In part 3 of my exploration of variables in QGIS 2.12, I’m going to dig into how variables are scoped in QGIS and what layer level variables are available (you can read parts 1 and 2 for a general introduction to variables).

Some background

Before we get to the good stuff, a bit of background in how variables work behind-the-scenes is important. Whenever an expression is evaluated in QGIS the context of the expression is considered. The context is built up from a set of scopes, which are all stacked on top of each other in order from least-specific to most-specific. It’s easier to explain with an example. Let’s take an expression used to set the source of a picture in a map composer. When this expression is evaluated, the context will consist of:

1. The global scope, consisting of variables set in the QGIS options dialog, and other installation-wide properties
2. The project scope, which includes variables set in the Project Properties dialog and the auto-generated project variables like @project_path, @project_title (you can read more about this in part 2)
3. A composer scope, with any variables set for the current composer, plus variables for @layout_pagewidth, @layout_pageheight, @layout_numpages, etc.
4. A composer item scope for the picture, with item-specific variables including @item_id

The more specific scopes will override any existing clashing variables from less specific scopes. So a global @my_var variable will be overridden by an @my_var variable set for the composer:

Another example. Let’s consider now an expression set for a data-defined label size. When this expression is evaluated the context will depend on where the map is being rendered. If it’s in the main map canvas then the context will be:

1. The global scope
2. The project scope
3. A map settings scope, with variables relating to how the map is being rendered. Eg @map_rotation, @map_scale, etc
4. A layer scope. More on this later, but the layer scope includes layer-level variables plus preset variables for @layer_name and @layer_id

If instead the map is being rendered inside a map item in a map composer, the context will be:

1. The global scope
2. The project scope
3. The composer scope
4. An atlas scope, if atlas is enabled. This contains variables like @atlas_pagename, @atlas_feature, @atlas_totalfeatures.
5. A composer item scope for the map item
6. A map settings scope (with scale and rotation determined by the map item’s settings)
7. The layer scope

Using layer level variables

Ok, enough with the details. The reason I’ve explained all this is to help explain when layer level variables come into play. Basically, they’ll be available whenever an expression is evaluated inside of a particular layer. This includes data defined symbology and labeling, field calculator, and diagrams. You can’t use a layer-level variable inside a composer label, because there’s no layer scope used when evaluating this. Make sense? Great! To set a layer level variable, you use the Variables section in the Layer Properties dialog:

Any layer level variables you set will be saved inside your current project, i.e. layer variables are per-layer and per-project. You can also see in the above screenshot that as well as the layer level variables QGIS also lists the existing variables from the Project and Global scopes. This helps show exactly what variables are accessible by the layer and whether they’ve been overridden by any scopes. You can also see that there’s two automatic variables, @layer_id and @layer_name, which contain the unique layer ID and user-set layer name too.

Potential use cases for layer-level variables

In the screenshot above I’ve set two variables, @class1_threshold and @class2_threshold. I’m going to use these to sync up some manual class breaks between rule based symbology and rule based labeling. Here’s how I’ve set up the rule-based symbols for the layer:

In a similar way, I’ve also created matching rule-based labeling (another new feature in QGIS 2.12):

Here’s what my map looks like now, with label and symbol colors matched:

If I’d hard-coded the manual class breaks, it would be a pain to keep the labeling and symbology in sync. I’d have to make sure that the breaks are updated everywhere I’ve used them in both the symbology and labeling settings. Aside from being boring, tedious work, this would also prevent immediate before/after comparisons. Using variables instead means that I can update the break value in a single place (the variables panel) and have all my labeling and symbols immediately reflect this change when I hit apply!

Another recent use case I had was teaming layer-level variables along with Time Manager. I wanted my points to falloff in both transparency and size with age, and this involved data defined symbol settings scattered all throughout my layer symbology. By storing the decay fall-off rate in a variable, I could again tweak this falloff by changing the value in a single place and immediately see the result. It also helps with readability of the data defined expressions. Instead of trying to decipher a random, hard-coded value, it’s instead immediately obvious that this value relates to a decay fall-off rate. Much nicer!

I’m sure there’s going to be hundreds of novel uses of layer-level variables which I never planned for when adding this feature. I’d love to hear about them though – leave a comment if you’d like to share your ideas!

One last thing – the new “layer_property” function

This isn’t strictly related to variables, but another new feature which was introduced in QGIS 2.12 was a new “layer_property” expression function. This function allows you to retrieve any one of a bunch of properties relating to a specific map layer, including the layer CRS, metadata, source path, etc.

This function can be used anywhere in QGIS. For instance, it allows you to insert dynamic metadata about layers into a print composer layout. In the screenshot below I’ve used expressions like layer_property(‘patron’,’crs’) and layer_property(‘patron’,’source’) to insert the CRS and source path of the “patron” layer into the label. If either the CRS or the file path ever changes, this label will be automatically updated to reflect the new values.

So there you go – layer level variables and the layer_property function – here in QGIS 2.12 and making your workflow in QGIS easier. In the final part of this series, we’ll explore the magical @value variable. Trust me, I’ve saved the best for last!

If you’re not like me and don’t keep a constant eye over at QGIS development change log (be careful – it’s addictive!), then you’re probably not aware of a bunch of labelling improvements which recently landed in QGIS master version. I’ve been working recently on a large project which involves a lot (>300) of atlas map outputs, and due to the size of this project it’s not feasible to manually tweak placements of labels. So, I’ve been totally at the mercy of QGIS’ labelling engine for automatic label placements. Generally it’s quite good but there were a few things missing which would help this project. Fortunately, due to the open-source nature of QGIS, I’ve been able to dig in and enhance the label engine to handle these requirements (insert rhetoric about beauty of open source here!). Let’s take a look at them one-by-one:

Data defined quadrant in “Around Point” placement mode

First up, it’s now possible to specify a data defined quadrant when a point label is set to the Around Point placement mode. In the past, you had a choice of either Around Point mode, in which QGIS automatically places labels around point features in order to maximise the number of labels shown, or the Offset from Point mode, in which all labels are placed at a specified position relative to the points (eg top-left). In Offset from Point mode you could use data defined properties to force labels for a feature to be placed at a specific relative position by binding the quadrant to a field in your data. This allowed you to manually tweak the placement for individual labels, but at the cost of every other label being forced to the same relative position. Now, you’ve also got the option to data define the relative position when in Around Point mode, so that the rest of the labels will fall back to being automatically placed. Here’s a quick example – I’ll start with a layer with labels in Around Point mode:

You can see that some labels are sitting to the top right of the points, others to the bottom right, and some in the top middle, in order to fit all the labels for these points. With this new option, I can setup a data defined quadrant for the labels, and then force the ‘Tottenham’ label (top left of the map) to display below and to the left of the point:

Here’s what the result looks like:

The majority of the labels are still auto-placed, but Tottenham is now force to the lower left corner.

