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Tag "Basel"

This will be some new stuff. Welcome to urbantick’s new home! Yes, it is WordPress, and it has a brand new custom domain – www.urbantick.org also the previously used urbantick.eu domain will still be working ahh.. redirecting here.

It has been in the making for too long, but that doesn’t matter now. It’s back, it’s fresh and its same old stuff.


Walled City Andy young


aerial photography

With this online move, the real home of urbantick is also relocating. It started out at CASA at UCL back in 2008 and had then moved to the IArch at FHNW for a couple of years. Its new home is in Calgary at the Department of Environmental Design. Some might remember the Twitter work on Calgary that we did back in the days.

NCL Calgary

There is a NCL Calgary map and a aNCL visualisation on Vimeo.

There is a host of new topics to be expected, but we’ll keep an eye on the developing issues of urban-related stuff from around the world. There is also a trove of recent research around typology and technology that hasn’t yet found its way onto this platform awaiting publication.


Anyhow, same old, same old let’s plough on. Good read and please comment as you see fit or get in touch.

We have to wait and see…..

  1. Image taken from My Modern Met by Andy Young / Walled City #03, from the series Walled City. Drone footage of urban areas in China. Check out his portfolio here.
  2. Image taken from My Modern Met by Andy Young / Walled City #01, from the series Walled City. Drone footage of urban areas in China.
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How does the social network link location as people communicate? It would be very interesting to see how communication pattern link to location and context.

There is already quite some good stuff on this topic. Only recently John Reads defended successfully his PhD on a topic in this field. He was looking at telecommunication patterns in the South East and London region base on land line connections. He found some interesting patterns of linkages and hubs and was able to identify regions according to dominant trades. Also some landscape features showed up. For example the Thames was acting as a barrier even in the realm of phone call connections.

The TwitterNetworks of London, San Francisco or Munich generated from the NCL datasets are quite interesting where we can see how individuals are connected via interaction on te Twitter plattform using @-tweets and RT-tweets. The networks are built establishing the edges using these two direction indicators. Other networks based on twitter data have been focusing on institutions and text as with the ‘Why Mediate Art‘ project.

Image by urbanTick for NCLn / Circular graph showing the connection between the data sets collected for different urban areas in Switzerland. No connections between them exist, each one operates separate.

Recently the NCL network ha been looking at areas in Switzerland and mapped out the four large urban areas Zuerich, Geneva, Basel and Bern. Overall it is quite visible that Twitter is not as popular as it is in other parts of the world. It is still sort of seen as a time waister and something for nerds. This was aso reflected in the language settings with foreign languages dominating the fields. It seems quite popular with people to keep in touch with other parts of the world.

Switzerland is quite small and the linkages between the cities are well established. This is supported by a perfect public transport network and a wealth of political mechanisms to ensure equality and exchange. However socially of course the different languages to separate different communities. French is spoken in the West, German in central and North and Italian in the South of Switzerland. In the middle of sorts there is the dominating geographical landscape feature, the alps acting as barriers.

This complicated setting of barriers and ties makes Switzerland an interesting study object for social networks. It would be great to see how the different urban areas connect via individuals on social networking platforms.

Regarding our Twitter data we have two data sources. One is the individual records for each urban area over the period of one week, the other is a week long record of location based tweets sent across the whole of Switzerland including the south of Germany and the north of Italy with Milan.

Image by urbanTick for NCLn / Showing the social connections as found on Twitter within Switzerland. Data based on a location based Twitter record over the period of one week.
The alps in the centre act as barrier with only a few connections crossing them, either via a celebrity Twitter account, in this case Justin Biber and Jessica Alba or physical travel.

Looking at the first data set with individual records for each urban area, the networks separate out each city with no established connections between them. It was sort of expected, since the sample is small and the parameters are tight with only location based tweets.

Looking at the second dataset where the whole area was simultaneously recorded the big barriers show up clearly and there is a well established separation between North and South showing the alps as mountainous Twitter blockers. Interesting however, are especially the links across this barrier and there are some. Three links connect the norther part consisting of Geneva, Basel, Bern, Zuerich and southern Germany with the southern part consisting of Milan, Como and Turin. They represent different types.

The first type is the link via a common third party that is not necessarily in the area. This is most likely a very active and popular twitter acount. In this case there are three celebrities that establish the connections. They are Justin Biber, Jessica Alba and some guy Kenny Hamilton. These are the hubs that individual Twitter users from both sides of the mountains tweet at and establish a sort of second grade connection.

There is also the other type of first hand connections. this is established by an individua traveling around and tweeting both to connections in Milan, the southern part and users in Zuerich, the northern part. The fact that the individual has actually physically traveled between the two parts enforces these connections.

Image by urbanTick for NCLn / Switzerland with the locations of recorded tweets. This has been collected over a period of one week. The purple line shows the route travels by one individual users tweeting along the way and interacting with other user from both sides of the mountainous barrier.

