Carson Farmer

For part of a traffic simulation project I am currently working on we need country-wide road network data for Ireland. In the past, getting decent road network data for an area this large was quite a task (not to mention expensive and time consuming), however, with OpenStreetMap we have access to this type of data instantly, and for free! In order to download full country coverage all at once, all I had to do was turn to this extremely useful site, which provides links for daily excerpts of OpenStreetMap data for any country in Europe plus several non-country regions such as the Alps region, as well as select countries outside of Europe. It currently also features special coverage of Haiti.

Now that I have the OSM data downloaded, it should be relatively easy to import it into my PostGIS database using pgRouting and the osm2pgrouting import tool. More to come on this topic once I get things working nicely…

Carson

Several colleagues of mine have asked whether it is possible to visualise the results of a SELECT statement on a PostGIS database that returns spatial data in QGIS. In other words, can we map the results of something like SELECT id, st_union(the_geom) FROM spatial_table GROUP BY id;. My usual answer to this in the past has been “not yet…”, but now thanks to Giuseppe Sucameli and Jürgen E. Fischer, the answer is a resounding “yes!”. A recent patch to QGIS trunk now makes custom Postgres queries possible via the postgres data provider.

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Last week I attended the 2009 QGIS Developers Meeting in Vienna, Austria. We all had a really good time, met many new people, and actually got a lot done in the process. There have been updates about the meeting (hackfest) on the QGIS blog, and Tim Sutton has written a few words about our progress as well. I’m not going to repeat what others have said, but I would like to give a quick update on the work that I was doing at the meeting, and show off the new geoprocessing features now available to all QGIS developers (Python and C++).
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Many natural and human systems can be represented as networks, including the Internet, social interactions, food webs, and transportation and communication flows. One thing that these types of networks have in common, is that they can each be represented as a series of vertices (or nodes) and edges (or links). This blog entry presents a nice description of networks, highlighting the differences between various network types (directed, undirected, weighted, unweighted, etc.).
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To create a nice bounded Voronoi polygons tessellation of a point layer in R, we need two libraries: sp and deldir. The following function takes a SpatialPointsDataFrame as input, and returns a SpatialPolygonsDataFrame that represents the Voronoi tessellation of the input point layer.
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One project I’m working on at the moment involves exploring a dynamic extension of the Isomap algorithm for visualising constantly varying real-world road networks. Currently, we are testing out the method on a small scale simulated road network, and most of the original code (written by Laurens van der Maaten, with updates by Alexei Pozdnoukhov), was done in Matlab. Since this work is eventually going to have to run on relatively large datasets, and probably behind the scenes on a server somewhere, we decided that Python was the way to go. The goal therefore was to reproduce the Matlab code using only Python libraries, and the fewer additional libraries required, the better.
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The other day I was loading a shapefile of approximately 11 million records into a PostGIS database (stay tuned for more on that later) and I wanted to know when shp2pgsql was done. Instead of continually checking the console, I decided to ‘watch’ the process using the *nix command watch. I discovered this handy tool a while ago, and have found that for long running processes, I can use watch to notify me when the process has finished, using the following command:

watch -ben 1 "ps u -C shp2pgsql"
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A few months ago I decided to add syntax highlighting capabilities to a piece of software that I have been working on. Since it is a PyQt based application, the obvious choice for implementing syntax highlighting was to use Qt’s QSyntaxHighlighter. Unfortunately, there weren’t many examples around that implemented syntax highlighting in Python, so I decided to post my own.
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For those of you who are still unclear about what exactly a spatial reference system is, how it is used, and what it means for your data, I found a pretty good quick guide to spatial references, coordinate systems, projections, datums and ellipsoids. This article was written by Morten Nielsen (who works for ESRI), and it does a good job of quickly and simply describing what makes up a spatial reference system, and some of the errors that people make when talking about their spatial data.

Having a good grasp of this stuff is important when working with spatial data, so guides like the one above should really only be used as a quick reference to more in-depth material covering these concepts. Check out the links below if you want to learn a little bit more:
An ESRI overview of map projections
spatialreference.org/
Carlos A. Furuti’s Map Projection Pages
Knippers, R.A. - Map projections

C

Out of the box gedit is a basic text editor, but it comes equipped with about 12 standard plugins, and another 9 readily available. In addition to this, there are a range of ‘third-party’ plugins developed to do various specific tasks, such as assist you in writing and exporting LaTeX documents!
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