As announced a while ago, I went to GIS Day in Zurich, Switzerland.
On my employer’s blog, I have written up a review of the event in German. Head over to find out about interesting Switzerland-based GIS projects (in-browser-translation should be fine to get the gist, I suppose).
Swiss air rescue organisation Rega uses GIS for emergency dispatching
Hot from the press: Esri announces the acquisition of Procedural. The Switzerland-based company specialises in procedurally (i.e., rule-based) constructed 3D city models and is known, for example, for its reconstruction of ancient Rome. Procedural’s approach, embodied in its software CityEngine, allows for very fast modelling of urban scenes.
Esri’s move will considerably strengthen its stand in the 3D realm and maybe we will at some point see BIM (Building Information Modelling) by Esri? Spatial Sustain points out correctly that Esri hasn’t usually grown by acquisitions, but steadily by its own activities. Before that background, Esri’s move into 3D via Procedural seems rather outstanding and meaningful!
Head past the break for some rather captivating examples of Procedural’s products. Continue reading
Over on his blog, Bill Dollins muses about the range and ubiquity of the Python language in the geospatial realm.
It’s true – if you work with ESRI products on a daily basis (like I do) you almost can’t get away without using Python one way or the other, be it for scripting some workflow, writing some standalone programme with or without using ESRI’s arcpy or implementing advanced Field Calculations in ArcGIS. The most important upside about the ubiquity of Python to me is the availability of great packages. In my work I have for example used such diverse packages as EXIF.py for manipulating EXIF data in images (think extraction of geocoding information from photos), suds for accessing SOAP services and Numpy for handling computations in, and manipulations of, rasters.
Very recently I tested map production automation in ArcGIS using the arcpy.mapping package. Part of the task encompassed automatically adapting the map title in accordance with changing map content. The title was put into a relatively small text box and I had thus to find a way to make sure that both a string of say ten characters as well as 25 characters could fit in the space. After some digging I came across a nice package called PyHyphen which I could include into my script for hyphenating the title string and thus perfectly solving my problem. It even came with a German dictionary which handled names of Swiss municipalities well!
Also very recently, I finished a study on the threat nuclear power stations present to people living in their (more or less immediate) environment. The geospatial part of that study was – except for a small bit of the open source statistics software R thrown in there – completely done in Python. And if I had already been aware of rpy which Bill mentions in his post, I might have been able to pull off the entire analysis in Python.
I think Python is here to stay for a while. In the geospatial realm which works with ESRI it has always been clear that Python is the next thing after AML and VBA/ArcObjects. But it’s very good to see that Python in fact has a much broader base than just the ESRI products in the geospatial realm and certainly beyond that. And I also really like that it runs on my Ubuntu desktop as well.