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With the release of the first long term release (2.8 LTR), and two other stable versions (2.10 and 2.12), 2015 was a great (and busy) year for the QGIS community, with lots of improvements and new features landing on QGIS source code.

As a balance, I have asked users to choose wich were their favorite new features during 2015 (from the visual changelogs list). As a result I got the following Top 5 features list.

5 – Python console improvements (2.8)

Since QGIS 2.8, we can drag and drop python scripts into QGIS window and they will be executed automatically. There is also a new a toolbar icon in the plugins toolbar and a shortcut ( Ctrl-Alt-P) for quick access to the python console.

4 – Processing new algorithms (2.8)

Also in QGIS 2.8, there were introduced some new algorithms to the processing framework. If you are into spatial analysis this must have done your day (or year).

• Regular points algorithm
• Symmetrical difference algorithm
• Vector split algorithm
• Vector grid algorithm
• Hypsometric curves calculation algorithm
• Split lines with lines
• Refactor fields attributes manipulation algorithm

3 – Show rule-based renderer’s legend as a tree (2.8)

There were introduced a few nice improvements to QGIS legend. Version 2.8 brought us a tree presentation for the rule-based renderer. Better still, each node in the tree can be toggled on/off individually providing for great flexibility in which sublayers get rendered in your map.

2 – Advanced digitizing tools (2.8)

If you ever wished you could digitize lines exactly parallel or at right angles, lock lines to specific angles and so on in QGIS? Since QGIS 2.8 you can! The advanced digitizing tools are a port of the CADinput plugin and adds a new panel to QGIS. The panel becomes active when capturing new geometries or geometry parts.

1 – Rule-based labeling (2.12)

This was a very awaited feature (at least by me), and it was voted by the majority of users. Since 2.12, you can style features labels using rules. This gives us even more control over placement and styling of labels. Just like the rule based cartographic rendering, label rules can be nested to allow for extremely flexible styling options. For example, you can render labels differently based on the size of the feature they will be rendered into (as illustrated in the screenshot).

There were other new features that also made the delight of many users. For example, the Improved/consistent projection selection (2.8), PostGIS provider improvements (2.12), Geometry Checker and Geometry Snapper plugins (2.12), and Multiple styles per layer (2.8).

Don’t agree with this list? You can still cast your votes. You can also check the complete results in here.

Obviously, this list means nothing at all. I was a mere exercise as with such a diverse QGIS crowd it would be impossible to build a list that would fit us all. Besides, there were many great enhancements, introduced during 2015, that might have fallen under the radar for most users. Check the visual changelogs for a full list of new features.

On my behalf, to all developers, sponsors and general QGIS contributors,

THANK YOU VERY MUCH FOR YOUR TREMENDOUS WORK!

I wish you a fantastic (and productive) 2016.

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)

Another sold-out event with a programme packed with useful, interesting and delightful talks. Fifty seven (57!) folk blew in from all over Scotland through a freezing rain but hot coffee and pastries were waiting in the Informatics Forum at the University of Edinburgh.

First up was an overview the current status of the QGIS project by Saber from Lutra Consulting. It was good for people new to QGIS and open-source to see how the project is organised and run and the direction it is taking. Pete, also from Lutra Consulting, then gave a quick summary of the bits of core functionality they have been working on including the new ruled based labelling system.
The group then split into two for 90 minute workshop sessions on cartographic labelling and advanced Atlas usage – a tough choice! Chris, from Ordnance Survey, presented a detailed how-to on the new ruled based labelling tools using some OS open data, interspersed with some slides on guidelines to good cartographic practices and labelling tips. The slides and material for this workshop are available here: https://dl.dropboxusercontent.com/u/185489368/QGIS-Scotland2015.pdf

Heikki, from thinkWhere, lead us through the process of using Atlas in Print Composer to automate map production for a series of maps containing a main context map and an inset overview map. Nothing better than doing something once and then being able to repeat it at the click of a button! The slides and material for this workshop are available here: https://github.com/HeikkiVesanto/Scottish_QGIS_User_Workshop

A break for lunch and a good hour of catching up with users from across all sectors – local government, central government, academia, forestry, planning consultancies, developers, student life and education. QGIS is popular and is obviously a flexible tool that meets many demands.

After lunch, Neil, from thinkWhere, organised a quick-fire “quirky QGIS quiz” with random questions from all aspects of FOSS4G demanding quick thinking for true/false answers. At least half the audience grabbed prizes courtesy of thinkWhere and Ordnance Survey.

