tldr; Tired of working with large CSV files? Give GeoParquet a try!
“Parquet is a powerful column-oriented data format, built from the ground up to as a modern alternative to CSV files.”https://geoparquet.org/
(Geo)Parquet is both smaller and faster than CSV. Additionally, (Geo)Parquet columns are typed. Text, numeric values, dates, geometries retain their data types. GeoParquet also stores CRS information and support in GIS solutions is growing.
I’ll be giving a quick overview using AIS data in GeoPandas 1.0.1 (with pyarrow) and QGIS 3.38 (with GDAL 3.9.2).
File size
The example AIS dataset for this demo contains ~10 million rows with 22 columns. I’ve converted the original zipped CSV into GeoPackage and GeoParquet using GeoPandas to illustrate the huge difference in file size: ~470 MB for GeoParquet and zipped CSV, 1.6 GB for CSV, and a whopping 2.6 GB for GeoPackage:
Reading performance
Pandas and GeoPandas both support selective reading of files, i.e. we can specify the specific columns to be loaded. This does speed up reading, even from CSV files:
Whole file
Selected columns
CSV
27.9 s
13.1 s
Geopackage
2min 12s
20.2 s
GeoParquet
7.2 s
4.1 s
Indeed, reading the whole GeoPackage is getting quite painful.
Here’s the code I used for timing the read times:
As you can see, these times include the creation of the GeoPandas.GeoDataFrame.
If we don’t need a GeoDataFrame, we can read the files even faster:
Non-spatial DataFrames
GeoParquet files can be read by non-GIS tools, such as Pandas. This makes it easier to collaborate with people who may not be familiar with geospatial data stacks.
And reading plain DataFrames is much faster than creating GeoDataFrames:
But back to GIS …
GeoParquet in QGIS
In QGIS, GeoParquet files can be loaded like any other vector layer, thanks to GDAL:
Loading the GeoParquet and GeoPackage files is pretty quick, especially if we zoom into a small region of interest (even though, unfortunately, it doesn’t seem possible to restrict the columns to further speed up loading). Loading the CSV, however, is pretty painful due to the lack of spatial indexing, which becomes apparent very quickly in the direct comparison:
(You can see how slowly the red CSV points are rendering. I didn’t have the patience to include the whole process in the GIF.)
As far as I can tell, my QGIS 3.38 ‘Grenoble’ does not support writing to or editing of GeoParquet files. So I’m limited to reading GeoParquet for now.
However, seeing how much smaller GeoParquets are compared to GeoPackages (and also faster to write), I hope that we will soon get the option to export to GeoParquet.
For now, I’ll start by converting my large CSV files to GeoParquet using GeoPandas.
Oslandia is the main partner of OPENGIS.ch around QField. We are proud today to forward the announcement of the new QField release 3.4 “Ebo”.
Main highlights
A new geofencing framework has landed, enabling users to configure QField behaviors in relation to geofenced areas and user positioning. Geofenced areas are defined at the project-level and shaped by polygons from a chosen vector layer. The three available geofencing behaviours in this new release are:
Alert user when inside an area polygon;
Alert user when outside all defined area polygons and
Inform the user when entering and leaving an area polygons.
In addition to being alerted or informed, users can also prevent digitizing of features when being alerted by the first or second behaviour. The configuration of this functionality is done in QGIS using QFieldSync.
Pro tip: geofencing settings are embedded within projects, which means it is easy to deploy these constraints to a team of field workers through QFieldCloud. Thanks Terrex Seismic for sponsoring this functionality.
QField now offers users access to a brand new processing toolbox containing over a dozen algorithms for manipulating digitized geometries directly in the field. As with many parts of QField, this feature relies on QGIS’ core library, namely its processing framework and the numerous, well-maintained algorithms it comes with.
The algorithms exposed in QField unlock many useful functionalities for refining geometries, including orthogonalization, smoothing, buffering, rotation, affine transformation, etc. As users configure algorithms’ parameters, a grey preview of the output will be visible as an overlay on top of the map canvas.
To reach the processing toolbox in QField, select one or more features by long-pressing on them in the features list, open the 3-dot menu and click on the process selected feature(s) action. Are you excited about this one? Send your thanks to the National Land Survey of Finland, who’s support made this a reality.
