foster this even when physical meetings are not possible.
I’m super excited to announce that after some very motivating discussions on the HackFest telegram channel and in the PSC, starting from next week on every last Friday of each month we will hold an informal online virtual meeting to hack around, document, discuss and in general meet the awesome QGIS community.
Editing multiple features at the same time, support for stylus pens, dynamic configuration of image names and much more. QField 1.6 Qinling 秦岭 comes packed with awesome new features and an improved user experience.
We have been very busy over the last few months working on a new and shiny QField release. We have added many new features that increase efficiency on the field or allow for new workflows. In parallel, we have also been working on ironing out a series of issues and improving the overall user experience to make the app as pleasurable to use as possible. The result is QField 1.6 which has been published now.
Enough of the highlevel talking, let’s see what has been done.
Multi editing
Do you recall Geography lesson 101, Toblers first law? Everything is related to everything else. But near things are more related than distant things.
Very often there are similar objects nearby which share a property, tree species tend to group, human created objects like street light types or street paint markings tend to be of the same type at the same location.
With QField 1.6 it is now much easier to select a couple of features and change an attribute with very few taps. Identify a feature, long press an identify results, select more features and click the edit attributes button.
Stylus support
Sometimes it is just too cold to be working with fingers (although of course you can get capacitive gloves too). Or you just prefer to be working with a pen. QField 1.6 comes with support for stylus pens. If your device ships with one, give it a try.
Lock geometries
For some scenarios, especially in asset management, you only need to change attributes of existing objects and never add new features, delete features or change geometries. This can be configured through QFieldSync and set in the layer properties.
Image name configuration
Did you ever want to have the file names of your pictures to match the feature id, the layer name or any free text? The expression based configuration in QFieldSync offers now complete freedom in naming your images.
Legend and UX and legacy code
Didn’t expect to read UX and legacy code in one single title?
QML is the technology on which the QField user interface is built. QML ships a lot of user interface elements in a library called “Quick Controls”. A long time ago already it received an update from version 1 to version 2. Up to recently we still have been using some elements from version 1, which had an effect on high resolution displays not being able to properly display everything. To workaround that we introduced a lot of band aids, to improve the situation. We are very happy, that by migrating the legend and few other remaining elements to Quick Controls 2 in version 1.6, we have been able to completely drop this code.
Topological editing
QGIS can detect shared boundary by the features, so you only have to move a common vertex once, and QGIS will take care of updating the neighboring ones. So does his little college QField since this release.
Fast editing mode
For the real adventurers who know what they are doing this release brings the fast editing mode. In this mode, the features will automatically be stored on every change. The user interface is lighter and it combines perfectly with the topological editing.
Unter the hood
We have brought the whole technology stack up to speed with modern requirements. Proj and GDAL have been updated to recent versions. This helped to mitigate a couple of issues with coordinate transformations that were completely misplaced. It also paves the path for a future with datum corrections and always more important high precision measurements.
Known Issues
Unfortunately, we are experiencing a crash on startup with 32 bit devices. These devices are not that common any more, but if you have a device that is already a couple of years old it’s very well possible that it comes with a 32 bit cpu builtin. Despite the team’s hard efforts to isolate the reason, we were not able to find out what it was yet. Because of this we will not be able to update to 1.6 for these devices at the moment. We still hope that we will find a solution for this but don’t know yet when this will be.
We have updated proj to version 6. This brings plenty of bug fixes with coordinate handling. Among other things it adds support for using datum grids (gsb files) for very precise transformations, it is not yet possible to install those on the device. You will get an information message in the about dialog if your project happens to fall into this category. In this case, as a workaround switch the CRS of the project to a CRS with a known conversion that works without grid files.
What will the future bring
You guessed it already, we are not tired and have plenty of things stacked for the future. Prepare for more exciting updates for attribute forms and also for QFieldCloud which is right now being tested in our R&D labs.
QField is an open source project. This means that whatever is produced is available free of charge. To anyone. Forever. This also means that everyone has the chance to contribute. You can write code, but you don’t need to. You can also help translating the app to your language or help out writing documentation or case studies or by sponsoring a new feature.
Thanks to sponsors
Various organisations have helped to make this new release become a reality. Without the support of people in organisations who believe in the future of QField and open source tool for geospatial in general. The whole team behind QField would like to thank you with a big applause!
Today we had a small hackparty at Raymonds house. Focus: refocussing the qgis.nl blog site to the landing page of the Dutch QGIS user group. Ans yes, its there now :-).