Data defined label priority

Another often-requested feature which landed recently is the ability to set the priority for individual labels. QGIS has long had the ability to set the priority for an entire labelling layer, but you couldn’t control the priority of features within a layer. That would lead to situations like that shown below, where the most important central station (the green point) hasn’t been labelled:

By setting a data defined priority for labels, I can set the priority either via values manually entered in a field or by taking advantage of an existing “number of passengers” field present in my data. End result is that this central station is now prioritised over any others:

Obstacle only layers

The third new labelling feature is the option for “Obstacle only” layers. What this option does is allow a non-labelled layer to act as an obstacle for the labels in other layers, so they will be discouraged from drawing labels over the features in the obstacle layer. Again, it’s best demonstrated with an example. Here’s my stations layer with labels placed automatically – you can see that some labels are placed right over the features in the rail lines layer:

Now, let’s set the rail lines layer to act as an obstacle for other labels:

The result is that labels will be placed so that they don’t cover the rail lines anymore! (Unless there’s no other choice). Much nicer.

Control over how polygons act as obstacles for labels

This change is something I’m really pleased about. It’s only applicable for certain situations, but when it works the improvements are dramatic.

Let’s start with my labelled stations map, this time with an administrative boundary layer in the background:

Notice anything wrong with this map? If you’re like me, you won’t be able to look past those labels which cross over the admin borders. Yuck. What’s happening here is that although my administrative regions layer is set to discourage labels being placed over features, there’s actually nowhere that labels can possibly be placed which will avoid this. The admin layer covers the entire map, so regardless of where the labels are placed they will always cover an administrative polygon feature. This is where the new option to control how polygon layers act as obstacles comes to the rescue:

Now, I can set the administrative layer to only avoid placing labels over feature’s boundaries! I don’t care that they’ll still be placed inside the features (since we have no choice!), but I don’t want them sitting on top of these boundaries. The result is a big improvement:

Now, QGIS has avoided placing labels over the boundaries between regions. Better auto-placement of labels like this means much less time required manually tweaking their positioning, and that’s always a good thing!

Draw only labels which fit inside a polygon

The last change is fairly self explanatory, so no nice screenshots here. QGIS now has the ability to prevent drawing labels which are too large to fit inside their corresponding polygon features. Again, in certain circumstances this can make a huge cartographic improvement to your map.

So there you go. Lots of new labelling goodies to look forward to when QGIS 2.12 rolls around.

It’s been quite some time since I last had a chance to blog and a lot has happened since then. Not least of which is that QGIS 2.12 has now been released with a ton of new features that I’ve neglected to write about! To try and get things moving along here again I’m planning on writing a short series exploring how variables work in QGIS 2.12 and the exciting possibilities they unlock. First, let’s look into how variables can be used with QGIS map composer…

So, let’s get started! A new concept introduced in QGIS 2.12 is the ability to set custom variables for use in QGIS’ expression engine. The easiest way to do this is through the “Project Properties” dialog, under the “Variables” section:

You’ll see in the screenshot above that a blank project includes a number of read-only preset variables, such as @project_path and @project_title. (All variables in QGIS are prefixed with an @ character to differentiate them from fields or functions). You can add your own variables to this list by clicking the + button, as shown below:

Here I’ve added some new variables, @project_version and @author. Now, any of these variables can be used anywhere that you can use expressions in QGIS, including the field calculator, data defined symbology, labelling, map composer text, etc. So, you could make a map composer template with a label that includes the @author, @project_version and @project_path variables:

Sure, you *could* also manually enter all these details directly into the label for the same result. But what happens when you have multiple composers in your project, and need to update the version number in all of them? Or you move your project to a new folder and need to make sure the path is updated accordingly? Manually updating multiple composers is a pain – make QGIS do the work for you and instead use variables! This would especially be helpful if you’re saving map composer templates for use across multiple projects or users. Using variables will ensure that the template is automatically updated with the right details for the current project.

Another neat thing about QGIS variables is that they can be inherited and overridden, just like CSS rules. Opening the options dialog will also show a Variables group for setting “Global” variables. These variables are always available for your QGIS installation, regardless of what project you’re working on at the time. If your workplace tends to reorganise a lot and constantly shuffle your department around, you could add a global variable for @work_department, so that changing the global variable value in one place will automatically filter through to any existing and future projects you have.

And like I mentioned earlier, these variables are inherited through various “contexts” within QGIS. If I reopen the Project Properties dialog, you’ll see that a project has access to all the global variables plus the variables set within that specific project. In addition, by adding a variable with the same name to the Project variables the value of the Global variable will be overridden:

There’s also a variable editor within each individual composer’s properties tab, so variables can also be set and overridden on a composer-by-composer basis within a project. It’s a really flexible and powerful approach which both simplifies workflows and also opens up lots of new possibilities.

Stay tuned for more on this topic – this topic has only just scratched the surface of how expression variables have changed QGIS! (You can also read part 2 and part 3)

I’ve been heavily involved in the open source QGIS mapping project for a number of years now. During this time I’ve kept a close watch on the various mailing lists, issue trackers, stackexchange, tweets and other various means users have to provide feedback to the project. Recently, I’ve started to come to the conclusion that there’s a lot of fundamental confusion about how the project works and how users can get changes made to the project. Read on for these insights, but keep in mind that these are just my thoughts and not reflective of the whole community’s views!..

