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— urbantick

August 2010 Monthly archive

More and more location data becomes available and makes it possible to visualise the beat of the city over longer periods and/or compressed as a speed up sequence.

Eric Fischer has recently published online a few mappings of online available location data. Most popular were the flickr maps of world cities. This time it is bus movement data through which he visualises San Francisco. The data was collected of the period of one month.

Clip by Eric Fischer / Overlay of Muni vehicle movements for all of June, 2010.
Thanks to Matt for the link via flowingdata.

Visualisation of public transport vehicles in Vienna, Austria put together by Max Kossa on wissenbelasted.com . It is built from a database containing 1048 stops along 44 bus lines, 18 night bus lines and 29 tram lines. Within 24 hours there are some 510.026 total stops for all vehicles.

The different vehicle types are coded in colour. Green are the night buses. This is quite obvious at 01:30. At this time the regular service shuts down and the blue (tram) and red (bus) dots vanish for the rest of the night.

The author has published the scraped data base file for download if you want to have a play.

Clip by Max Kossa /24 hours in the life of the public transport network of Vienna.

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The UrbanDiary project lay dormant for a while after its write up in the CASA working paper 151. However it is back on track with a new set of participants currently tracking their every move. The biggest problem to overcome was the equipment, we simply did not have the recourses to keep it going on a larger scale. Throughout there were two GPS devices in use, but now we have again expanded and twelve GPS loggers are currently used simultaneously.

The area of study this time is not London. The idea is to set up a comparison between two locations. Currently the tracking location is the wider region around and of course in the city of Basel, Switzerland. Earlier posts on Basel can be found HERE and HERE.

It is a region of about 1’000’000 people The tourism office even puts it to 3.5m) and in this sense small compared to London, but in the Swiss context this is rather big. Basel-Stadt (the city of Basle) is the third largest city in Switzerland with 165’000 inhabitants.

TEB Besiedlung und Landschaftsgliederung
Image taken from TEB / The Basel region with green space (unbuilt land), urbanised land (grey) and water (blue). In dark grey is shown the urbanised land until 1960 and in light grey the urbanised land until the year 2000.

Basel is located right at the border to Germany and France. The region therefore covers all three countries. This is represented in the TEB, the ‘Trinationalen Eurodistrict Basel’ (the Three National Euro (not sure what Euro stands for) District Basel). This planing group is working across the borders and is put together from representatives of all three countries. For Basel as the main regional centre these connection sare very important as is the city for the region. In this sense the simbiosis of the different elements (culturally, politically and practical) will be an interesting aspect of the study in terms of spatial analysis.

The mix of participants is again, as was the London sample, a mixed group. It is put together of different age groups, interests and occupations. It will probably not be exactly the same mix, but similar. The idea is to also get some twenty participants in total to have a comparable amount of data.

The data is collected and stored locally on the device and it wil take a while untile we can download the new data and start analys and visualise. So for now this project has to run for about a month until the first data samples will be available. However I do have some very few days of sample tracks that will give an idea of the travel patterns that can be expected in this new location.

Image by urbanTick for UrbanDiary / Preliminary GPS tracking data in the region of Basel, Switzerland. The data is based on three participants over a couple of days, data is unprocessed. THe large C shape in the centre corresponds with the shape of the river in the main urban area in the TEB overview above.

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What if the city would be interactive in the sense of the emerging augmented reality technology? Not that the city is not interactive, but if one would be able to controle many aspects of the environment constantly and from every location? Not that we are not in controle of our lives, but just that there is more that we are aware of.
This time its in HD and 3D – put your glases on!


This is a great clip and goes in line with the previous one Keiichi Matsuda produced at the Bartlett School of Architecture for his thesis.
I very much like the sequence with all the adds and stuff crowding the footpath and swirling away like dry leaves. In the intro scene I guess the possibilities are portrait best. One of the protagonists is waking up, starting the day, changing some options and as the camera zooms out we see he is already in this cafe place. Reminds me very much of those zoom/re-zoom books.

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In out series of tweetography maps the latest addition is the Moscow New City Landscape. And it is now also available as an interactive, zoom and pan-able map using the GMap Image Cutter.
Russia, but mainly Moscow are currently going through an internet boom and in this context twitter has become quite popular. The data we were able to collect using the Steven Grays code of the Tweet-O-Meter was slightly less compared to the very active cities of London and New York. The percentage of geolocated tweets is with almost 12% however higher than those tweet intensive cities.

Moscow New City Landscape

Image by urbanTick using the GMap Image Cutter / Moscow New City Landscape – Use the Google Maps style zoom function in the top right corner to zoom into the map and explore it in detail. Explore areas you know close up and find new locations you have never heard of. Click HERE for a full screen view.

The character of the final map i in comparison to London or also Paris more distributed and includes a number of hot spots. The city seems to be active in a few place simultaneously. This island characteristic however still has a major location centered on around the area of the Kremlin, with the main peak just above the Lenin Library Mettro station. The lines of dispersion sort of indicate te metro lines and follow roughly the stations from the centre to the outskirts. One strong ‘arm’ is going from the centre toward the olympic stadium in the North-East.
There is also a tendency of quite a lot of activity along the main road from Moscow to St. Petersburg, centre towards North-West. The North -West quarter is generally a bit more active than the three others with the South-East being the lowest. This fits roughly with the wealth distribution in Moscow with the South-East being a production area.
Regarding the parks and open spaces, same pattern a previously, no twitter activity. However in this case this is little surprising since parks are very unpopular in Moscow with perceiving them as low safety areas.