QField’s camera has gained support for customized ratio and resolution of photos, as well as the ability to stamp details – date and time as well as location details – onto captured photos. In fact, QField’s own camera has received so much attention in the last few releases that it was decided to make it the default one. On supported platforms, users can switch to their OS camera by disabling the native camera option found at the bottom of the QField settings’ general tab.
Wait, there’s more
There are plenty more improvements packed into this release from project variables editing using a revamped variables editor through to integration of QField documentation help in the search bar and the ability to search cloud project lists. Read the full 3.4 changelog to know more, and enjoy the release!
After the initial ChatGPT hype in 2023 (when we saw the first LLM-backed QGIS plugins, e.g. QChatGPT and QGPT Agent), there has been a notable slump in new development. As far as I can tell, none of the early plugins are actively maintained anymore. They were nice tech demos but with limited utility.
However, in the last month, I saw two new approaches for combining LLMs with QGIS that I want to share in this post:
IntelliGeo plugin: generating PyQGIS scripts or graphical models
The workshop was packed. After we installed all dependencies and the plugin, it was exciting to test the graphical model generation capabilities. During the workshop, we used OpenAI’s API but the readme also mentions support for Cohere.
I was surprised to learn that even simple graphical models are actually pretty large files. This makes it very challenging to generate and/or modify models because they take up a big part of the LLM’s context window. Therefore, I expect that the PyQGIS script generation will be easier to achieve. But, of course, model generation would be even more impressive and useful since models are easier to edit for most users than code.
It uses a fine-tuned Llama 2 model in combination with spaCy for entity recognition and WorldKG ontology to write PyQGIS code that can perform a variety of different geospatial analysis tasks on OpenStreetMap data.
The paper is very interesting, describing the LLM fine-tuning, integration with QGIS, and evaluation of the generated code using different metrics. However, as far as I can tell, the tool is not publicly available and, therefore, cannot be tested.
Today marks the release of Trajectools 2.3 which brings a new set of algorithms, including trajectory generalizing, cleaning, and smoothing.
To give you a quick impression of what some of these algorithms would be useful for, this post introduces a trajectory preprocessing workflow that is quite general-purpose and can be adapted to many different datasets.
We start out with the Geolife sample dataset which you can find in the Trajectools plugin directory’s sample_data subdirectory. This small dataset includes 5908 points forming 5 trajectories, based on the trajectory_id field:
We first split our trajectories by observation gaps to ensure that there are no large gaps in our trajectories. Let’s make at cut at 15 minutes:
This splits the original 5 trajectories into 11 trajectories:
When we zoom, for example, to the two trajectories in the north western corner, we can see that the trajectories are pretty noisy and there’s even a spike / outlier at the western end:
If we label the points with the corresponding speeds, we can see how unrealistic they are: over 300 km/h!
Let’s remove outliers over 50 km/h:
Better but not perfect:
Let’s smooth the trajectories to get rid of more of the jittering.
(You’ll need to pip/mamba install the optional stonesoup library to get access to this algorithm.)
Depending on the noise values we chose, we get more or less smoothing:
Let’s zoom out to see the whole trajectory again:
Feel free to pan around and check how our preprocessing affected the other trajectories, for example:
If you downloaded Trajectools 2.1 and ran into troubles due to the introduced scikit-mobility and gtfs_functions dependencies, please update to Trajectools 2.2.
This new version makes it easier to set up Trajectools since MovingPandas is pip-installable on most systems nowadays and scikit-mobility and gtfs_functions are now truly optional dependencies. If you don’t install them, you simply will not see the extra algorithms they add:
If you encounter any other issues with Trajectools or have questions regarding its usage, please let me know in the Trajectools Discussions on Github.
Get high-precision elevation profiles in QGIS right from Swisstopo’s official profile service, based on swissALTI3D data!
Swiss elevation profiles are available with QGIS 3.38.
Thanks to this integration, you can take advantage of existing QGIS features, such as exporting 2d/3d features or distance/elevation tables, as well as displaying profiles directly in QGIS layouts.
Tip: Swiss elevation profiles will be available as long as the Swiss Locator plugin is installed and active. Should you need to turn Swiss elevation profiles off to create other profiles with your own data, go to the Plugin manager and deactivate the plugin in the meantime.
For developers
We’re paving the way for adding custom elevation profiles to QGIS. For that, we’ve added a QGIS profile source registry so that plugin developers can register their own profile sources (e.g., based on profile web services, just like we did here) and make them available for QGIS end users. The registry is available from QGIS 3.38. It’s your turn!