Firstly – QGIS is a community driven project. Unlike some open source projects (and unlike the proprietary GIS offerings) there is no corporate backer or singular organisation directing the project. This means two things:

1. The bad news: No-one will do your work for you. QGIS has been created through a mix of user-led contributions (ie, users who have a need to change something and dive in and do it themselves) and through commercially supported contributions (either organisations who offer commercial QGIS support pushing fixes because their customers are directly affected or because they’ve been contracted by someone to implement a particular change). There HAS been a number of volunteer contributions from developers who are just donating their time (for various reasons), but these contributions are very much the minority.
2. The good news: YOU have the power to shape the project! (And whenever I say “you” – I’m referring directly to the person reading this, or the company you work for. Just pretend it’s in 24 point bold red blinking text.) Because QGIS is community driven (and not subject to the whims of any one particular enterprise) every user has the ability to implement changes and fixes in the program.

So how exactly can users get changes implemented in QGIS? Well, let’s take a look at all the possible different ways that changes get made and how effective each one is:

1. YOU can make the changes yourself. This implies that you have the c++/Python skills required to make the changes, are able to find your way around the source code, and push through the initial hurdles of setting up a build environment and navigating git. This can be a significant time investment, but the ultimate result is that you can make whatever changes you want, and so long as your pull request is accepted you’ll get your changes directly into QGIS. You’ll find the QGIS team is very open to new contributors and will readily lend a hand if you need assistance navigating the source or for advise on the best way to make these changes. Just ask!
2. YOU (or your employer) can pay (or “sponsor”) someone to make the changes on your behalf. Reinvesting some of those savings you’re making through using an open source program back into the program itself is a great idea, and everyone benefits. There’s numerous organisations who specialise in QGIS development (eg… my own consultancy, North Road). You can liaise with these organisations to get them to make the changes on your behalf. This is probably the most effective way of getting changes implemented. These organisations all have a history with QGIS development and this experience generally translates to much faster development then if you code it yourself. It’s also somewhat of a shortcut – if you hire a core QGIS developer to make your changes, then you can be confident that they are familiar with the coding style, policies, and long-term goals of the project and accordingly can get the changes accepted rapidly. The obvious down side of paying for changes is that, well, it costs money. Understandably, not everyone has the resources available to do this.
3. Following on from option 2 – if you can’t directly sponsor changes yourself, you could help indirectly raise funds to pay for the changes. This is a great way to get changes implemented, because everyone has the power to do this. You could seek out similar organisations/users who have the same need and pool your resources, get involved with the local QGIS user group and raise funds together, organise a crowd-funding campaign, etc.
4. Ask a developer to make the changes for you. This is not terribly effective – you’re basically asking someone to work for free, and take time away from their family/job/hobbies/social life to do work for you. That said, it does sometimes happen, and here’s a few reasons I can think of why:
   • You’ve build up enough “karma” within the project through other contributions. If someone has been heavily involved in the non-development side of the project (eg translations, documentation, helping users out on mailing lists/stackexchange, organising hackfests or user groups, etc) then developers are much more likely to want to help them out in turn.
   • You’ve got a fantastic idea which has just never occurred to anyone before. By bringing it to the attention of a developer you might trigger the “wow, I could really benefit from that too!” impulse which is hard-wired into some of us!
   • It’s a particularly interesting or challenging problem, and sometimes developers just like to extend themselves.
5. (For bugs only) File a bug report, and hope it gets picked up in one of the pre-release bug fixing sprints. This is basically the same as option 2 – expect that in this case someone else (the QGIS steering committee) is paying for the development time. There’s no way of guaranteeing that your bug will get fixed during this time though, so it’s not a particularly reliable approach if the fix is critical for you.

Finally, there’s two more very ineffective approaches:

6. File a bug report/feature request, and wait. This isn’t very effective, because what you’re doing is basically the same as 1-4 above, but just waiting for someone else to either do the work or sponsor the changes. This might happen in a week, or might take 10 years.
7. Complain about something and hope for the best. This is… not very effective. No-one is particularly motivated to help out someone who is being a jerk.

That’s it. Those are the ONLY ways changes get made in QGIS. There’s no other magical short-cuts you can take. Some of these approaches are much more effective than others, and some require skills or resources which may not be available. If you want to see something change in QGIS, you need to take a look at these options and decide for yourself which best meets your needs. But please, just don’t choose option 7!

Update: a follow up to this article was published

Last week I had the pleasure to attend the combined FOSSGIS, AGIT and GI_Forum conferences in Salzburg. It was a great joint event bringing together GIS user and developers from industry and academia, working with both open source and commercial GIS.

I was particularly impressed by the great FOSSGIS video team. Their tireless work makes it possible to re-watch all FOSSGIS talks (in German).

I also had the pleasure to give a few presentations. Most of all, it was an honor to give the AGIT opening keynote, which I dedicated to Open Source, Open Data & Open Science.

In addition, I also gave one talk related to an ongoing research project on pedestrian routing. It was really interesting to see that other people – in particular from the OSM community – also talked about this problem during FOSSGIS:

(For more details, please see the full paper (OA).)

To wrap up this great week, Astrid Emde, Andreas Hocevar, and myself took the chance to celebrate the 10th anniversary of OSGeo during AGIT2016 OSGeo Day.

Full house at #AGIT2016 os geoday with @astroidex @ahoce and myself, celebrating 10 years #osgeo https://t.co/7n81G9oX81

—
Anita Graser (@underdarkGIS) July 08, 2016

And last but not least, I presented an update from the QGIS project with news about the 3.0 plans and a list of (highly subjective) top new features:

Towards the new stable release series

As of 24 May 2016, a new stable release branch was created for the upcoming GRASS GIS 7.2 release. This new branch includes all the many improvements which have been implemented in the former development version 7.1.svn.

What is a branch? In simple words, it is a kind of directory in the software development server (SVN in our case) in which no more development but only bugfixing happens. From a release branch, new stable releases are created and published.

