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Fri Jun 23 00:00:11 2017

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QGIS Planet

A QGIS router for GIP.at

Monday, January 4th 2016, was the open data release date of the official Austrian street network dataset called GIP.at. As far as I know, the dataset is not totally complete yet but it should be in the upcoming months. I’ve blogged about GIP.at before in Open source IDF parser for QGIS and Open source IDF router for QGIS where I was implementing tools based on the data samples that were available then. Naturally, I was very curious if my parser and particularly the router could handle the whole country release …

Some code tweaking, patience for loading, and 9GB of RAM later, QGIS happily routes through Austria, for example from my work place to Salzburg – maybe for some skiing:

Screenshot 2016-01-06 17.11.27

The routing request itself takes something between 1 and 2 seconds. (I should still add a timer to it.)

So far, I’ve implemented shortest distance routing for pedestrians, bikes, and cars. Since the data also contains travel speeds, it should be quite straight-forward to also add shortest travel time routing.

The code is available on Github for you to try. I’d appreciate any feedback!


Routing in polygon layers? Yes we can!

A few weeks ago, the city of Vienna released a great dataset: the so-called “Flächen-Mehrzweckkarte” (FMZK) is a polygon vector layer with an amazing level of detail which contains roads, buildings, sidewalk, parking lots and much more detail:

preview of the Flächen-Mehrzweckkarte

preview of the Flächen-Mehrzweckkarte

Now, of course we can use this dataset to create gorgeous maps but wouldn’t it be great to use it for analysis? One thing that has been bugging me for a while is routing for pedestrians and how it’s still pretty bad in many situations. For example, if I’d be looking for a route from the northern to the southern side of the square in the previous screenshot, the suggestions would look something like this:

Pedestrian routing in Google Maps

Pedestrian routing in Google Maps

… Great! Google wants me to walk around it …

Pedestrian routing on openstreetmap.org

Pedestrian routing on openstreetmap.org

… Openstreetmap too – but on the other side :P

Wouldn’t it be nice if we could just cross the square? There’s no reason not to. The routing graphs of OSM and Google just don’t contain a connection. Polygon datasets like the FMZK could be a solution to the issue of routing pedestrians over squares. Here’s my first attempt using GRASS r.walk:

Routing with GRASS r.walk

Routing with GRASS r.walk (Green areas are walk-friendly, yellow/orange areas are harder to cross, and red buildings are basically impassable.)

… The route crosses the square – like any sane pedestrian would.

The key steps are:

  1. Assigning pedestrian costs to different polygon classes
  2. Rasterizing the polygons
  3. Computing a cost raster for moving using r.walk
  4. Computing the route using r.drain

I’ve been using GRASS 7 for this example. GRASS 7 is not yet compatible with QGIS but it would certainly be great to have access to this functionality from within QGIS. You can help make this happen by supporting the crowdfunding initiative for the GRASS plugin update.


Exploring open government population data collected by ODVIS-AT

At FOSS4G2013, I had the pleasure to attend a presentation about the ODVIS.AT project by Marius Schebella from the FH Salzburg. The goal of the project – which ended in Summer 2014 – was “to display open data (demographic, open government data) in a quick and easy way to end users” by combining it with OpenStreetMap. Even though their visualization does not work for me (“unable to get datasets” error), not all is lost because they provide an SQL dump of their PostGIS database.

Checking the data, it quickly becomes apparent that each data publisher decided to publish a slightly different dataset: some published their population counts as timelines over multiple years, others classified population by migration background, age, or gender. Also, according to the metadata table, no data from Salzburg and Burgenland were included. Most datasets’ reference date is between 2011 and 2013 but the data of the westernmost state Vorarlberg seems to be from 2001.

Based on this database, I created a dataset combining the municipalities with the Viennese districts and joined the population data from the individual state tables. The following map shows the population density based on this dataset: it is easy to recognize the densely populated regions around Vienna, Linz, Graz, and in the big Alpine valleys.

odvis_popdens

Overall, it is incredibly time-consuming to create this seemingly simple dataset. It would be very helpful if the publishers would agree on a common scheme for releasing at least the most basic information.

Considering that OpenStreetMap already contains population data, it barely seems worth all the trouble to merge these OGD datasets. Granted, the time lines of population development would be interesting but they are not available for each state.

P.S. If anyone is interested in the edited database, I would be happy to share the SQL dump.


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