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Basel, the city at the ‘Rheinknie’, marks the northern gateway to Switzerland. The ‘Dreiländereck’ (three country corner) is an important fix point in the port of Basel, where the borderlines of France, Germany and Switzerland touch. The resulting ‘trinational’ region with Basel as the largest hub has established its own culture and functions across borders both culturally and economically.

Basel is the largest city in this area with Mulhouse and St. Louis being the French and the German main city respectively. Basel offers a lot of work places for about 100’000 cross border commuters. A connecting feature throughout the region is the river Rhine. It marks the North-Eastern border of Switzerland coming from the ‘Bodensee’. In Basel this important landscape bends North, leaving Switzerland and continues to mark the boarder between France and Germany.

Right at this bend is where the Basel hub is located and obviously the river has historically been a very important source of identity and still continues to be. A lot of activity is happening along the waterline and this is then also reflected in the twitter map. The New City Landscape to some extend reflects the river and it can be read how it trails from the East side into the city and sharply turns North exiting between the French-German ‘gate’ at the Northern end of the NCL map.

Basel New City Landscape
Map by urbanTick for NCL / Basel New City Landscape map generated from location based tweets collected over the period of one week. The area covered is within a 30 km radius of Basel.

With a population of 166’173 residence it is in the international context a very small centre. Economically it is however rather important as a banking hub and is the home to very large international pharmaceutical companies such as Novartis and Roche. Nevertheless, the countryside around the city is completely missing from the NCL map. There are very little activity on twitter. The distinction between city and countryside in Switzerland is no loger very dramatic, since most of the rural landscape is urbanised to a high degree. The covered area of the NCL map must be the home to about 800’000 the twitter activity clusters on the city of Basel.

Basel New City Landscape
Image by Wladyslaw taken from Wikimedia / “Panorama Basel vom Martinsturm des Basler Münsters aus” (Panoramic view from one of the towers of the Basel Münster, with the Rhine bend and the Messeturm in the focus.

The highest point is the ‘Münsterstock’ probably the very most central location of the city, a hill overlooking the river Rhine right at the bend with the Basle Münster, a very attractive Church. From this central location the twitter activity trails out along the main infrastructure axis, Rhine, public transport along tram no 10, no 11 and no 6 as well as along the Motorway A2 and A3.

Basel New City Landscape

Image by urbanTick using the GMap Image Cutter / Basel 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 maps were created using our CASA Tweet-O-Meter, in association with DigitalUrban and coded by Steven Gray, this New City Landscape represents location based twitter activity.

In terms of time of day twitter is active, Basel has strong morning and evening peaks. Also lunch is a time for tweetig as most people leave the work place for a lunch brake. The evening peak is very consistent between eight and ten, but then drops of rather quickly and stays very ow until it picks up the next morning around seven, the start of the next working day.

The language top three is Germa, English and French. Where English dominated the top ten in Zuerich, has Basel, with its proximity to Germany a very different position. However rank two reflects the importance of the international ties.

Basel NCL timeRose
Image by urbanTick for NCL / The rose shows the twitter activity over the tweet activity per hour of the day, starting at 00:00 at the top. Here we are showing Basel local time. Hence the characteristic dip between three and five o’clock in the morning. Basel is a morning and afternoon city with more activity around start and end of the work day. The graphs show the platform of preference used to send the tweet and the language set respectively.

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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.

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The data collection in Basel is well under way and the second series of participants are now collecting data for the study. For ten people we already have a complete set of two month of tracking data using the new GPS trackers.

There are a number of very interesting observations that has been made also in comparison with the previous study undertaken in London. The scale differences are striking what is a regular commute is completely different. It might be on average one hour for Londoner, but is probably stretched for Basler if it is thirty minutes. As a consequence work and leisure journeys do tend to much more similar in Basel than in London where certain trips have a stronger specification.
However there are a lot of similarities too. Foremost the extension of the direct and persistent interaction in the urban realm is very much directed and selective. There is in both cases a strong local activity around the ‘known’ territory.

The study was also presented to representatives of the Basel Department of Town Planning who were interested to hear about the research undertaken. A summary of the presentation can be previewed below, it is in German though, but there are enough images to illustrate and communicate.

Essentially it explains the method and uses illustration taken from all three sample studies in London, Plymouth and London. The Basel data is still in development so only some preliminary information could be provided. However the maps ‘drawn’ by the participants using the GPS, beautifully illustrate the focus each individual puts on the city.

Image by urbanTick / Visualisation of GPS tracked movement in Basel, Switzerland. The nine different individuals have been tracked over a longer period and it beautifully shows the individual focus on the city that is developed.

