Some new data has com in from the GPS tracking project in Basel, Switzerland. Earlier a first group was blogged as 'Urbandiary Comparison Study' where we looked at the region and in 'Stadtraum - UrbanDiary' the focus was on the interaction area between participant and the city.
Image by urbantick for urbanDiary / Basel-Stadt view, plotting all participants GPS track locations. Plotted using cartographica using Bing Maps in the background.
With the new data the focus shifts towards the individual movement in the urban area. This is in a next step also the unit that will be comparable to the existing urbanDiary London data sets.
Image by urbantick for urbanDiary / Grossbaselview, plotting a single participant's locations. Plotted using cartographica using Bing Maps in the background.
Of much interest is of course the temporal structure of the everyday rhythm. The earlier London data was visualised as a graph plotted the number of track points per hour. This represented the amount of activity per each hour in 24 hour day. The resulting graph fitted well with the expected pattern, higlighting the rush hours, the lunch brake as well as elements of weekend activities following a different time structure. Examples HERE and updated HERE.
Image by urbantick for urbanDiary / Distance-Time graph over 24 hours linear single participants. Plotted using DataGraph.
The strategy to visualise the Basel data in a similar graph has been changed a bit in order to create a stronger contextual sense. The Basel graphs are not based on number of track points, but on distance traveled from home. The home location is assumed to be a sort of start and end location in this case.
The graphs therefor trace the ebb and flows of the movement from and to home. On the way different activities paint the patterns and reoccurring activities enforce their pattern.
Image by urbantick for urbanDiary / Distance-Time graph over 24 hours circular single participant. The 24 hours are here visualised around the circle, clockwise, with the distance plotted radial. Plotted using DataGraph and wound in photoshop - cheating I know but I needed a quick fix.
For the working week the distance starts to increase just after seven as participants leave the house to travel to work. Generally the distance then stays more or less the same through out the day, sometimes with a little bit of movement around the lunch time brake. In the evening the distance changes again until it is back to zero as the participants get back home.
However, the evening is compared to the morning a lot less precise. The morning fits across the sample into a timeframe of around one hour. The evenings are more divers and different activities take place opening a timeframe of up to four hours. This will need some more analysis in terms of how this timeframe divides into different activities and how it is structured. Maybe it is dominated by work activities and if there is more work people stay longer or there are groups of after work activities, such as fitness, shopping, socialising, and so on. Together with the interviews and the schedules it should be possible to entangle the structure.
Image by urbantick for urbanDiary / Distance-Time graph over 24 hours circular multiple participants. The 24 hours are here visualised around the circle, clockwise, with the distance plotted radial. Plotted using DataGraph and wound in photoshop - cheating I know but I needed a quick fix.