Loading Swiss vector tiles is now easier than ever. Just go to the locator bar, type the prefix “chb” (add a white space after that) and you’ll get a list of available and already styled Swiss vector tiles layers. Some of them will even load grouped auxiliary imagery for reference.
Vector tiles will be loaded at the bottom of the QGIS layer tree as base maps, so you will see all your data on top of them.
Vector tiles are optimized for local caching and scale-independent rendering. This also makes it a perfect fit for adding it to your QField project.
There are a couple of different vector tile sets available:
leichte-basiskarte
Light base map
Similar to the leichte-basiskarte layer, but using an older version of the data source and adjusted styles.
leichte-basiskarte-imagery (with WMTS sublayer)
Imagery base map (with WMTS sublayer)
This layer is similar to the leichte-basiskarte-imagery layer, but it uses an older version of the data source and adjusted styles.
Thanks to your feedback, we’ve also fixed some issues. Don’t hesitate to reach out to us at GitHub if you’d like to suggest or report something related to the Swiss Locator plugin.
During the pandemic, people noticed how well they could work remotely, how productive meetings via video call could be, and how well webinars worked. At OPENGIS.ch, this wasn’t news because we have always been 100% remote. However, we missed the unplanned, in-person interactions that occur during meetups with a or . That’s why we’re very pleased that last week we could join the Swiss QGIS user day for the second time after the pandemic.
OPENGIS.ch has been invested in QGIS since its inception in 2014, actually even before; our CEO Marco started working with QGIS 0.6 in 2004 and our CTO Matthias with version 1.7 in 2012. Since 2019, we have also been the company with the most core committers. We can definitely say that OPENGIS.ch has been one of the main driving forces behind the large adoption of QGIS in Switzerland and worldwide.
Contributions to the QGIS core measured in commit numbers
Looking at the work done in the QGIS code we’re by far the most prolific company in Switzerland and second worldwide only to North Road Consulting. On top of it, we were the first – and still only one of two- companies to sustain QGIS.org at a Large level since 2021.
This makes us very proud and it is why we’re even happier to see how much that is happening around QGIS in Switzerland aligns with the visions and goals we set out to reach years ago.
The morning started with a presentation by our CTO Matthias “What’s new in QGIS” featuring plenty of work sponsored by the Anwendergruppe CH.
Our CTO Matthias answering QGIS questions
DXF Improvements, the release of SwissLocator 3.0 with swissalti3d and vector tiles integration, and an update on the advances towards solid curve handling in QGIS, a prerequisite for properly handling AV data in Switzerland, were only some of the many noteworthy points he touched.
The highlight of Matthias’ presentation was the better OGC API Features support in QGIS, which was also highlighted in a subsequent talk about Kablo, showing how the next generation of industry solutions (Fachschalen) will be implemented.
Following was a short presentation on the project DMAV, Christoph Lauber introduced a project that aims to implement an industry solution for official cadastral surveying with QGIS.
Adrian Wicki of the Federal Office for the Environment (FOEN) and Isabel presented how OPENGIS.ch and the partners Puzzle and Zeilenwerk help the FOEN with the SAM project with assess the hazards of flood, forest fire, or landslides, and warn authorities and the population. With an agile project organisation, the complex project succeeds in fulfilling requirements by applying user-centred development concepts. QGIS is used for visualizing and analyzing data and helping forecasters gain insights into the current situation.
Andreas Neumann from ETH Zurich and Michael presented the qgis-js project. QGIS-js is an effort to port QGIS core to WebAssembly so that it can be run in a web browser. Although still in the early experimentation phase, this project has great potential to leverage interesting new use cases that weren’t even thinkable before.
Olivier Monod from the City of Yverdon presented Kablo, an electricity management proof of concept of the next generation implementation for industry solutions developed in collaboration with OPENGIS.ch.
By applying a middleware based on OGC API Features and Django, Kablo shows how common limitations of current industry solutions (like permission management and atomic operations) can be overcome and how the future brings desktop and web closer together.
Obviously, it wasn’t just OPENGIS.ch. Sandro Mani from Sourcepole presented the latest and greatest improvements on QWC2, like street view integration and cool QGIS features brought to a beautiful web gis. Andreas Schmid from Kt. Solothurn presented how cool cloud-optimized geotiff (COG) is and what challenges come with it. Interested in the topic? Read more in our report about cloud optimized formats. Mattia Panduri from Canton Ticino explained how they used QGIS to harmonise the cantonal building datasets and Timothée Produit from IG Group SA presented how pic2map helps bring photos to maps.
