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Tag "tracking"

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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Today is RGS day, actually RGS has been on since Tuesday this week. RGS is the Royal Geographical Society: ‘We are the learned society and professional body for geography’. The annual conference of course is a big event, prestigious and well attended we hope. THe official twitter tag for this conference is #RGSIBG10. So look out for this to follow the latest news on the day.

I will be presenting a paper in the session 143 organised by James Cheshire from spatialanlaysis. The session title is: Postgraduate Session: Analysing and Visualizing Social Change

THe paper I will be presenting is on aspects of routine migration in the city, the daily migration from home to work and changes in location on short term. I will be using both, the study using GPS to trace individuals in urban areas as well as the more recent twitter mined data with the New City Landscapes to illustrate these aspects. Important key elements will be time obviously, but also a number of aspects of repetition, memory and the creation of identity. There will also be a focus on visualisation using the Hagerstrand time-space aquarium.

The abstract of the paper:
The research project investigates temporal spatial patterns of citizens. For the study we are using GPS technology to track participants over a longer period to record repetitive activities. The collected data, through the GPS has a timestamp and a location, serves well this purpose. However the challenge is the visualisation and the interpretation of the data. To approach this problem the ‘technical’ GPS data is complemented with individual information collected through interviews and mental maps. This set of data helps to create a context, in which the aspects of temporal experience can be studied as an additional dimension to urban life. Visualisation concentrates on time budget in the spatial context taking location features into account as part of the memory as well as the creation of identity. For visualisation purposes a number of approaches are used, from time-space aquariums to animations.

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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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A Google Maps mash-up has gone online that visualises the approximate location of every single tube train on the London Tube network. This has become possible since TfL’s move to install an open API allowing access to their vast pool of data. Through this the map calculates real time location of trains by accessing the data from departure information board. This is the same information passengers see on the platform. The very familiar 7 minutes, 3 minutes, 1 minute, due, writing in orange dot letters.
The API is currently still in beta and provided through the LondonDataStore.
This comes only a few days after the publishing of the API and it was developed by Matthew Somerville via mySociety. The source code for the mash-up is also available. It was developed in the context of the science hack day that took place over the past weekend.
This is great to look at, but like the information on the tube platform, we know from experience that the time displayed usually is just an approximation.
In an earlier post the beat of the london tube network was covered in a different visualisation type, using timeLapse.

Image by wired.co.uk / Screenshot of the live tube map
Image by wired.co.uk / Screenshot of the live tube map

Thanks for the link to Duncan.

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The Football World Cup virus has of course spread to all the mobile platforms, foremost the iPhone and iPad. Numerous apps promis the most up to date info and the most detailed analysis. In an earlier post I was interested in tracking of activity on the football pitch and came across these different methods of analysis. The big sports broadcaster are using a palett of software helping them with analysis as well as visualisation. The visualisation part has become important during these very formal and serious debates around the table. Usually the graphics put in to the video are based on tracking information derived from different cameras. There aren’t currently physical tracking technologies in place, as for example RFID, GPS or Bluetooth. The producers must be very satisfied with the visual tracking tools. Tools are Piero, Visual Sports. A nice visualisation of pitch activity also is supplied by the New York Times including time slider allowing you to scroll through the 90 minutes dynamically.

Image by urbanTick / Screen shot taken from Total Football 2010 iPhone app, analysis of the game Switzerland 1-0 Spain, all passes.

If you are keen to get up to date information on matches and analysis where ever you go and where ever you are, you need a app fot the iPhone or your new iPad. A really cool on eis the Total Football 2010 developed by Colm McMullan. It provides you with all the details and infos you want to know. I was particularly interested in the visualisation of spatial activity on the pitch. How do players stand and where is the action taking place. Here you can get detailed info down to which player took a throw in where, when, in which direction and how far – Amazing! With the dynamic slider all the information can be specifically focused on a specific period of the game or over the whole 90 min period.

Image by urbanTick / Screen shot taken from Total Football 2010 iPhone app, analysis of the game Switzerland 1-0 Spain, all passes in the attack third.

