PG routing – driving distance

Building on the work of previous posts looking at building routable networks and finding the shortest path in a network, this post will look at creating buffers around nodes based on a cost attribute specifed by the user.

The driving distance function, which comes with pg routing 2.0, creates an alpha shape around a node, normally based on the distance someone could travel from that node, or how far someone could go in a time interval.

For this example, we are looking at where someone could travel in 1km along the network from a central node. The following query selects all the nodes that are within 1 km of node 2000.

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PG routing – shortest path algorithms

Once a routable network has been set up we can start to find the shortest path (using Dijkstra’s algorithm) between two points. From here on, I will be using the OSM data for the London road network.

The query use’s a ‘cost’ column – which could be anything thing you like – to calculate the shortest cost from one node to another. In this example I decided to use travel time (rather than distance).

First, I changed the distance of each vertex (the way table) from km to miles, and then calculated the time it would take to traverse each vertex whether walking, cycling or driving. To make this more accurate, I updated the max speed (forward and backward) along each vertex dependent on its class (as listed in the class table).

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PG Routing – Creating a routable network

As an open source alternative to ESRI’s Network Analyst, PG routing provides a very solid platform to perform routing queries. This post, in tandem with posts on shortest distance algorithms and driving distance calculations, will highlight certain basic functionalities within pg routing that I have been playing around with over the past few weeks. I should add that most of this would not have been possible without the help of Anita Graser’s blog, which contains many wonderful posts on the seemingly unlimited capabilities of QGIS!

Pg routing can be downloaded here. Copy the bin, lib and share folders over to your postgres installation folder. Test that it is been installed properly by creating a pg routing enabled database using

 CREATE extension pg_routing 

and then running pgr_version() which should result in details of the pg routing you installed.

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Extracting layers from open street map using osmosis and overpass API

Thanks to the good folk developing Open Street Map (OSM), we have a fantastic mapping resource that is completely free. Coverage is quickly expanding, as well as detail, and its these advancements that provide an opportunity to create gis layers that we would otherwise struggle to find in the public domain.

My first need of this was when I needed a shapefile of all the open/green spaces in london, and after many hours trying to locate this resource without paying a high fee or waiting several weeks, I decided to look into OSM.

OSM contributors provide a tag for every object they map, and this provides the basis for extracting objects of interest.

Firstly, we need some data! Probably the easiest place to collect this is from geofabrik. Here you can download maps at various different geographical scales in both .shp and .osm format. If you want to just extract general attributes e.g. landuse, leisure, natural etc. then downloading the shapefile can provide this straightaway. If you want to go deeper then you will need the .osm file. After the data was collected, I used two different methods to extract data.


Osmosis is a command line interface that allows extraction based on the key:value tag provided by the contributor e.g. landuse would be the main tag, with agriculture being a specific key under that tag. Osmosis can be easily installed on windows with instructions here.

There were two main commands I used to for extraction: Firstly to extract nodes (i.e. any object represented by a point; like a bus stop):

 osmosis --rbf layer_name.osm.pbf -–node-key-value keyValueList=”key.value” -–wx outputfile.osm

Secondly, the following was used for extracting ways (i.e. polygons):

osmosis --read-xml layer_name.osm –-way-key-value keyValueList = “key.value” –-used-node –-wx outputfile.osm

Note: Make sure you are in the directory where your map is stored.

Note 2: When extracting ways (i.e. polygons) you need to use a .osm file as the input. The tool osmconvert can easily convert from pbf to osm.
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