The actual branches in the GRASS GIS project are:

• very old stable: releasebranch_6_4 (used for bugfixing and to publish stable GRASS GIS 6.4.x releases) – very low release frequency (started in revision r34936)
• old stable releasebranch_7_0 (used for bugfixing and to publish stable GRASS GIS 7.0.x releases) – perhaps one last release upcoming (branch started in revision r59487 but development already started in Apr 2008 in r31142)
• new stable releasebranch_7_2 (used for bugfixing and to publish stable GRASS GIS 7.2.x releases) – upcoming series of stable releases (branch started in revision r68500)
• trunk (used for development, with pseudo-name 7.3.svn) – under heavy development

Note to SVN users

The trunk branch with pseudo-name 7.1.svn has become 7.3.svn due to the creation of the new 7.2.svn release branch. You can simply continue to update from SVN, the version will be automatically updated.

If you used to work with the 7.0.svn release branch, consider to download the new 7.2.svn release branch, either from the weekly source code snapshot (here) or from the SVN server directly (here).

About GRASS GIS

The Geographic Resources Analysis Support System (http://grass.osgeo.org/), commonly referred to as GRASS GIS, is an Open Source Geographic Information System providing powerful raster, vector and geospatial processing capabilities in a single integrated software suite. GRASS GIS includes tools for spatial modeling, visualization of raster and vector data, management and analysis of geospatial data, and the processing of satellite and aerial imagery. It also provides the capability to produce sophisticated presentation graphics and hardcopy maps. GRASS GIS has been translated into about twenty languages and supports a huge array of data formats. It can be used either as a stand-alone application or as backend for other software packages such as QGIS and R geostatistics. 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).

The GRASS Development Team, May 2016

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There is a FOSS4G UK conference, unconference, workshop, hackathon, code sprint and party happening in Southampton in June this year.  If you are free from the 14th to 16th then this is a fantastic opportunity to come and find out more about free and open-source software for Geo.  Have a look at the OSGeo site (http://uk.osgeo.org/foss4guk2016/) for more information.  If you want to submit a talk and/or workshop then you can do so through the site.  Early bird tickets will be going on sale tomorrow (13 April) and will be available through the site from Eventbrite.

So some good news for QGIS users who also need/want to use MapInfo.  QGIS via GDAL 2.0 can support MapInfo TAB file editing. In all older versions of GDAL there was only support for read and/or write but not both.

MapInfo TAB editing has been supported in GDAL 2 but up until this point QGIS has only be built against GDAL 1.xx.  GDAL 2.x is now the default GDAL release in OSGeo4w.

From Jurgen:

2.0.2 is now the default GDAL in OSGeo4W and the nightlies (qgis-ltr-dev,
qgis-rel-dev and qgis-dev) already picked it up.

With the next release the regular packages (2.14 and 2.8) will also be updated
to use it

Even if you don’t want to make the switch to full QGIS you can now use both bits of software and edit in both.

QGIS will still only support a single geometry type per layer so if you open a mixed tab file you will get the geometry type selector.  You can load the layer 3 times if you need the 3 different geometry types.

Press release

From March 2016 onwards, Dr. Markus Neteler, a prominent head of the Open Source GIS scene, will join the management board of mundialis GmbH & Co. KG in Bonn, Germany. Founded in 2015, mundialis combines remote sensing and satellite data analysis in the field of Big Data with Open Source WebGIS solutions.

Since 2008, Dr. Neteler was the head of the GIS and remote sensing unit at the Edmund Mach Foundation in Trento (Italy) and worked in this capacity on numerous projects related to biodiversity, environmental and agricultural research. He is also a founding member of the Open Source Geospatial Foundation (OSGeo), a nonprofit organization with headquarters in Delaware (USA), that promotes the development and use of free and open source geographic information systems (GIS). Since 1998 he coordinated the development of the well known GRASS GIS software project, a powerful Open Source GIS that supports processing of time series of several thousand raster, 3D raster or vector maps in a short time.

Markus will keep his role as “Mr. GRASS” at mundialis, especially because the company also sees itself as a research and development enterprise that puts its focus on the open source interfaces between geoinformation and remote sensing. Although a new company, mundialis offers more than 50 years of experience in GIS, due to the background of its management. Besides Neteler, there are Till Adams and Hinrich Paulsen, both at the same time the founders and CEOs of terrestris in Bonn, a company that develops Open Source GIS solutions since 2002. These many years of experience in the construction of WebGIS and Geoportal architectures using free software as well as in the application of common OGC standards – are now combined with mundialis’ expertise in the processing of big data with spatial reference and remote sensing data.

Contact: http://www.mundialis.de/

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In part 3 of my exploration of variables in QGIS 2.12, I’m going to dig into how variables are scoped in QGIS and what layer level variables are available (you can read parts 1 and 2 for a general introduction to variables).

Some background

Before we get to the good stuff, a bit of background in how variables work behind-the-scenes is important. Whenever an expression is evaluated in QGIS the context of the expression is considered. The context is built up from a set of scopes, which are all stacked on top of each other in order from least-specific to most-specific. It’s easier to explain with an example. Let’s take an expression used to set the source of a picture in a map composer. When this expression is evaluated, the context will consist of:

1. The global scope, consisting of variables set in the QGIS options dialog, and other installation-wide properties
2. The project scope, which includes variables set in the Project Properties dialog and the auto-generated project variables like @project_path, @project_title (you can read more about this in part 2)
3. A composer scope, with any variables set for the current composer, plus variables for @layout_pagewidth, @layout_pageheight, @layout_numpages, etc.
4. A composer item scope for the picture, with item-specific variables including @item_id

The more specific scopes will override any existing clashing variables from less specific scopes. So a global @my_var variable will be overridden by an @my_var variable set for the composer:

Another example. Let’s consider now an expression set for a data-defined label size. When this expression is evaluated the context will depend on where the map is being rendered. If it’s in the main map canvas then the context will be:

1. The global scope
2. The project scope
3. A map settings scope, with variables relating to how the map is being rendered. Eg @map_rotation, @map_scale, etc
4. A layer scope. More on this later, but the layer scope includes layer-level variables plus preset variables for @layer_name and @layer_id

If instead the map is being rendered inside a map item in a map composer, the context will be:

1. The global scope
2. The project scope
3. The composer scope
4. An atlas scope, if atlas is enabled. This contains variables like @atlas_pagename, @atlas_feature, @atlas_totalfeatures.
5. A composer item scope for the map item
6. A map settings scope (with scale and rotation determined by the map item’s settings)
7. The layer scope

Using layer level variables

Ok, enough with the details. The reason I’ve explained all this is to help explain when layer level variables come into play. Basically, they’ll be available whenever an expression is evaluated inside of a particular layer. This includes data defined symbology and labeling, field calculator, and diagrams. You can’t use a layer-level variable inside a composer label, because there’s no layer scope used when evaluating this. Make sense? Great! To set a layer level variable, you use the Variables section in the Layer Properties dialog:

Setting a layer variable

Any layer level variables you set will be saved inside your current project, i.e. layer variables are per-layer and per-project. You can also see in the above screenshot that as well as the layer level variables QGIS also lists the existing variables from the Project and Global scopes. This helps show exactly what variables are accessible by the layer and whether they’ve been overridden by any scopes. You can also see that there’s two automatic variables, @layer_id and @layer_name, which contain the unique layer ID and user-set layer name too.

Potential use cases for layer-level variables

In the screenshot above I’ve set two variables, @class1_threshold and @class2_threshold. I’m going to use these to sync up some manual class breaks between rule based symbology and rule based labeling. Here’s how I’ve set up the rule-based symbols for the layer:

Rule based symbology using layer level variables

In a similar way, I’ve also created matching rule-based labeling (another new feature in QGIS 2.12):

Matching rule-based labels

Here’s what my map looks like now, with label and symbol colors matched:

*Map for illustrative purposes only… not for cartographic/visual design excellence!

If I’d hard-coded the manual class breaks, it would be a pain to keep the labeling and symbology in sync. I’d have to make sure that the breaks are updated everywhere I’ve used them in both the symbology and labeling settings. Aside from being boring, tedious work, this would also prevent immediate before/after comparisons. Using variables instead means that I can update the break value in a single place (the variables panel) and have all my labeling and symbols immediately reflect this change when I hit apply!

Another recent use case I had was teaming layer-level variables along with Time Manager. I wanted my points to falloff in both transparency and size with age, and this involved data defined symbol settings scattered all throughout my layer symbology. By storing the decay fall-off rate in a variable, I could again tweak this falloff by changing the value in a single place and immediately see the result. It also helps with readability of the data defined expressions. Instead of trying to decipher a random, hard-coded value, it’s instead immediately obvious that this value relates to a decay fall-off rate. Much nicer!

I’m sure there’s going to be hundreds of novel uses of layer-level variables which I never planned for when adding this feature. I’d love to hear about them though – leave a comment if you’d like to share your ideas!

One last thing – the new “layer_property” function

This isn’t strictly related to variables, but another new feature which was introduced in QGIS 2.12 was a new “layer_property” expression function. This function allows you to retrieve any one of a bunch of properties relating to a specific map layer, including the layer CRS, metadata, source path, etc.

This function can be used anywhere in QGIS. For instance, it allows you to insert dynamic metadata about layers into a print composer layout. In the screenshot below I’ve used expressions like layer_property(‘patron’,’crs’) and layer_property(‘patron’,’source’) to insert the CRS and source path of the “patron” layer into the label. If either the CRS or the file path ever changes, this label will be automatically updated to reflect the new values.

Inserting dynamic layer properties into a composer label

So there you go – layer level variables and the layer_property function – here in QGIS 2.12 and making your workflow in QGIS easier. In the final part of this series, we’ll explore the magical @value variable. Trust me, I’ve saved the best for last!

Following on from part 1 in which I introduced how variables can be used in map composers, I’d like to now explore how using variables can make it easier to manage your QGIS projects. As a quick refresher, variables are a new feature in QGIS 2.12 which allow you to create preset values for use anywhere you can use an expression in QGIS.

Let’s imagine a typical map project. You load up QGIS, throw a bunch of layers on your map, and then get stuck into styling and labelling them ‘just right’. Over time the project gets more and more complex, with a stack of layers all styled using different rendering and labelling rules. You keep tweaking settings until you’re almost happy with the result, but eventually realise that you made the wrong choice of font for the labelling and now need to go through all your layers and labelling rules and update each in turn to the new typeface. Ouch.

Variables to the rescue! As you may recall from part 1, you can reuse variables anywhere in QGIS where you can enter an expression. This includes using them for data defined overrides in symbology and labelling. So, lets imagine that way back at the beginning of our project we created a project level variable called @main_label_font:

Creating a variable for label font

Now, we can re-use that variable in a data defined override for the label font setting. In fact, QGIS makes this even easier for you by showing a “variables” sub-menu allowing easy access to all the currently defined variables accessible to the layer:

Binding the label font to the @main_label_font variable

When we hit Apply all our labels will be updated to use the font face defined by the @main_label_font variable, so in this case ‘Courier New’:

In a similar way we can bind all the other layer’s label fonts to the same variable, so @main_label_font will be reused by all the layers in the project. Then, when we later realise that Courier New was a horrible choice for labelling the map, it’s just a matter of opening up the Project Properties dialog and updating the value of the @main_label_font variable:

And now when we hit Apply the font for all our labelled layers will be updated all at once:

It’s not only a huge time saver, it also makes changes like this easier because you can try out different font faces by updating the variable and hitting apply and seeing the effect that the changes have all at once. Updating multiple layers manually tends to have the consequence that you forget what the map looked like before you started making the change, making direct comparisons harder.

Of course, you could have multiple variables for other fonts used by your project too, eg @secondary_label_font and @highlighted_feature_font. Plus, this approach isn’t limited to just setting the label font. You could utilise project level variables for consolidating font sizes, symbol line thickness, marker rotation, in fact, ANYTHING that has one of those handy little data defined override buttons next to it:

See all those nice little yellow buttons? All those controls can be bound to variables…

One last thing before I wrap up part 2 of this series. The same underlying changes which introduced variables to QGIS also allows us to begin introducing a whole stack of new, useful functions to the expression engine. One of these which also helps with project management is the new project_color function. Just like how we can use project level variables throughout a project, project_color lets you reuse a color throughout your project. First, you need to create a named colour in the Default Styles group under the Project Properties dialog:

Define a colour in the project’s colour scheme…

Then, you can set a data defined override for a symbol or label colour to the expression “project_color(‘red alert!’)“:

When you go back and change the corresponding colour in the Project Properties dialog, every symbol bound to this colour will also be updated!

