Last year, for my University Master’s project, I completed a project which explored the potential of combining time with maps. The basic concept was to build dynamic maps, based on the user’s frame of reference, which would adapt to describe journey time to different locations on the map. The primary method I considered for implementing this was the isochrone - which is essentially a contour which traces a boundary beyond which you cannot cross in less than a given time period. For my implementation I focussed on their usage in describing the status of the London Underground network. See here for a detailed overview of the project, and here for the full project report.
During the development of the project, a lot of discussion was sparked when Oskar Karlin released his Master’s project looking at isochrones on the Underground on the Internet. Tom Carden followed this up with an applet implementation using Processing, and then mySociety created an isochronal map for Britain as a whole. The flurry of activity proved that the concept has potential, and I expect a resurgence to appear as the GeoWeb continues to develop. I did look into the potential for improving my software, and taking it to either KaZoom (who do Transport For London’s web software), or one of the advertising agencies, but I haven’t been able to find the time the project would require. If people are interested in the code, then I may still be persuadable to Open Source it.
Working on the project led me to develop ideas further around the concept of relating points in space to the “cost” of travelling there. I think that there is potential to apply this concept to a much more complex set of variables than just time, such as the financial impact, or “value” to the user in reaching that location. I’m particularly interested in the application of this idea to relief situations, where decisions have to be made very quickly on limited knowledge. For example, after the Tsunami, information such as availability of transport and resources could be combined with risk and need to generate a heat map describing where best to set up camps and food distribution points. Implementations may be crude, but they could certainly help in describing the overall picture of a complex situation quickly to relief workers. In all likelihood this already exists, or at least I hope something like it does!