To round up the morning, Nyall Dawson from North Road Consulting did a live session around the world to show the latest developments around elevation filtering in QGIS.
In the afternoon, workshops followed. Claas Leiner led a QGIS expression one while Matthias and Michael showed how to leverage QGIS processing for building geospatial data processing workflows.
The first QGIS model baker user meeting took place in the third room. The participants discussed this fantastic tool we developed to make INTERLIS work smarter and more productive.
First ModelBaker user meeting
It was a very rich and constructive QGIS user day. We came home with plenty of new ideas and a sense of fulfilment, seeing how great the community we observed and helped grow has become.
A big thanks go to the organisers and everyone involved in making such a great event happen. Only the beer in the sunshine was literally watered by the rain. Nevertheless, there were exciting discussions in the station bistro or in the restaurant coaches on the way home.
Oslandia is the main partner of OPENGIS.ch around QField. We are proud today to forward the announcement of the new QField release 3.3 “Darién”. This release introduces a brand new plugin framework that empowers users to customize and add completely new functionalities to their favourite field application.
The plugin framework comes with other new features and improvements for this release, detailed below.
Main highlights
One of the biggest feature additions of this version is a brand new drawing tool that allows users to sketch out important details over captured photos or annotate drawing templates. This was a highly requested feature, which is brought to all supported platforms (Android, iOS, Windows, macOS, and, of course, Linux) with the financial support of the Swiss QGIS user group.
Also landing in this version is support for copying and pasting vector features into and from the clipboard. This comes in handy in multiple ways, from providing a quick and easy way to transfer attributes from one feature to another through matching field names to pasting the details of a captured feature in the field into a third-party messenger, word editing, or email application. Copying and pasting features can be done through the feature form’s menu as well as long pressed over the map canvas. Moreover, a new feature-to-feature attributes transfer shortcut has also been added to the feature form’s menu. Appreciation to Switzerland, Canton of Lucerne, Environment and Energy for providing the funds for this feature.
The feature form continues to gain more functionalities; in this version, the feature form’s value map editor widget has gained a new toggle button interface that can help fasten data entry. The interface replaces the traditional combo box with a series of toggle buttons, lowering the number of taps required to pick a value. The German Archaeological Institut – KulturGutRetter sponsored this feature.
Other improvements in the feature form include support for value relation item grouping and respect for the vector layer attributes’ « reuse last entered value » setting.
Finally, additional features include support for image decoration overlay, a new interface to hop through cameras (front, back, and external devices) for the ‘non-native’ camera, the possibility to disable the 3-finger map rotation gesture, and much more.
User experience improvements
Long-time users of QField will notice the new version restyling of the information panels such as GNSS positioning, navigation, elevation profile, and sensor data. The information is now presented as an overlay sitting on top of the map canvas, which increases the map canvas’ visibility while also achieving better focus and clarity on the provided details. With this new version, all details, including altitude and distance to destination, respect user-configured project distance unit type.
The dashboard’s legend has also received some attention. You can now toggle the visibility of any layer via a quick tap on a new eye icon sitting in the legend tree itself. Similarly, legend groups can be expanded and collapsed directly for the tree. This also permits you to show or hide layers while digitizing a feature, something which was not possible until now. The development of these improvements was supported by Gispo and sponsored by the National Land Survey of Finland.
Plugin framework
QField 3.3 introduces a brand new plugin framework using Qt’s powerful QML and JavaScript engine. With a few lines of code, plugins can be written to tweak QField’s behaviour and add new capabilities. Two types of plugins are possible: app-wide plugins as well as project-scoped plugins. To ensure maximum ease of deployment, plugin distribution has been made possible through QFieldCloud! Amsa provided the financial contribution that brought this project to life.
Our partner OPENGIS.ch will soon offer a webinar to discover how QField plugins can help your field (and business) workflows by allowing you to be even more efficient in the field.
Total Open Station : https://github.com/totalopenstation
An open-source project initiated by Italian and French archaeologists, it is a tool to convert various formats of survey field books.
Topaze : https://gitlab.com/azimut-fr/qgis/topaze
A topometric calculation tool developed with Jean-Marie Arsac (Azimut). It was a proof of concept that such calculations can be done within a GIS.