In te context of the game Switzerland Spain, the analysis of the spatial pattern are telling a lot about the narrative of the game. If you look at the spatial distribution of the passes by Spain that covers two third of the pitch towards the opposition goal witha strong focus around the Swiss box. The Swiss passes on the other hand got stuck in the center of the field with a high percentage of red, meaning failed passes.
The Swiss goal that decided the match was a real surprise just a few minutes into the second half. It was one of the long balls in to the Spanish half surprising the Spanish defence and muddling the ball in to to the net.
The strategy of the Swiss team to focus on closing the box with every player and simply not letting the Spanish side get to have a got at the net worked out and left this clear spatial pattern of a maximum of activity just outside the Swiss box.

Image by urbanTick / Screen shot taken from Total Football 2010 iPhone app, analysis of the game Switzerland 1-0 Spain, all shots.

The data feed comes through a service from Opta Sports. They are using a specifically developed software to analyse the games. However surprisingly it is all done manually. Two people are watching a football game. Each one focuses on one team and records every single move. The actions are coded and the operator also registers with the mouse the location and direction on the pitch via visual input. Basically this way they record the ball movement. It could be summarised as a linear recording of the balls movement over 90 minutes.

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World cup is on and I even find my self occasionally following a game with some pretended interest. What I am more interested really is the movement and the strategies. There is not much space and most of the points of orientation are moving elements. However rough positions are allocated together with assigned tasks.
There is a lot of important talking about options and chances, tactics and plans. It sounds all very sophisticated and important. But what is it in the end, 23 guys chasing the ball.
This however is random enough to generate some distinct pattern. of course random in this context means the characteristic mixture of task oriented inventive behaviour as we also observe it in everyday movement. In a very interesting blogpost Rob from Mammoth has summarised his thoughts on the similarities between football and urban movement tactics – as diagram traced on exported landscape.

Image by urbanTick /Adidas’ Match Tracker, the heath map view – game Chelsea vs International.

Analysis of the game in real time is this year available from multiple sources. Addis offers the ‘match tracker‘ or you can check out visualsports.com. The adidas tool offers a graphic replay feature that based on a movement record. It has a quite elaborated interface with an interactive time tracker below.
A very different approach took the artist David Marsh with his work ‘Some People are on the Pitch‘. He traced with pen and paper the movement of the players in the 1966 victory, the last time England won the World Cup. He also offers the selection of some particular traces, though. For example one plate is the movement of Martin Peters in the first half of the game, another is Charlton vs Beckenbauer over the full length of the match.
It is ‘Created by mapping archive footage at 1/2 real speed, using the pitch markings and the stripes of the cut grass as a coordinate system, the work follows the movement of each player against time, on and off the ball, as they move across the ‘field’ of play throughout the full 90 minutes, plus extra time.
The recorded information is then coded through a system of line type, weight and colour to allow the narrative of the recorded information to be represented and read graphically, producing a work simultaneously latent with an immense level of information, and one seemingly abstract in its aesthetic.’

some people are on the pitch by David Marsh

Image by David Marsh / ‘Alan Ball – Full Mach’ Working drawing, Ink on trace.

Details via Mammoth and Infostetics. Other football drawings can be found via SwissMiss.

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It is really something that is the aesthetic of the time. Thin black endless wiggly lines on an abstract white background, densifying here, loosening up here only to cuddle in an other heap of completely tangled up strings over her. These abstract patterns are visually fascinating, but why this is, I am not sure. One thing is the abstraction from an obvious continuos activity of some sort, the presence of an invisible repetition, of which one is sure must be there and the forming pattern of density and mess.
We have, over the last two, three years learned to recognise these sort of drawings as movement line. Movement of people and animals perhaps, but movement lines quite different from other movement paths previously visualised such as the path of the sun or planets, the movement of shadows or water. It contains the aspects of immediate and real-time decision on the spot, the reaction to a range of influences from large scale, distant events, to the immediate surrounding and interactions with other static or moving objects. It represents in this sense a process as a string of events that were actively dealt with. This aspect of process or in this context better ‘creation’ – in the sense of creating as you go along, of individual actions influenced by background, experience and personality – is a unique characteristic that usually is either underestimated and erase-simplified or over estimated by putting it as random. What exactly is its role in a denser aggregated context?

Image by urbanTick / Movement tracking over the period of 1.9 hours working in the evening on some posts and mapping tasks. The activity is captured as curser positions using the software IOGraphica.

The visualisation here, come very close to what has been described above, but actually it does not represent any physical movement, it is a simple track map of the curser activity on the computer screen. There are similarities, however the context is extremely confined and designed to work and relate in a specific way. Nevertheless it produces visually interesting images. And if your bored and dont have time to go for a walk, a stole and drift thought the city, let you mouse curser do it for you. The too is called IOGraphica was deveoped by Anatoly Zenkov and Andrey Shipilov and is currently available in v0.9. A tool to run in the background and track you workday at the desk. One started it records each location of the curser as well as the duration, draws lines between them and upon request visualises the time spent per location as growing black dots. Only a few options available but nicely presented.
Download from HERE. See some more visuals on flickr.

Thanks to Paul M. fo the link

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Physicist Albert-László Barabási, well known for his work on network theory, has tuned his attention in a recent paper to the human movement. In the latest issue of Science 19 February 2010
Vol 327, Issue 5968, his paper ‘Limits of Predictability in Human Mobility‘ reports the research work undertaken with 50’000 anonymized mobile phone user data.
Barabási has don a lot of work on networks as early as 1999 were he coined the term Scale Free Networks, describing a type of networks with major hubs, such as for example the world wide web. In his barabasilab at Northeastern University, Centre for Complex Network Research a number of network related project are researched.

Image taken from The University of Chicago / Diagram of a scale-free network that contains components with a highly diverse level of connectivity. Some components form highly interconnected hubs, while other components have few connections, and there are many levels of interconnectivity in between.

However in this recent work the focus is on the predictability of human movement. The authors say: “By measuring the entropy of each individual’s trajectory, we find a 93% potential predictability in user mobility across the whole base. Despite the significant differences in the travel patterns, we find a remarkable lack of variability.” The work was intended to close a gap in the approaches to modeling human behavior. Despite personally we rarely perceive our actions as random, the existing models are largely based on the factors of random movement. The paper demonstrated that even though the activities, distances and motivations for individual movement might be very divers and different the predictability of an individuals location is not. They all have very similar predictability values, ranging between 80 % and 92 %. AOL News titles their article on the work “Study Makes It Official: People Are So Predictable” implying that this must be soooo boring.

Image taken from AOL News / These diagrams represent the movements of two mobile phone users. The one on the left shows that the person moved between 22 different cell towers during a three-month period, and placed 52 percent of his calls from one area; the other subject hit 76 spots, and was much less rooted.

This might be very surprising news for most people. The fact that there is so much less changing and spontaneity might seem unrealistic, but a similar impression was given by the data collected with the UrbanDiary project last year. Even though this was a really small sample, the fact that individuals travel most of the time along their known routes, between only a few hot spots clearly emerged. This can also be seen visualised in the What Shape are You? renders. Also Hagerstand’s work pointed in to this direction arguing that the ‘Constraints’ are too strong for too many out of rhythm activities.
Barabási already undertook similar work with mobile phone data in 2008, which war published as an article in nature, by Gonzalez MC, Hidalgo CA, Barabasi A-L. with the title ‘Understanding individual human mobility patterns’. In this article they analysed data of 100’000 mobile phones. Was the media coverage back then (two years) very much concerned about privacy issues related to the data source, for example NYTimes is this less of an issue. Nevertheless it is obvious that the researchers try to play it save by mentioning about ten times in the article that they work with anonymized data.
The argument is largely the same in both articles and the finding too. In both papers the researchers show their surprise about the outcome, that the movement can be predicted. However to my surprise they stick to their study and do not draw any strong links to routines and rhythms of personal habits. You can listen to a podcast where Barabási talks about this research.
In the more recent paper they conclude “At a more fundamental level, they also indicate that, despite our deep-rooted desire for change and spontaneity, our daily mobility is, in fact, characterized by a deep-rooted regularity.”
I believe that the former, spontaneity, is very much a cultural phenomenon similar to the urge to stay young. The later, regularity, is the provider of identity and orientation resulting in stability and safety and therefor fundamental to human everyday life. Interesting should be Barabási’s upcomming new book Burst on “The Hidden Patterns Behind Everything We Do”.

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We have been logging Twitter activities in the London area (M25) over an earlier weekend in January with some code Steven Gray has put together. The idea was to log the location based traffic and see what the mapping of it would bring. There are a number of twitter mapping projects out there already, for example twittermap.tv from where the timeLapse of the weekend activity was captured HERE, or the first big mapping project twittervision.com. However, we wanted to focus on a local region, a city, to see what the traffic is and how the location might play a role. The traffic visualisation page tweeTOMeter is part of this interest.

Image by UrbanTick / Screenshot of Twitter data visualised in GeoTime’s space-time aquarium.

One could think of this investigation as following the urban story quite literally, while following the tweets of citizens. However it is quite tricky to make sense of it all. The dataset for the weekend, which covers Friday evening to Monday morning contains some 300’000 tweets. Not all of them are properly geo referenced. Only 1’700 have actual Lat/Long information in the geo tag field. Furthermore some 60’000 have Lat/Long details in their profile tag field and the ret only has a generic profile location, such as London. This probably is because of the relatively new geo support of the Twitter API. Most users still seem to have little interest to include their actual location, as well as a lot of the applications do not yet properly support the format. Interesting seems to be the network. Whom are tweets directed at? It seems to be quite a high average of direct tweets, almost 3 per message. Also who will actually read it, how many followers are there in average?
Working with the real geo referenced tweets, surprisingly they contain quite a bit of movement.
For a quick look at the data it has been visualised in GeoTime. The representation in the time-space aquarium makes the diagonal lines, that suggest movement, very distinguishable from the vertical stationary lines. While looking at the replay in the 2D view the weekend really comes to life and London gets busy.

Similar visualisation, with snippets and names, but without the river Thames, can be fund HERE.
GeoTime here really offers a powerful and very quick way of visualising the data in space and time and offers a whole pallet of different visualisation types, each including a set of tools for analysis and manipulation. Import comes either via ARCGIS or even quicker excel.
The main problem really is the quality of the graphics, the design of the result. Here the user has hardly any choice or possibilities to manipulate anything from colour palette to line style or font. This is a bit annoying especially because the tool is kind of an end of the line analysis tool, after you have prepared the data elsewhere.
The second quick one goes into Google Earth obviously. Here the data again comes from a simple excel spread sheet with a VB macro to write the KML file. This literally takes 5 seconds to do and you have a KML file, including time tags in Google Earth.
This one only plays the locations though, also in a time window of some six hours.

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Are you someone who would just bag a nice object found on the street and take it home? I certainly am and I have a large collection of ‘objet truve’ at home. I am not talking about steeling things, but reusing things that someone else has left behind or doesn’t want any longer. This is apparently called curb-mining.
Secondhand objects have somehow a special charm to them, marks of usage often add to the appearance and make them appear beloved and therefore valuable. It’s amazing what can be found. However in this example here, the object were left out intentionally for people to take home with a commercial idea in mind.

Images taken from clip by BluDot

The furniture and design company BluDot created a publicity stunt to mark the first anniversary of their NY Soho store late last year. Together with mono they created ‘the Blue Dot Real Good Exeriment’. For this they placed 24 of their chairs, product, Real Good’, on the streets of NY and tracked them as people decided to take them home. The public could follow the project on line and witness how the chairs traveled through NY. For some of the tacking GPS was used. They have modified basic GPS devices to fit underneath the seat of the chair. With its sleek thin design this was not an easy task. They even fitted it with an special activation switch, turning the GS device on as the chair is moved by the collector. The rest of the chairs was tracked old style by agents on roof tops with binoculars and cameras with triple dimensional lenses just like in any good old thriller. The whole project was a publicity stunt designed around involvement. I think it is a great idea. Of course the finder could keep the $129 chair but was ‘politely’ asked for an interview to use for the documentation of the stunt. The project has now finished but as a documentation here is a clip. Thanks to Radoslaw Panczak for the link.

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