So, there you have it. With a little bit of forward planning and by taking advantage of the power of expression variables in QGIS 2.12 you can help make your mapping projects much easier to manage and update!

That’s all for now, but we’re still only just getting started with variables. Part 3, coming soon!.. (Update: Part 3 is available now)

It’s been quite some time since I last had a chance to blog and a lot has happened since then. Not least of which is that QGIS 2.12 has now been released with a ton of new features that I’ve neglected to write about! To try and get things moving along here again I’m planning on writing a short series exploring how variables work in QGIS 2.12 and the exciting possibilities they unlock. First, let’s look into how variables can be used with QGIS map composer…

So, let’s get started! A new concept introduced in QGIS 2.12 is the ability to set custom variables for use in QGIS’ expression engine. The easiest way to do this is through the “Project Properties” dialog, under the “Variables” section:

Default project variables

You’ll see in the screenshot above that a blank project includes a number of read-only preset variables, such as @project_path and @project_title. (All variables in QGIS are prefixed with an @ character to differentiate them from fields or functions). You can add your own variables to this list by clicking the + button, as shown below:

Adding new variables to a project

Here I’ve added some new variables, @project_version and @author. Now, any of these variables can be used anywhere that you can use expressions in QGIS, including the field calculator, data defined symbology, labelling, map composer text, etc. So, you could make a map composer template with a label that includes the @author, @project_version and @project_path variables:

Variables in a composer label

Sure, you *could* also manually enter all these details directly into the label for the same result. But what happens when you have multiple composers in your project, and need to update the version number in all of them? Or you move your project to a new folder and need to make sure the path is updated accordingly? Manually updating multiple composers is a pain – make QGIS do the work for you and instead use variables! This would especially be helpful if you’re saving map composer templates for use across multiple projects or users. Using variables will ensure that the template is automatically updated with the right details for the current project.

Another neat thing about QGIS variables is that they can be inherited and overridden, just like CSS rules. Opening the options dialog will also show a Variables group for setting “Global” variables. These variables are always available for your QGIS installation, regardless of what project you’re working on at the time. If your workplace tends to reorganise a lot and constantly shuffle your department around, you could add a global variable for @work_department, so that changing the global variable value in one place will automatically filter through to any existing and future projects you have.

Global variables

And like I mentioned earlier, these variables are inherited through various “contexts” within QGIS. If I reopen the Project Properties dialog, you’ll see that a project has access to all the global variables plus the variables set within that specific project. In addition, by adding a variable with the same name to the Project variables the value of the Global variable will be overridden:

Overridden variables

There’s also a variable editor within each individual composer’s properties tab, so variables can also be set and overridden on a composer-by-composer basis within a project. It’s a really flexible and powerful approach which both simplifies workflows and also opens up lots of new possibilities.

Stay tuned for more on this topic – this topic has only just scratched the surface of how expression variables have changed QGIS! (You can also read part 2 and part 3)

What’s new in a nutshell

The new GRASS GIS 7.0.2 release provides 190 stability fixes and manual improvements.

About GRASS GIS 7: Its graphical user interface supports the user to make complex GIS operations as simple as possible. The updated Python interface to the C library permits users to create new GRASS GIS-Python modules in a simple way while yet obtaining powerful and fast modules. Furthermore, the libraries were significantly improved for speed and efficiency, along with support for huge files. A lot of effort has been invested to standardize parameter and flag names. Finally, GRASS GIS 7 comes with a series of new modules to analyse raster and vector data, along with a full temporal framework. For a detailed overview, see the list of new features. As a stable release series, 7.0.x enjoys long-term support.

Source code download:

• http://grass.osgeo.org/grass70/source/
• http://grass.osgeo.org/grass70/source/grass-7.0.2.tar.gz
• To get the GRASS GIS 7.0.2 source code directly from SVN, see here.

Binaries download:

• winGRASS 7.0.2 standalone installer
• winGRASS 7.0.2 in OSGeo4W installer
• openSUSE
• … further binary packages for other Linux distributions and Mac OSX will follow shortly.

More details:

See also our detailed announcement:

About GRASS GIS

The Geographic Resources Analysis Support System (http://grass.osgeo.org/), commonly referred to as GRASS GIS, is an Open Source Geographic Information System providing powerful raster, vector and geospatial processing capabilities in a single integrated software suite. GRASS GIS includes tools for spatial modeling, visualization of raster and vector data, management and analysis of geospatial data, and the processing of satellite and aerial imagery. It also provides the capability to produce sophisticated presentation graphics and hardcopy maps. GRASS GIS has been translated into about twenty languages and supports a huge array of data formats. It can be used either as a stand-alone application or as backend for other software packages such as QGIS and R geostatistics. 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).

The GRASS Development Team, November 2015

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If you’re not like me and don’t keep a constant eye over at QGIS development change log (be careful – it’s addictive!), then you’re probably not aware of a bunch of labelling improvements which recently landed in QGIS master version. I’ve been working recently on a large project which involves a lot (>300) of atlas map outputs, and due to the size of this project it’s not feasible to manually tweak placements of labels. So, I’ve been totally at the mercy of QGIS’ labelling engine for automatic label placements. Generally it’s quite good but there were a few things missing which would help this project. Fortunately, due to the open-source nature of QGIS, I’ve been able to dig in and enhance the label engine to handle these requirements (insert rhetoric about beauty of open source here!). Let’s take a look at them one-by-one:

Data defined quadrant in “Around Point” placement mode

First up, it’s now possible to specify a data defined quadrant when a point label is set to the Around Point placement mode. In the past, you had a choice of either Around Point mode, in which QGIS automatically places labels around point features in order to maximise the number of labels shown, or the Offset from Point mode, in which all labels are placed at a specified position relative to the points (eg top-left). In Offset from Point mode you could use data defined properties to force labels for a feature to be placed at a specific relative position by binding the quadrant to a field in your data. This allowed you to manually tweak the placement for individual labels, but at the cost of every other label being forced to the same relative position. Now, you’ve also got the option to data define the relative position when in Around Point mode, so that the rest of the labels will fall back to being automatically placed. Here’s a quick example – I’ll start with a layer with labels in Around Point mode:

Around Point placement mode

You can see that some labels are sitting to the top right of the points, others to the bottom right, and some in the top middle, in order to fit all the labels for these points. With this new option, I can setup a data defined quadrant for the labels, and then force the ‘Tottenham’ label (top left of the map) to display below and to the left of the point:

Setting a data-defined quadrant

Here’s what the result looks like:

Manually setting the quadrant for the Tottenham label

The majority of the labels are still auto-placed, but Tottenham is now force to the lower left corner.

Data defined label priority

Another often-requested feature which landed recently is the ability to set the priority for individual labels. QGIS has long had the ability to set the priority for an entire labelling layer, but you couldn’t control the priority of features within a layer. That would lead to situations like that shown below, where the most important central station (the green point) hasn’t been labelled:

What… no label for the largest station in Melbourne?

By setting a data defined priority for labels, I can set the priority either via values manually entered in a field or by taking advantage of an existing “number of passengers” field present in my data. End result is that this central station is now prioritised over any others:

Much better! (in case you’re wondering… I’ve manually forced some other non-optimal placement settings for illustrative purposes!)

Obstacle only layers

The third new labelling feature is the option for “Obstacle only” layers. What this option does is allow a non-labelled layer to act as an obstacle for the labels in other layers, so they will be discouraged from drawing labels over the features in the obstacle layer. Again, it’s best demonstrated with an example. Here’s my stations layer with labels placed automatically – you can see that some labels are placed right over the features in the rail lines layer:

Labels over rail lines…

Now, let’s set the rail lines layer to act as an obstacle for other labels:

… setting the layer as an obstacle…

The result is that labels will be placed so that they don’t cover the rail lines anymore! (Unless there’s no other choice). Much nicer.

No more clashing labels!

Control over how polygons act as obstacles for labels

This change is something I’m really pleased about. It’s only applicable for certain situations, but when it works the improvements are dramatic.

Let’s start with my labelled stations map, this time with an administrative boundary layer in the background:

Stations with administrative boundaries

Notice anything wrong with this map? If you’re like me, you won’t be able to look past those labels which cross over the admin borders. Yuck. What’s happening here is that although my administrative regions layer is set to discourage labels being placed over features, there’s actually nowhere that labels can possibly be placed which will avoid this. The admin layer covers the entire map, so regardless of where the labels are placed they will always cover an administrative polygon feature. This is where the new option to control how polygon layers act as obstacles comes to the rescue:

…change a quick setting…

Now, I can set the administrative layer to only avoid placing labels over feature’s boundaries! I don’t care that they’ll still be placed inside the features (since we have no choice!), but I don’t want them sitting on top of these boundaries. The result is a big improvement:

Much better!

Now, QGIS has avoided placing labels over the boundaries between regions. Better auto-placement of labels like this means much less time required manually tweaking their positioning, and that’s always a good thing!

Draw only labels which fit inside a polygon

The last change is fairly self explanatory, so no nice screenshots here. QGIS now has the ability to prevent drawing labels which are too large to fit inside their corresponding polygon features. Again, in certain circumstances this can make a huge cartographic improvement to your map.

So there you go. Lots of new labelling goodies to look forward to when QGIS 2.12 rolls around.

I’ve been working on QGIS for a number of years now and, contrary to what I thought when I started, my wishlist seems to grow longer with every feature I add to QGIS! Unfortunately, almost all of my QGIS development work is done on a volunteer basis and it’s sometimes hard to justify the time required to tackle items on this list. So here’s your chance to help me fix this!

Here’s a quick list of things which I’d love to add to QGIS (or improve), but would need someone to step up and help sponsor their development:

• Raster marker symbol type: Currently QGIS supports a number of marker symbol types (simple markers, font markers, SVG markers) but there’s no option to just use a raster image file for a symbol. A few versions back I added support for a raster image fill type, and now I’d love to do the same for markers. Options could include overriding the image size, rotation and opacity. And of course, all of these properties would be data-definable.
  
• Paint effects for diagrams: The successful Kickstarter campaign meant that QGIS 2.10 includes a powerful framework for applying live effects to layers, including drop shadows, outer glows, blurs, and colour effects (plus lots of others!). I’d like to take this framework and allow effects to be applied to diagrams on a layer. Drop shadows and outer glows would really help aid the readability of diagrams by allowing them to sit on a different visual layer to the rest of the map. The effects framework was designed to allow reuse across all of QGIS, and diagrams would be the next logical step in this.
  

  Layer effects for diagrams! (Well… a mockup of them…)

• Additional diagram types/options: While we’re on the topic of diagrams, there’s lots more that we could do with QGIS’ diagram support. We’ve currently got support for pie charts, text diagrams and histograms, but there’s a lot of really nice diagram styles which we don’t yet support. Everybody loves infographics with nicely designed diagrams… so I’d love the chance to extend what’s possible using QGIS diagram engine. Some ideas include icon arrays, circle packing.
• Adding a geometry widget in the attribute table: This feature has been on my mind a lot lately. What I’d like to add is a new “geometry widget” as the last column in a layer’s attribute table. This widget would allow you to do all sorts of modifications to the geometry attached to a feature. Possible options include clearing the geometry (resetting it to null), copying the geometry as WKT or GeoJSON, or pasting geometry into the feature from a WKT string (making it super easy to copy the geometry between features). This could also be extended in future to start incorporating the editing capabilities current possible through the Plain Geometry Editor plugin.
  

  Poor quality mockup of a geometry widget…

• Options for non square/straight line legend patches: QGIS’ legend currently has no options for customising the shape of legend patches. Polygon layers in the legend are rectangles, line layers are straight lines — that’s it. There’s lots of room for improvement here. I’d like to add options for shapes such as circles, rounded rectangles, jagged lines, and possibly even custom shapes (via a WKT string or something similar).
  