What followed was a series of lightning talks on different aspects of using QGIS. Amy, from Cawdor Forestry, gave a brief overview of the plugins available in the QGIS plugin repository and highlighted some of her personal favourites. Paul, from Scottish Water, showcased some of the complex workflows created using SAGA, QGIS and the Processing Toolbox to model hydrological process. Ross, from Inverclyde Council, demonstrated the use of the QGIS Road Graph plugin to generate walking routes to school across a custom road and path network. Seb, from West Dunbartonshire Council, showed us how QGIS had put them in a happy place and showed how a “hearts and minds” campaign championing QGIS had changed the way they worked. Steve, fae Embra, gave some information on how to give back to the QGIS project through submitting Processing scripts and plugins to the repository. Don’t reinvent the wheel! Ross, from Angus Council, gave a quick demonstration of setting up a local plugin repository that could be used to share custom plugins or control access to plugins in an internet-less environment.

By this time, tea and cake was required and it gave everyone an opportunity to mix and ask questions of the speakers.

The last session was as series of longer talks started by Gemma, from Ordnance Survey, explaining how open-source software is used extensively at Ordnance Survey to underpin a lot of the cartographic processes and workflows. They use QGIS 2.8 LTR for stability and consistency across the business and a selection of plugins from both OS developers and the community. QGIS is used to generate all the cartographic styles sheets for the OS vector products: https://github.com/OrdnanceSurvey/OS-VectorMap-District-stylesheets

Tom, from EDINA, explained the processing of creating and delivering a QGIS training course to University staff and students. The first class sold out in next to no time and there is demand for more. Makes sense really, doesn’t it?

Steve, from GeoGeo, wrapped up the day with the kind of mapping we’d all like to be doing – high resolution elevation models, time series analysis of shadows, viewsheds across the Edinburgh skyline and analysis of rooftops for potential solar panels with sub 1m resolution LiDAR datasets. He uses a mix of QGIS, SAGA, Blender and other FOSS to inspiring effect. Check his Flickr stream: https://www.flickr.com/photos/stevefaeembra/

The day finished with Pete (Lutra Consulting) releasing into the open a new Search plugin for QGIS called Discovery (http://www.lutraconsulting.co.uk/products/discovery/) based on the PostGIS Search plugin from Tim Martin (Ordnance Survey). A very useful addition to any QGIS installation.

The day was sponsored by EDINA, thinkWhere and Ordnance Survey.

Links to slides will be coming shortly.

The task of projecting, or unfolding the spherical Earth onto a flat map, is an age old problem in cartography. Projection almost always introduces distortion, most projections cannot preserve angles, areas and distances at the same time, they may be conformal (angle-preserving), equal-area (area-preserving) or equidistant (distance preserving) but not all at once. The only exception is a Globe, which preserves angles, areas and distances perfectly. Thus a projection is a compromise.

The choice of projection depends on a map’s use, scale and audience. Conformal projections, for example, are preferred for nautical charts or small scale maps because they locally preserve angles necessary for navigation and survey drawings. Equal-area projections are best suited for maps of broad continental region as they preserve the relative sizes of countries, seas and oceans and allow comparison between regions. Finally, there are hybrid projections that minimise the distortion by merging conformal and equal-area projections, these can be used to create visually pleasing maps of the entire Earth (for a guide to selecting a map projection see Fig. 9 in Jenny (2011), link below).

But how does one measure the degree and type of distortion in a map projection?

One elegant method was developed in the 1880s century by the French cartographer Monsieur Nicolas Auguste Tissot, the Tissot’s Indicatrix (or Tissot’s Ellipse). This mathematical contrivance consists of a grid of infinitely small circles that measures the degree and type of distortion caused by projection. While Monsieur Tissot’s approach is mathematical, involving infinity small circles, his technique can be approximated overlaying a regular grid of large circles and crosses to a map.

