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Wed Nov 14 15:20:12 2018

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QGIS Planet

Visualize Postgres JSON data in QML widgets

As promised some time ago in “The new QML widgets in QGIS – When widgets get unbridled” we still owe you some fancy unicorns, but first let’s have a look at another nice feature that has been introduced in QGIS 3.4

My favorite new recipe in QGIS Map Design 2nd ed

If you follow me on Twitter, you have probably already heard that the ebook of “QGIS Map Design 2nd Edition” has now been published and we are expecting the print version to be up for sale later this month. Gretchen Peterson and I – together with our editor Gary Sherman (yes, that Gary Sherman!) – have been working hard to provide you with tons of new and improved map design workflows and many many completely new maps. By Gretchen’s count, this edition contains 23 new maps, so it’s very hard to pick a favorite!

Like the 1st edition, we provide increasingly advanced recipes in three chapters, each focusing on either layer styling, labeling, or creating print layouts. If I had to pick a favorite, I’d have to go with “Mastering Rotated Maps”, one of the advanced recipes in the print layouts chapter. It looks deceptively simple but it combines a variety of great QGIS features and clever ideas to design a map that provides information on multiple levels of detail. Besides the name inspiring rotated map items, this design combines

  • map overviews
  • map themes
  • graduated lines and polygons
  • a rotated north arrow
  • fancy leader lines

all in one:

“QGIS Map Design 2nd Edition” provides how-to instructions, as well as data and project files for each recipe. So you can jump right into it and work with the provided materials or apply the techniques to your own data.

The ebook is available at LocatePress.

(Nederlands) BGT Import plugin vernieuwd

Sorry, this entry is only available in the Dutch language

The new QML widgets in QGIS – When widgets get unbridled

Individuality is the definition of freedom. And freedom is the fundamental requirement of man’s mind. QGIS possibly cannot give you all the freedom you require in life. But at least a lot of freedom in how you manage your work.

Add Realistic Mist and Fog to Topography in QGIS 3.2

I recently came across a great tutorial by in which he demonstrated how to create map of Switzerland in the style of Edward Imhof, the famed Swiss cartographer renowned for his hand painted maps of Switzerland and other mountainous regions of the world. John’s map used traditional hillshading, multidirectional hillshading and crucially, a translucent topographic layer that created a mist like appearance he likened to the sfumato technique used by painters since the Renascence.

I followed John’s tutorial in QGIS 3.2 and I was quite pleased with the initial result below. However, the process creating it is a bit too complicated for a tutorial so I set about simplifying the process and rather than imitating Imhof’s distinct style, my goal this time is realism.

The heart of the effect involves the very clever idea of using the topographic layer as a subtle opacity mask to simulate mist, fog and atmospheric haze. Have a look at the image below taken on March 17th, 2005 by NASA’s Terra satellite. This is the industrialised Po valley of northern Italy, surrounded by the Alps and Apennine Mountains that rise above the valley’s hazy pollution. The haze adds a sense of depth to the surrounding hills and mountains. It’s not uncommon to see fog and pollution in satellite imagery that gives way to the clear air in high mountains e.g. northern India and Nepal, China, Pakistan and India. Creating a similar mist effect in QGIS is actually quite simple.

First download topography for the Alps and Po region (a 68.55 Mb GeoTiff file derived from freely available EU-DEM data I resampled from 25 to 100m resolution). Next, make sure you have the plugin QuickMapServics (QMS) installed (menu Plugins – Manage and Install Plugins). This great plugin provides access to over 1000 basemaps.

Load the GeoTiff file into QGIS (Raster – Load) and rename the layer Hillshade. Right click the layer to open the Layer Properties window. In the Symbology panel, next to Render Type, choose Hillshade. Change the altitude to 35 degrees, Azimuth to 300 degrees and Z Factor of 1.5 (illuminating the landscape from the top left). Finally, change the Blending mode to Multiply. Click OK to close the dialogue.

To add the basemap layer, Esri World Imagery (Clarity), type “ESRI clarity” in the QMS search bar to find and add the basemap; Go to View – Panels and activate the QMS search bar if it isn’t initially visible. Make sure it’s the bottommost layer.

Oh, that’s a bit disappointing, we only increased the relief little a bit. It’s missing the vitally important mist layer.

To create mist, right click the Hillshade layer and choose Duplicate. Rename the new layer Mist and make sure it’s above the Hillshade layer. Now open the Layer Properties window of the layer, we’re going edit it’s attributes to make it look like mist.

Change the Render type to Singleband Pseudocolor and use 0 and 3000 for the min and max values (limiting maximum latitude of the mist to 3000 meters). Then open the colour ramp window by clicking on the Color ramp and enter these values:

  • Left Gradient – HSV 215 15 50 and 75% transparency
  • Right Gradient – HSV 215 15 50 and 0% transparency

Close the Color Ramp dialogue. In the Layer Properties window, and this is very important, change the Blending mode to Lighten. Click OK to close the Layer Properties window.

Wow, we have mist!

The mist effect looks great. It certainly adds a lot of realism to the topographic map, it now looks quite like NASA’s images. This is just a quick and basic map so there’s lots of scope to improve the effect. Play around with the colour of the mist layer and its opacity, or even brighten the Hillshade layer underneath. See what effects these changes have.

Here’s another example below. In this example I duplicated the hillshade layer and set the second hillshade layer to Multidirectional Hillshading (yes, QGIS 3.2 has Multidirectional Hillshading). I then adjusted the transparency of both hillshade layers so they blended together nicely. I then replaced the basemap with another duplicated topography layer that I coloured using the gradient sd-a (by Jim Mossman, 2005) using the cpt-city plugin. And lastly, I doubled the opacity of the mist layer turning it into a milky fog. I think it looks great!

What next? Well, there’s lots of possibilities. Perhaps download Martian topography and add mist to the bottom of Valles Marineris?

References:

Eduard Imhof – Biography

TV documentary about Eduard Imhof

The Map as an Artistic Territory: Relief Shading Works and Studies by Eduard Imhof

Haze in northern Italy – NASA Terra Satellite

Tzvetkov, J., 2018. Relief visualization techniques using free and open source GIS tools. Polish Cartographical Review, 50(2), pp.61-71.

Programme change…

See the Dutch website for more info on the programme.

Edit Features “In Place” crowdfund — made it to QGIS 3.4!

Well, thanks to the resounding success of our QGIS edit-in-place crowdfunding campaign, we’ve been frantically smashing away at our keyboards in an attempt to reward the QGIS community by sneaking this feature in a whole 4 months earlier than originally promised! And, we’re very proud to announce, that this exciting new feature has been implemented and will be included in the upcoming QGIS 3.4 release (due late October 2018). So go ahead — grab one of the nightly pre-release of QGIS 3.4 and checkout the results.

This wouldn’t have been possible without the rapid response to the campaign and the generosity of our wonderful backers:

(In addition to these backers, we’ve also received numerous anonymous donations to this feature from many other individuals — while we can’t list you all publicly, you’re also in our thanks!)

 

Keep an eye on this blog for other upcoming QGIS crowdfunding campaigns targeted at QGIS 3.6 and beyond… we’ve got lots more exciting work planned for these releases!

 

Dutch QGIS usergroup meeting

All presentations will be in Dutch. Please have a look at the Dutch version of this page to see more…

Edit Features “In Place” crowdfund — target reached!

Well, the final pledges have been tallied and we’re very proud to announce that our latest crowd funding campaign has been a roaring success!

We’ve been completely blown away by the response to this campaign. Thanks to some incredibly generous backers and donors, we’ve been able to hit the campaign target with plenty of time to spare. As a result, we’ll be pushing hard to reward the generosity of the community by trying to sneak this feature in for the upcoming QGIS 3.4 release (instead of the originally promised 3.6 release)! You can read more about what we’re adding at the campaign page.

We’d like to take this opportunity to extend our heartfelt thanks to all the backers who have pledged to support this project:

In addition to these backers, we’ve also received numerous anonymous donations to this feature from many other individuals — while we can’t list you all publicly, you’re also in our thanks!

Stay tuned for more updates to come as work proceeds on this feature…

QGIS speaks a lot of languages

QGIS is a real cosmopolitan. Born in Alaska sixteen years ago, it has spread all over the world since. Thanks to its open source mentality, it finds not only in economically strong countries big usergroups. No question, that beside all

(Nederlands) 3 oktober QGIS gebruikersdag in Nieuwegein

Sorry, this entry is only available in the Dutch language

OpenCL acceleration now available in QGIS

What is OpenCL?

From https://en.wikipedia.org/wiki/OpenCL:

OpenCL (Open Computing Language) is a framework for writing programs that execute across heterogeneous platforms consisting of central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs) and other processors or hardware accelerators. OpenCL specifies programming languages (based on C99 and C++11) for programming these devices and application programming interfaces (APIs) to control the platform and execute programs on the compute devices. OpenCL provides a standard interface for parallel computing using task- and data-based parallelism.

Basically, you write a program and you execute it on a GPU (or, less frequently, on a CPU or on a DSP) taking advantage of the huge parallel programming capabilities of the modern graphic cards.

Depending on many different factors, the speed gain can vary to a great extent, but it is typically around one order of magnitude.

How QGIS benefits from OpenCL?

The work I’ve done consisted in integrating OpenCL support into QGIS and writing all the utilities to load, build and run OpenCL programs.

For now, I’ve ported the following QGIS core algorithms, all of them are availabe in processing:

  • slope
  • aspect
  • hillshade
  • ruggedness

Since the framework to support OpenCL is now in place, I think that more algorithms will be ported over the time.

During this development, even if was not in scope, the hillshade renderer has been optimized for speed and it can also benefit of OpenCL acceleration.

How to activate OpenCL support

OpenCL support is optional and opt-in, to use it, you need to activate it into the QGIS options dialog like shown in the screenshot below:

How much performance gain can I expect?

Well, YMMV, but here are some figures for a big DEM raster, low values mean faster execution.

GDAL means CPU execution using the GDAL processing algorithm.

How to install the OpenCL drivers?

Of course it depends on your specific hardware and on your O.S., AMD, NVidia and Intel have different distributions channels, in general the driver for your graphic card will also provide the OpenCL driver, if your GPU is compatible, if OpenCL is not available on your current machine, try to Google for OpenCL, your O.S. and graphic card.

If there is no OpenCL support for your graphic card, you might try to install a driver for your GPU (Intel for example provides them) and you will probably have a decent acceleration even if not as much as you can get on a real graphic card.

This fact worths some more explanation: you might ask your self why running and algorithm directly on the CPU and running it on the same CPU but using OpenCL would make any difference and the reason why it is generally faster by using OpenCL is that OpenCL will run the algorithm in parallel on all cores of your CPU, while a normal application (and QGIS does not make an exception here) will use a single core.

Credits

I started this work as a proof of concept in my spare time (that it is not much, lately) and when I realized that it was promising, I submitted a QGIS grant proposal in order to allocate some working time to port more algorithms, write tests and polish the implementation.

This work would not be possible without all the generous sponsors and donors that feed the QGIS grant program year after year, many thanks to the QGIS community for this amazing support!

Jürgen Fischer was as usual very helpful and took care of the windows builds, now available in OSGeo4W packages.

Nyall Dawson helped with the code review and with testing the implementation on different cards and machines.

Matthias Kuhn reviewed the code.

Even Rouault pointed me to some highly efficient GDAL algorithm optimizations that I’ve been able to integrate in QGIS.

 

 

Edit Features “In Place” Using QGIS Spatial Operations crowdfund launched!

We’ve just launched a new QGIS crowd funding campaign which we’re super-excited about! This time, we’re addressing what we see as the major shortcoming within QGIS vector layer editing tools, and bridging the gap between the vast power of QGIS’ Processing algorithms and easy-to-use operations which modify layer features “in place”. Here’s a quick sneak preview of what we have planned:

 

QGIS is already a vector editing powerhouse, and we believe that this improvement will boost the current functionality up an order of magnitude! To make it possible we need 6500€ pledged before 30 September 2018.

This is also our first crowdfunding campaign in which we’re running a “dual funding” approach, which we think should make things friendly and easy for both corporate backers and end user contributions alike. Read more about this at the full campaign page.

You can help make this a reality by supporting the campaign or by sharing the page and increasing exposure to the campaign. Updates to follow!

 

Using Threads in PyQGIS3

While porting a plugin to QGIS3 I decided to also move all it’s threading infrastructure to QgsTasks. Here three possible variants to implement this. the first uses the static method QgsTask.fromFunction and is simpler to use. A great quick solution.

PyQGIS for non-programmers

If you’re are following me on Twitter, you’ve certainly already read that I’m working on PyQGIS 101 a tutorial to help GIS users to get started with Python programming for QGIS.

I’ve often been asked to recommend Python tutorials for beginners and I’ve been surprised how difficult it can be to find an engaging tutorial for Python 3 that does not assume that the reader already knows all kinds of programming concepts.

It’s been a while since I started programming, but I do teach QGIS and Python programming for QGIS to university students and therefore have some ideas of which concepts are challenging. Nonetheless, it’s well possible that I overlook something that is not self explanatory. If you’re using PyQGIS 101 and find that some points could use further explanations, please leave a comment on the corresponding page.

PyQGIS 101 is a work in progress. I’d appreciate any feedback, particularly from beginners!

Create a QGIS vector data provider in Python is now possible

 

Why python data providers?

My main reasons for having Python data provider were:

  • quick prototyping
  • web services
  • why not?

 

This topic has been floating in my head for a while since I decided to give it a second look and I finally implemented it and merged for the next 3.2 release.

 

How it’s been done

To make this possible I had to:

  • create a public API for registering the providers
  • create the Python bindings (the hard part)
  • create a sample Python vector data provider (the boring part)
  • make all the tests pass

 

First, let me say that it wasn’t like a walk in the park: the Python bindings part is always like diving into woodoo and black magic recipes before I can get it to work properly.

For the Python provider sample implementation I decided to re-implement the memory (aka: scratch layers) provider because that’s one of the simplest providers and it does not depend on any external storage or backend.

 

How to and examples

For now, the main source of information is the API and the tests:

To register your own provider (PyProvider in the snippet below) these are the basic steps:

metadata = QgsProviderMetadata(PyProvider.providerKey(), PyProvider.description(), PyProvider.createProvider)
QgsProviderRegistry.instance().registerProvider(metadata)

To create your own provider you will need at least the following components:

  • the provider class itself (subclass of QgsVectorDataProvider)
  • a feature source (subclass of QgsAbstractFeatureSource)
  • a feature iterator (subclass of QgsAbstractFeatureIterator)

Be aware that the implementation of a data provider is not easy and you will need to write a lot of code, but at least you could get some inspiration from the existing example.

 

Enjoy wirting data providers in Python and please let me know if you’ve fond this implementation useful!

Locatieserver: about parcels and roadnumbers

For those interested in dutch OpenData: our national OpenData service PDOK has a Solr based geocoding service available. Since this week it is possible to search for ‘parcel’ codes to find cadastral parcels, but also to search on so called ‘hectometer-paaltjes': the little green number signs you see when you drive the dutch highways. So … Continue reading Locatieserver: about parcels and roadnumbers

AmsterdamTimeMachine

Via twitter: AmsterdamTimeMachine.nl. Jan Hartman’s and WebMappers hard work of georeferencing a set of Old Amsterdam maps: http://amsterdamtimemachine.nl. 6 XYZ-Map services with maps old as 1625 to have a look into history, off course also to be loaded in QGIS Wanna see ‘the red light district’ in 1625? Or see Dutch 17th century glory on … Continue reading AmsterdamTimeMachine

Coding a QgsLocator (Plugin)

What is a Locator (plugin) Some months ago, Nyall Dawson silently dropped a nice widget into the lower left corner of your QGIS screen: People familiar with QtCreator (the Qt-development environment) should recognize it as a QtCreator Locator look-a-like: a way to (very) quickly search in your project for words, classes, bookmarks, help topics, files … Continue reading Coding a QgsLocator (Plugin)

Movement data in GIS #13: Timestamp labels for trajectories

In Movement data in GIS #2: visualization I mentioned that it should be possible to label trajectory segments without having to break the original trajectory feature. While it’s not a straightforward process, it is indeed possible to create timestamp labels at desired intervals:

The main point here is that we cannot use regular labels because there would be only one label for the whole trajectory feature. Instead, we are using a marker line with a font marker:

By default, font markers only display one character from a given font but by using expressions we can make it display longer text, including datetime strings:

If you want to have a label at every node of the trajectory, the expression looks like this:

format_date( 
   to_datetime('1970-01-01T00:00:00Z')+to_interval(
      m(start_point(geometry_n(
         segments_to_lines( $geometry ),
         @geometry_part_num)
      ))||' seconds'
   ),
   'HH:mm:ss'
)

You probably remember those parts of the expression that extract the m value from previous posts. Note that – compared to 2016 – it is now necessary to add the segments_to_lines() function.

The m value (which stores time as seconds since Unix epoch) is then converted to datetime and finally formatted to only show time. Of course you can edit the datetime format string to also include the date.

If we only want a label every 30 seconds, we can add a case statement around that:

CASE WHEN 
m(start_point(geometry_n(
   segments_to_lines( $geometry ),
   @geometry_part_num)
)) % 30 = 0
THEN
format_date( 
   to_datetime('1970-01-01T00:00:00Z')+to_interval(
      m(start_point(geometry_n(
         segments_to_lines( $geometry ),
         @geometry_part_num)
      ))||' seconds'
   ),
   'HH:mm:ss'
)
END

This works well if the trajectory sampling interval is fairly regular. This is not always the case and that means that the above case statement wouldn’t find many nodes with a timestamp that ends in :30 or :00. In such a case, we could resort to labeling nodes based on their order in the linestring:

CASE WHEN 
 @geometry_part_num  % 30 = 0
THEN
...

Thanks a lot to @JuergenEFischer for providing a solution for converting seconds since Unix epoch to datetime without a custom function!

Note that expressions using @geometry_part_num currently suffer from the following issue: Combination of segments_to_lines($geometry) and @geometry_part_num gives wrong segment numbers


This post is part of a series. Read more about movement data in GIS.

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