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I gave a talk today at ARUP London about my research on cycles and rhythms in the city.
The talk was titled Shaping Cities, from the body rhythm to urban morphology. With this title, it brings together the different aspects of scale in the research, ranging from natural body functions to patterns of movement in the city.
Along this key terms such as memory, identity, time and orientation are explored and visualized with examples from the work featuring on this blog, ranging from PLY365 to UrbanDiary.


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What is now possible is to compare three different cities. I have a track record from Plymouth, Basle and London.
The following three screenshots are taken from Google Earth at an altitude of 9km. So they are comparable in scale.
What they all have in common is the fix points. The main structural elements of how my days work in terms of space and time are the same. Leaving home going to the same workplace everyday and returning back home. Between those fix points there build up quite intense tracks lines. This base layer get extended by some secondary points, e.g. location for the weekly shopping, favorite spots, friends location, … The third element are the trips. Journeys that are usually going out of the daily routine to a further destination or just a stroll. They occur characteristically on days off or weekends. Depending on how familiar I am with the surrounding they are more focused or of more explorative nature.

Image by urbanTick – Plymouth

Image by urbanTick – Basel

Image by urbanTick – London

Interesting is to compare how I respond to the urban surrounding. The three cities have very distinct urban patterns from one another. Take Plymouth, a city completely planned almost from scratch after it was destroyed in the Second World War. The planner was Patrick Abercrombie who also presented ideas for the reconstruction or better new construction of London after the Blitz. Basel on the other hand is a similar size city in a very different setting with its growth patterns structuring very much its appearance. Or London as the third example, the world city with its single centre core.
To explore how those characteristics influence my interaction with the built environment in terms of routs I choose I overlay my tracks onto maps that capture the characteristics of the three cities.

Image by urbanTick – Plymouth Abercrombie Plan with Plymouth 365 track overlay

Surprisingly, or maybe not so surprisingly, the tracks redraw quite exactly the characteristics of the Abercrombie Plan.

Image by urbanTick – Basel city center with track overlay

Note area A (dark brown) is the old medieval town surrounded by walls dated ca 1860. Area B (beige) is the extension, ca 1875,but still surrounded by a wall. Area C is the extension of the city ca 1926, but is also mainly the present extend. It is important to know that after the walls have been demolished, the freed up space has been used for major infrastructure placements such as roads, but also as open spaces. This means that additionally to the link roads that from the centre outwards there is also a no of ring roads (on the ground of the former walls) that tie in very well with the rest of the network. Moving radial is quite simply in therefore and the use of it is represented in through the no of tracks. Compared to this in London it’s quite tricky to travel radial as it has a strong centralized structure, roads mainly leading into or out of the city centre.
This then is represented in the London track log. It is strongly linear and this represents exactly this centrality as the line is pointing towards the centre.
So now guess which track log is which city.

Images by urbanTick – track record line drawings

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For a three month period I tracked my journey while living in Basel, Switzerland. In this example the modes of transport are bicycle, bus, tram and as a pedestrian. There are a number of lines leaving the image down in to the rest of Switzerland towards north is Germany and west is France). This is probably down to the fact that Basel as a city is quite small compared to Plymouth or London. An other aspect, especially compared to Plymouth is that the public transport is very good. Even though one does not have a car, it is simple and quick to go somewhere, this probably motivates to make trips to other places.​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​ ​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​
The pattern that usually shows where I live and where I work appears surprisingly less obvious that expected. The knot where I lived is somehow visible, but apart from this is rather unclear.
Strong lines also appear along the train line Basel-Olten and there is a strongly visible mark leading towards the Laufental.
Image by urbanTick – The straight lines occur where the GPS device had a weak satellite connection

The following are notes just after I recorded the tracks in 2007-02-15.
“…it is again the graph with the plotted tracks that show how I move around the city. The pattern stayed the same it became just denser. I stopped this record at the end of the year. So I do have now three month of records, guess that’s enough as there is no changes in sight for the near future.
The pattern develops around a few hotspots and connects them within and with some points of interest or necessity.
As it is basically a movement pattern and not an activity pattern there is not much to find about my acting in the city. It is talking about the city structure and tells the story of how one can move about this particular area. Maybe more interesting is what I do in between. One could say this is closer to some kind of space-syntax research, but maybe in terms of how activities are structuring the movement within the settlement this is not very useful. It is too close to the physical reality to tell a richer story.
There is a lot of information missing. For example it would be very interesting to actually see where and how long I stopped somewhere. There are brakes in between the lines, at my workplace, where I go for lunch… these events could tell a totally different story. It is actually recorded in most of the daily data on the GPS device, I just do not know how to visualize this…!
I am already working for a few months with this device and I am still impressed by the output. The drawing shown is very simple but it visualizes very clear how much of the city structure I actually know, in terms of physically experienced, and how much I have left out. But still, I would claim to know the city as a whole. Despite the fact I haven’t seen large areas I create a mental image of the city and its network of connections. …”

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