This map was produced in the context of the recent workshop at Strelkainstitute. Thanks for the cyrillic translation to Masha. The maps were created using our Tweet-O-Meter, in association with DigitalUrban and coded by Steven Gray, this New City Landscape represents location based twitter activity.

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Do you remember what you did just forty minutes ago, or maybe over lunch or just after you got up this early morning?
Maybe roughly and most likely you could piece it back together using key frames of memory constructing a sort of narrative reaching close to the area in question.

As a sort of extension of the UrbanDiary project, where GPS technology is used to trace the spatial extension of an everyday routine, timeLapse technology is used to frame individual activities and record a massive pool of images documenting an individuals day.

Image by urbanTick for UrbanDiary / Everyday situation recorded with the ViconRevue during the initial trials in August 2010. The perspective is something the viewer has to get used to.

The technology used is a ViconRevue cam. It is based on the Microsoft SensCam discussed in another post. From the distance, not having had the chance to test the device, the impression was not too convincing. However now, having used it for a coupe of days, taken a few thousand snaps, it has to be said that it work really well.

Vicom describes the product everywhere as a memory suport and uses a couple of medical studies where the Revenue is used by patients suffering memory loss, brain injuries or Alzheimer. In the current setting we are focusing on urban and city navigation, differences of activities in a number of spatial configuration. For this we have coupled the camera with a GPS device inorder to trace the spatial movement.


Image by urbanTick for UrbanDiary / Everyday situation recorded with the ViconRevue during the initial trials in August 2010. The available privacy button gives a 4minute time-out, but usually this is over in the very wrong moment.

It does help a bit with the remembering of specific situations. However the perspective is something one has to get use to. It si not exactly the belly button view, but slightly higher. More strange it is the sort of Doom/Quake perspective with one’s own hands constantly in the frame that distracts from the actual activity documented. It is your personal first person shooter perspective.

The installation and managing of the camera and data surprisingly works on a Mac as well as a Windows machine. It uses the Adobe AIR (Adobe Integrated Runtime) technology.
Best surprise was the accessibility of a CSV fiel that actually stores the sensor information for each captured image. The camera uses, in addition to a timer, several sensors to trigger the capturing of an image. This should ensure an image being captured at every change of environment. However, in the accompanying documentation Vicom does not reveal what sort of sensors there are integrated wiht the cam. There is a brightness sensor, maybe a motion sensor? but not sure what else there might be. The CSV file should reveal more details.

Not convincing is the desktop software to review the captured material. Maybe there is less function on the mac version, but even with establishing the various folders the app has difficulties. It did corrupt some of the days and is not willing to show the material unlike for other days where it works perfectly. Handling is tricky and the only option given is a note box either for full albums or individual images. There is not option to sort the images other than by album which is based on time and date.

We will keep working with the as part of the UrbanDiary project in collaboration with the New Scientist. A variety of different participants will contribute glimpses of their everyday lives over the coming weeks. We will keep you posted for update.

Music ‘Ain’t my Night to Drive‘ taken from mp3unsigned by Jennifer Riddle.

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For only three weeks the London Bike Hire Scheme is in operation and so far it seem to be rather well received. The 6,000 Barclays (sponsor) bikes, which have arrived in London are parked at 315 stations dotted across the centre of the capital. An initial map is available through the TfL website.

It give basic infos such as no available bikes and no of available parking spaces. The scheme is based on the concept that people can hire a bike at one station, ride it through the city and park it at another. This means the bikes are in a constant rotation around the city. In this sense both these infors, no of bikes and no of parking spaces, are essential for the functioning and comfort of usage.

As a data source this has obviously inspired data and mapping enthusiasts from different London universities to, on one hand improve on the visualisation and on the other to start analysing the data.
One of the mashup maps is developed by Oliver O’Brien from CASA. The visualisation was already covered by the Londonist, the Telegraph and other blogs such as spatialanalysis.

Image taken from suprageography / Mashup map showing the status of each London Bike Scheme docking station. Yellow border line indicates a station as full, clicking on a dot reviles the bottom left usage graph over the past couple of hours.

It shows the parking locations as dots indicating with a red-blue colour scheme the status of the docking station. In real time one can follow how hundreds of bikes migrate through the city. This is obviously tightly linked to the routines of the bike users and as O’Brien note on the blog seems to be mainly determined by the working pattern. This suggests that a lot of working people in the city are actually switching and using the scheme already for everyday use.

In a graph based visualisation Aidan Slingsby form City University in London is working with the same data, focusing on the trend of usage per station. Each graph compares the current to the previous day.

Image taken from gicentre / Graph visualisation showing the status of each London Bike Scheme docking station. The list is ordered by distance from, as input in the right column.

In a timeLapse copmiled from screenshots O’Brien and Chechire show the dinamics in a 24 hour day of the London Bike Hire Scheme. Quite nice how the dots change the colour over time and viualise the daily migration.


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