These plugins can be used at different stages of a project. They can be used all together or only those needed and integrated into workflows.
2- Improvements on QGIS
Oslandia also focuses on improving the core of QGIS. Last years, our teams have worked on:
— Integration of shape tools: circles, ellipses, rectangles, regular polygons, etc.
— Improvement of snapping tools.
— Enhancement of Z and M coordinate support.
— Improvement of topological tools (relationships between geometries).
Coming soon is the possibility to use geometry and topology validation and correction plugins directly in QGIS processing tools, developed by Jacky Volpès and Loïc Bartoletti.
3- Training
Oslandia is QUALIOPI certified and offers a training program around QGIS and QField:
Topography with QGIS (LSCI, Topaze, QompliGIS, Total Open Station)
QField Training
Deployment of QField Cloud
« In 2023, 89 people were trained by Oslandia, who recommend our training at 90.9%.»
4- And QField ?
Since our partnership with OPENGIS.ch, Oslandia offers QField Cloud server deployment services, training, and QField support.
5- Coming Soon!
Several technical posts are being prepared: how to open CAD files in a GIS? What are the differences between QField and LSCI? You will find them on our website in the coming weeks.
Additionally, we are preparing a white paper on the topic of migrating from CAD to QGIS, which we should release in September.
The PostgreSQL Connection Service File pg_service.conf is nothing new. It has existed for quite some time and maybe you have already used it sometimes too. But not only the new QGIS plugin PG service parser is a reason to write about our love for this file, as well we generally think it’s time to show you how it can be used for really cool things.
What is the Connection Service File?
The Connection Service File allows you to save connection settings for each so-called “service” locally.
So when you have a database called gis on a local PostgreSQL with port 5432 and username/password is docker/docker you can store this as a service called my-local-gis.
This Connection Service File is called pg_service.conf and is by client applications (such as psql or QGIS) generally found directly in the user directory. In Windows it is then found in the user’s application directory postgresql.pg_service.conf. And in Linux it is by default located directly in the user’s directory ~/.pg_service.conf.
But it doesn’t necessarily have to be there. The file can be anywhere on the system (or on a network drive) as long as you set the environment variable PGSERVICEFILE accordingly:
Once you have done this, the client applications will search there first – and find it.
If the above are not set, there is also another environment variable PGSYSCONFDIR which is a folder which is searched for the file pg_service.conf.
Once you have this, the service name can be used in the client application. That means in psql it would look like this:
~$ psql service=my-local-gis
psql (14.11 (Ubuntu 14.11-0ubuntu0.22.04.1), server 14.5 (Debian 14.5-1.pgdg110+1))
SSL connection (protocol: TLSv1.3, cipher: TLS_AES_256_GCM_SHA384, bits: 256, compression: off)
Type "help" for help.
gis=#
And in QGIS like this:
If you then add a layer in QGIS, only the name of the service is written in the project file. Neither the connection parameters nor username/password are saved. In addition to the security aspect, this has various advantages, more on this below.
But you don’t have to pass all of these parameters to a service. If you only pass parts of them (e.g. without the database), then you have to pass them when the connection is called:
$psql "service=my-local-gis dbname=gis"
psql (14.11 (Ubuntu 14.11-0ubuntu0.22.04.1), server 14.5 (Debian 14.5-1.pgdg110+1))
SSL connection (protocol: TLSv1.3, cipher: TLS_AES_256_GCM_SHA384, bits: 256, compression: off)
Type "help" for help.
gis=#
You can also override parameters. If you have a database gis configured in the service, but you want to connect the database web, you can specify the service and explicit the database:
$psql "service=my-local-gis dbname=web"
psql (14.11 (Ubuntu 14.11-0ubuntu0.22.04.1), server 14.5 (Debian 14.5-1.pgdg110+1))
SSL connection (protocol: TLSv1.3, cipher: TLS_AES_256_GCM_SHA384, bits: 256, compression: off)
Type "help" for help.
web=#
Of course the same applies to QGIS.
And regarding the environment variables mentioned, you can also set a standard service.
export PGSERVICE=my-local-gis
Particularly pleasant in daily work with always the same database.
$ psql
psql (14.11 (Ubuntu 14.11-0ubuntu0.22.04.1), server 14.5 (Debian 14.5-1.pgdg110+1))
SSL connection (protocol: TLSv1.3, cipher: TLS_AES_256_GCM_SHA384, bits: 256, compression: off)
Type "help" for help.
gis=#
And why is it particularly cool?
There are several reasons why such a file is useful:
Security: You don’t have to save the connection parameters anywhere in the client files (e.g. QGIS project files). Keep in mind that they are still plain text in the service file.
Decoupling: You can change the connection parameters without having to change the settings in client files (e.g. QGIS project files).
Multi-User: You can save the file on a network drive. As long as the environment variable of the local systems points to this file, all users can access the database with the same parameters.
Diversity: You can use the same project file to access different databases with the same structure if only the name of the service remains the same.
For the last reason, here are three use cases.
Support-Case
Someone reports a problem in QGIS on a specific case with their database. Since the problem cannot be reproduced, they send us a DB dump of a schema and a QGIS project file. The layers in the QGIS project file are linked to a service. Now we can restore the dump on our local database and access it with our own, but same named, service. The problem can be reproduced.
INTERLIS
With INTERLIS the structure of a database schema is precisely specified. If e.g. the canton has built the physical database for it and configured a supernice QGIS project, they can provide the project file to a company without also providing the database structure. The company can build the schema based on the INTERLIS model on its own PostgreSQL database and access it using its own service with the same name.
Test/Prod Switching
You can access a test and a production database with the same QGIS project if you have set the environment variable for the connection service file accordingly per QGIS profile.
You create two connection service files.
The one to the test database /home/dave/connectionfiles/test/pg_service.conf:
In QGIS you create two profiles “Test” and “Prod”:
And you set the environment variable for each profile PGSERVICEFILE which should be used (in the menu Settings > Options… and there under System scroll down to Environment
or
If you now use the service my-local-gis in a QGIS layer, it connects the database prod in the “Prod” profile and the database test in the “Test” profile.
The authentication configuration
Let’s have a look at the authentication. If you have the connection service file on a network drive and make it available to several users, you may not want everyone to access it with the same login. Or you generally don’t want any user information in this file. This can be elegantly combined with the authentication configuration in QGIS.
If you want to make a QGIS project file available to multiple users, you create the layers with a service. This service contains all connection parameters except the login information.
This login information is transferred using QGIS authentication.
You also configure this authentication per QGIS profile we mentioned above. This is done via Menu Settings > Options… and there under Authentication:
(or directly where you create the PostgreSQL connection)
If you add such a layer, the service and the ID of the authentication configuration are saved in the QGIS project file. This is in this case mylogin. Of course this name must be communicated to the other users so that they can also set the ID for their login to mylogin.
Of course, you can use multiple authentication configurations per profile.
QGIS Plugin
And yes, there is now a great plugin to configure these services directly in QGIS. This means you no longer have to deal with text-based INI files. It’s called PG service parser:
It finds the connection service file according to the mentioned environment variables PGSERVICEFILE or PGSYSCONFDIR or at its default location.
As well it’s super easy to create new services by duplicating existing ones.
And for the Devs
And what would a blog post be without some geek food? The back end of this plugin is published on PYPI and can be easily installed with pip install pgserviceparser and then be used in Python.
There are some more functions. Check them out here on GitHub or in the documentation.
Well then
We hope you share our enthusiasm for this beautiful file – at least after reading this blog post. And if not – feel free to tell us why you don’t in the comments
Today marks the 2.1 release of Trajectools for QGIS. This release adds multiple new algorithms and improvements. Since some improvements involve upstream MovingPandas functionality, I recommend to also update MovingPandas while you’re at it.
If you have installed QGIS and MovingPandas via conda / mamba, you can simply:
Afterwards, you can check that the library was correctly installed using:
import movingpandas as mpd mpd.show_versions()
Trajectools 2.1
The new Trajectools algorithms are:
Trajectory overlay — Intersect trajectories with polygon layer
Privacy — Home work attack (requires scikit-mobility)
This algorithm determines how easy it is to identify an individual in a dataset. In a home and work attack the adversary knows the coordinates of the two locations most frequently visited by an individual.
Furthermore, we have fixed issue with previously ignored minimum trajectory length settings.
Scikit-mobility and gtfs_functions are optional dependencies. You do not need to install them, if you do not want to use the corresponding algorithms. In any case, they can be installed using mamba and pip:
or 
. That’s why we’re very pleased that last week we could join the Swiss QGIS user day for the second time after the pandemic.
