Pedro M Cruz has updated his work on the Lisboa traffic visualisation. His earlier visualisation, part of his Master Thesis, featured here and on many other blogs back in April 2010.
The visualisations are built in processing using different models. The data represented traffic on the roads of Lisbon recorded over the period of one month.
About his new version Cruz sais: "the traffic of Lisbon is portrayed exploring metaphors of living organisms with circulatory problems. Rather than being an aesthetic essay or a set of decorative artifacts, my approach focuses on synthesizing and conveying meaning through data portrayal".
His new attempt is clearly chalenging to some extend slowly settling standards in the field of visualisation. Those being the attempt to visualise everything as is and as much of it as possible. Traditional techniques of abstraction, simplification or focus, what ever you would like to call it, are ignored and rendered away using sheer computing power.
The system used here is developed having some rough biology concepts in mind, images of blood vessels. Cruze explains: "the thickness, the color and the length of the vessels are excited by the number of vehicles and average velocity in each road".
Image taken from mondeguinho.com / The road network of Lisbon was queried from OpenSreetMap, parsed and filtered. Using this information, a spring based physics system is build for the road network and a filling structure of each vessel. The data is overlaid on the resultant structure to determine the road where each vehicle is at a given moment. This allows to inject data at runtime and excite the system.
This has a dramatic effect for the representation of the geometry and alters the appearance of the whole system. Nevertheless since the visualisation is reduced to the road as the single feature this is not producing any complication, on the contrary the system starts to become readable.
Especially interesting in this visualisation is the built in time-distance representation. The basic idea of that if a connection is fast it is short and if it is slow it becomes longer. This is as if saying time = distance (length). This is of course a very abstract and dangerous thing to propose, but in this case it produces some interesting results, since one all of a sudden is reading a visualisation roughly to its location in regards of how long it takes. As Cruz points out his is connecting the local and the global features of this representation and in this sense take it a step forward. Details on his blog.