The Indicatrix Mapper plugin for QGIS by Ervin Wirth and Peter Kun creates a Tissot’s Indicatrix by adding a vector layer of circles and crosses in a gridded pattern on a map. The degree and type of distortion of the Tissot’s Indicatrix reveals the class of map projection as follows: –

• If a projection is conformal, the area of circles and sizes of the crosses will change while the shapes of circles remain the same and intersection angle of the crosses will always meet at 90 degrees e.g. Mercator projection

• If a projection is equal-area, the area of the circles will remain the same while the shape of the circles change and intersection angle of the crosses will not always meet at 90 degrees e.g. Mollweide projection or Hammer projection

• If a projection preserves neither property, the area of the circles and their shape will change, and the intersection angle of the crosses will not always meet at 90 degrees e.g. Robinson

After adding the Indicatrix Mapper plugin to QGIS (menu Plugins – Manage and Install Plugins) first add a basemap using the OpenLayers plugin e.g. Bing Aerial layer, then click the Indicatrix Mapper icon and run the plugin using default settings. You can then select different projections (lower right in world icon QGIS) to see the effects of various protections on the Tissot Indicatrix. If the circles appear as squares after selecting a different projection, right click the Circles layer in the layers panel, then select the Rendering tab and deselect the Simplify geometry check box. Also, turn off the basemap layer when using different projections, unfortunately the OpenLayers plugin only supports Google Mercator projection (EPSG 3857). To create the basemap below, that can be displayed using different projections, I styled vector data downloaded from Natural Earth and OpenStreetMap.

Mercator Projection – the area of the circles and size of the crosses increase towards the poles but their shape remains the same.

Mollweide Projection – the area of the circles remain the same but their shapes are distorted, the crosses do not always intersect at 90 degrees.

Robinson Projection – both the area of the circles and intersection angle of the crosses circles vary.

It is important to note that a Tissot’s Indicatrix generated in QGIS is an approximation of mathematical ideal, we are not no longer dealing with infinity small circles. As a result, here will be some minor distortion visible towards the edge of a map independent of the projection used; notice that the circles in the Mercator projection nearest the poles are not quite symmetrical or the circles at the edge of the Mollweide projection do not appear to preserve area as they should. This anomalous distortion can be minimised by reducing the size and spacing of the circles and crosses created by the Indicatrix Mapper plugin. However, despite these limitations a Tissot’s Indicatrix elegantly reveals the distortion present. This is something to important to understand when when choosing a map projection.

References:

Last year we described a command line method that adds ESRI REST layers in QGIS. Well, a team at the Geometa Lab in the University of Applied Sciences Rapperswil (HSR) Switzerland, have released a plugin for QGIS that adds ESRI REST layers via a GUI (Github page). The plugin is experimental so you will need to tick the box “Show also experimental plugins” in the settings panel of the “Plugins – Manage and Install Plugins” dialogue in order to add the plugin to QGIS. The following URLs lists numerous REST layers in the plugin’s GUI:

http://services.arcgisonline.com/arcgis/rest/services

http://basemap.nationalmap.gov/arcgis/rest/services

http://services.nationalmap.gov/arcgis/rest/services

Reference:

REST API Connector Plug-in Wiki Page

In this tutorial I will show you how to create a Hillshaded topographic map in QGIS. We will be using Shuttle Radar Topography Mission (SRTM) data, a near global Digital Elevation Model (DEM) collected in February 2000 aboard NASA’s Space Shuttle Endeavour (mission STS-99). The mission used a X-Band mapping radar to measure the Earth’s topography, built in collaboration with the U.S. Jet Propulsion Laboratory, the U.S. National Imagery and Mapping Agency (now the National Geospatial-Intelligence Agency), and the German and Italian space agencies.

The raw radar data has been continuously processed and improved since it was first collected. Countless artefacts have been painstakingly removed and areas of missing data have been filled using alternate data sources. The version we will be using is the 1 Arc-Second Global SRTM dataset, an enhanced 30 meter resolution DEM that was released last year. It is a substantial improvement over the 3 Arc-Second / 90 meter SRTM data previously available for Ireland. SRTM elevation data can be downloaded from the United States Geological Survey’s EarthExplorer website.

When first loaded into QGIS (via Add Raster Layer), the DEM is displayed as a rather uninformative black and white image.

It is therefore necessary to apply a suitable colour ramp that accentuates topography. While it is possible to create your own colour ramp, or use one of the colour ramps provided by QGIS, superior colour ramps can be downloaded using Etienne Tourigny’s Color Ramp Manager (Plugins – Manage and Install Plugins). After the plugin is added to QGIS, go to the Plugins menu again and choose the Colour Ramp Manager.

In the window that pops up, choose the full opt-city package and click check for update. The plugin will then download the cpt-city library, a collection of over a hundred cartographic gradients (version 2.15). After the package downloads, quit the dialogue.