  Custom legend shapes anyone?

• Improving the heatmap plugin: The current heatmap plugin needs some love. The code and UI could do with a big refresh. I’d love a chance to totally revamp this plugin and move it into QGIS core code, and allow it to be used from within processing models. I’d also like to add additional hotspot techniques, such as Getis Ord Gi* hotspotting, to the plugin.
• Extending the raster calculator: QGIS’ raster calculator was given a bunch of needed fixes and improvements in 2.10, but there’s more we could do. The major limitation with the calculator is that it currently only supports functions with at most two parameters. This needs to be fixed so that we can add a bunch of much desired functions to the calculator – eg min, max, avg, coalesce, if, etc… Lack of support for multi-parameter functions is really holding back what’s possible in the calculator.

Of course, this list is just a start. I’m always keen to chat about any other features you’d like to see added to QGIS (or even tackle specific pet-hate bugs or frustrations!). Just drop me an email at [email protected] to discuss.

Oh, one last thing – I’m in the process of preparing for my next crowd funded feature for QGIS – and this one is big! More on that shortly.

TimeManager is a fantastic plugin for QGIS which allows you to create animated maps from your data. You can read all about it here and here, and there’s a really nice demonstration of it here.

I’ve been playing with TimeManager a fair bit over the last month, and thought I’d share a quick tip on improving the appearance of TimeManager’s time stamp. TimeManager includes some basic functionality for placing a time stamp in the corner of your outputs, but it’s fairly limited. There’s only some basic appearance options, and no way to control the date or time formats displayed.

Default TimeManager time stamp

But, there’s a trick we can use to get around this: use a temporary point layer for the time stamp label. Let me elaborate:

1. Create a throwaway point layer. It doesn’t matter what fields or format this layer has.
2. Add a single point feature to this layer at the place you’d like the improved time stamp to appear at.
   

   …add a single point feature

3. We don’t want to see the marker, so hide the symbol for this layer by setting it to use a transparent fill and outline.
   

   Transparent fill and outline

4. Then, enable labels for this layer. Here’s the trick – set the label expression for the label to use “animation_datetime()” (or for QGIS 2.8, “$animation_datetime”). This is a custom function provided by the TimeManager plugin which evaluates to the current frame’s date and time.
   

   Setting the layer’s label expression

5. Now, you can use all the built-in options within QGIS for styling this label. Buffers, drop shadows, background shapes… anything!
   

   …tweaking the label appearance

6. Apply and check. Much nicer!
   

   A nicely formatted time stamp

7. To tweak the formatting of the time stamp’s date and time, you can modify the label expression using the built-in ‘format_date’, ‘year’, ‘month’, etc functions. Let’s try “format_date(animation_datetime(),’ddd dd MMM yyyy’)”:
   

   Tweaked expression

Now, our final formatted time stamp looks like this:

Final, formatted time stamp

…and there we go. Using this simple trick allows you to take advantage of all the possibilities which the QGIS labelling and expression engines allow!

*Bonus points for the first person to use this technique along with data defined controls for animating the label colour/size!

It seems like over the last year the amount of literature published regarding QGIS has really exploded. In the past few months alone there’s been at least three titles I can think of (Building Mapping Applications with QGIS, Mastering QGIS, and the QGIS Python Programming Cookbook). I think this is a great sign of a healthy project. Judging by this there’s certainly a lot of demand for quality guides and documentation for QGIS.

I recently finished reading one of these titles – Building Mapping Applications with QGIS. (Erik Westra, Packt Publishing 2015) In short, I’m a huge fan of this work and think it may be my favourite QGIS book to date! I’ve read Erik’s previous work, Python Geospatial Development, and thought it was an entertaining and really well written book. He’s clearly got an in-depth knowledge about what he’s writing about and this confidence comes through in his writing. So when I first saw this title announced I knew it would be a must-read for me.

In Building Mapping Applications with QGIS, Erik has created a comprehensive guide through all the steps required to create QGIS plugins and standalone Python applications which utilise the QGIS libraries. It’s not a beginner’s guide to Python or to PyQGIS, but that’s what helps it stand out. There’s no introductory chapters on programming with Python or how to use QGIS and instead Erik dives straight into the meat of this topic. I found this approach really refreshing, as I’m often frustrated when the first few chapters of an advanced work just cover the basics. Instead, Building Mapping Applications with QGIS is packed with lessons about, well, actually building mapping applications!

So, why do I like this book so much? Personally, I think it fills a a really crucial void in the existing QGIS literature. There’s a lot of works covering using QGIS, and a few covering PyQGIS development (eg, the PyQGIS Programmer’s Guide, which I reviewed here). But to date, there hasn’t been any literature that covers developing QGIS based applications in such great depth. It’s just icing on the cake that Erik’s writing is also so interesting and easy to read.

Is there any criticisms I have with this book? Well, there’s one small omission which I would have liked to see addressed. While the chapter Learning the QGIS Python API goes into some detail about how QGIS is built using the Qt libraries and a great deal of depth about interpreting the QGIS c++ APIs, I think it could really benefit from some discussion about both the PyQt and Qt APIs themselves. Since a lot of the QGIS classes are either directly derived from Qt classes or heavily utilise them it’s really important that PyQGIS developers are also directed to the PyQt and Qt APIs. For instance, the Qt QColor class is used heavily throughout PyQGIS, but you won’t find any API documentation on QColor in QGIS’ API. Instead, you need to first consult the PyQt API docs and also the detailed Qt c++ docs. It’s often that you may think the PyQGIS API is missing a crucial method, but consulting the Qt docs reveals that the method is instead implemented in the base classes. It’s an important point to note for mastering PyQGIS development. To be fair, I’m yet to read a PyQGIS book which has nailed the interaction between the QGIS, PyQt and Qt APIs.

Honestly, that’s a really minor quibble with an otherwise outstanding work. I’m so glad Erik’s written this work and strongly recommend it to anyone wanting to take their PyQGIS development skills to the next level.