Back in QGIS, right click the DEM layer to bring up the Layer Properties dialogue. In the Style tab, change the render type from single band grey to single band pseudocolor. Then click new color ramp and new color ramp again, choose the cpt-city color ramp to bring up the cpt-city dialogue. Click topography and choose the sd-a colour ramp. While this is an excellent colour ramp, I find its colours are a bit too strong for my liking.

Still in the Layer Properties dialogue, change the min and max values to match your DEM’s lowest and highest elevations values and click classify, this applies the new colour ramp. Next, change the brightness to 30 and lower the contrast and saturation to -20. Click OK to apply the new style and quit the Layer Properties dialogue.

Next we need to create a Hillshade layer from the DEM, a 3D like visual representation of topographic relief. This is achieved via the menu Raster – Analysis – DEM (Terrain models). There is one small catch, the hillshading algorithm assumes the DEM’s horizontal units are in meters (they are decimal degrees). We need to enter a scale correction factor of 111120 (in the Scale ratio vert. units to horiz. box). Once that is all done, select an output path to save the generated hillshade and click OK. Generating a hillshade may take up to a minute depending on the size of your DEM.

After the hillshade is created, open its Layer properties dialogue. Change the min and max values to 125 and 255, increase its brightness to 45 and contrast to 20. Finally, switch the blending mode from normal to multiply. This allows the DEM beneath the hillshade to show though. Click OK to apply the new style.

If you followed these steps correctly you will have created a fine looking topographic map similar to the one below. It’s also possible to create contours but that’s a tutorial for another day.

Technical note:

There are two hillshading algorithms available in QGIS, one by Horne (1981) and another by Zevenbergen and Thorne (1987). Jones (1998) examined the quality of hillshading algorithms, he found the algorithm of Fleming and Ho€er (1979) is slightly superior to Horne’s (1981) algorithm. Zevenbergen and Thorne’s (1987) algorithm is a derivation of Fleming and Ho€er’s (1979) formula. QGIS uses Horne’s (1981) algorithm by default.

References:

Horn, B.K., 1981. Hill shading and the reflectance map. Proceedings of the IEEE, 69, 14–47.

Jones, K.H., 1998. A comparison of algorithms used to compute hill slope as a property of the DEM [PDF]. Computers & Geosciences, 24, 315–323.

EN | PT

Now and then I get too many map symbols (points) in the same place, and I thought how nice it would be if we could drag n’ drop them around without messing with their geometries position, just like we do with labels. That thought gave me an idea for a cool hack.

Choose your point layer and start by creating two new fields called symbX and symbY (Type: Decimal number; Size: 20; Precision: 5). Now go the layer properties and in the Style tab edit your symbol. For each level of your symbol select “map units” as the offset units, and set the following expression in the offset data define properties option:

CASE WHEN symbX IS NOT NULL AND symbY IS NOT NULL THEN
    tostring($x - symbX) + ',' + tostring($y - symbY)
ELSE
    '0,0'
END

Be aware that, if your coordinates have negative values, you need to adapt the code. E.g., If you have negative values in X you should use “tostring(symbX -$x)” instead.

Now, temporarly  label your layer with a small convenient text (I used a centered ‘+’ (plus sign) with a white buffer) and set its coordinates to data defined using the symbX and symbY Fields.

From this point on, when you use the move label tool, not only the label position change but also the actual symbol! Pretty cool, isn’t it?

Notice that the features geometries are not changed during the process. Also, remember that in this case you can also add leading lines to connect the symbols to the original position of the points.

Sea Surface Temperature data downloaded by Oceancolor Data Downloader.

The Oceancolor Data Downloader is a new plugin for QGIS from the Mapping and Geographic Information Centre of the British Antarctic Survey that downloads Oceancolor and Sea Surface Temperature data from NASA’s Oceancolor website. The plugin currently downloads three datasets:

• MODIS AQUA chlorophyll concentration
• SeaWiFS chlorophyll concentration
• MODIS AQUA night time Sea Surface Temperatures

The data accessed includes daily, 8 day, monthly and yearly composites, all of which can be saved to disk while downloading. Future plans for the plugin include additional access to other datasets such as ocean Net Primary Production, selection by bounding box, the ability to save in other formats, a progress bar etc.

I used the plugin to download global Sea Surface Temperatures for the 13th Jan 2015. I then used shapefiles from Natural Earth to create a simple basemap. I finally chose the IBCAO Polar Stereographic projection (EPSG: 3996) to create a map centred on the North Pole.

If you use the plugin to produce published research, please cite: