Warning: "continue" targeting switch is equivalent to "break". Did you mean to use "continue 2"? in /nfs/c02/h01/mnt/15473/domains/architecture.io/html/main/wp-content/plugins/jetpack/_inc/lib/class.media-summary.php on line 77

Warning: "continue" targeting switch is equivalent to "break". Did you mean to use "continue 2"? in /nfs/c02/h01/mnt/15473/domains/architecture.io/html/main/wp-content/plugins/jetpack/_inc/lib/class.media-summary.php on line 87
Till Nagel: Unfolding the City – Architecture IO

Architecture IO

Select a topic

Rethinking How People Move in Cities November 14, 2014

Unfolding the City

In recent years more and more data about the city is digitally collected. This data from sources such as mobile phones, sensors, and location-based services can be visualised to reflect urban activity. Geovisualisation stimulates the visual analysis of spatial patterns, relationships, and trends, as well as enables interactive exploration and understanding of location-based information. Usable and approachable visualisations allow casual users and experts alike to make sense of this data, to see the city in different perspectives, and to understand their environment.

Till Nagel explores the challenges in urban data visualisation, as well as showcases multiple projects that demonstrate current approaches to and new thinkings about urban mobility.

So, I’m a computer scientist turned designer and I am interested in how maps and geovisualisations can help regular people to better understand their environment. And nowadays, we live in a very data rich world and it only increases, so we are seeing more and more sensors and services and systems and they are all recording and generating large amounts of data, and many of which are about movements in the city. So, let me give you a personal example.

Yesterday, coming from Paris with the Eurostar, I arrived at St. Pancras and bought a coffee with a credit card. Then, I took a cab, going to the hotel and that apparently was not a good idea, because at 5p.m., getting close to St. Paul’s Cathedral is really something you should not do. Anyway, after a good night sleep, this morning I learned it and I went to the tube station, tapping in with my Oyster card. So I went then, here, to Barbican Station and on my last metres to the museum, I tweeted how I’m thrilled to be here on the stage today. So, all the while, I was leaving some kind of invisible trail behind me. All the while, I was leaving some little digital bits in various databases. And I am only one person. So, of course, multiply that by a million and you have large amounts of data. The question is, how can we leverage this? How can we tap into complex urban systems and bring them to a human scale? And one means of doing that is visualising it. Visualisations can help to make the invisible visible. Visualisations can help to reveal patterns and relationships and trends.

And in the next 15 minutes, I am going to show you a couple of visualisation projects all showing different aspects of urban mobility and showcasing you different designs for the public. So, the very first one is “Touching Transport”, where we are visualising the bus network and this was part of the larger research initiative “LIVE Singapore!” by the MIT SENSEable City Lab. The aim of this project is to give access to the public and to different stakeholders on real time data about the city. So, in the process of bringing together different stakeholders we create various visualisations, for example, here, how the weather affects taxi usage in Singapore.

But today, I’m going to talk about the bus network which is an integral part of the public transport system here. So, you have to tap in and tap out also in buses, so that’s meaning we know from where to where the people are riding, how many passengers are on the bus at anytime and so forth. So, in the design process of creating a visualisation, in the beginning, we typically start with very simple graphs. Here, we are just showing boarding and deboarding passengers on a single bus line all over the day, or we are showing bus rides between the stations, and these kind of experiments, these kind of visual early prototypes help us not only to understand the data ourselves, but also to then go to the experts and, in this case, from the Land Transport Authority in Singapore, and discuss with them so they also can understand what and how visualisations may help.

So, as I said, this was aimed for the public so we put this on a large table top, we created also appealing visualisations. And here we start with a map view so people are accustomed to that, they know how to navigate on those. And you see here the blue dots representing stations and more boarding passengers and the orange ones more deboarding ones. So, we also see now, again, one of the first prototypes, one of the first experiments here in a highly polished way and the same with the arcs.

Now, let me guide you through the video. This was based, again, on a large multitouch table top and you can just use simple finger gestures, you can pinch and pan, like you know from your smartphone nowadays. And you can pan into the areas of interest, for example your own neighborhood or maybe the commuting area you are going to. So now, some small first spacial patterns emerge, for example this cluster of green areas here indicating – if it’s in the morning – indicating a dwelling area. And orange ones here meaning apparently the area where people are going to in the morning meaning this is the city center or some working environments, offices. And you can also pan through the time, pan through the day and just select areas in the time you’re interested in, but you have to keep that in mind. So a second view and we wanted to simplify those and separate them, now you see the whole day at a single glance and you still can compare now and start to see some tempo-spatial patterns. For example, you can see when in the evening, there are many orange dots in a cluster of stations, that probably is because there is an entertainment area, where people are going to for a drink in the evening. Now, we did a couple of user studies, I’m a researcher so we have to do these things and we try them, we tested these, with the experts and with the citizens of Singapore, with the public and also with non-locals, as some kind of control group, and what we learned here, from this user study is that all these different stakeholders that all participants from these different groups were able to gain some insights, were able to gain some knowledge. And of course, the depth of these insights differed. I mean, an expert, obviously could connect them to prior knowledge, prior expert knowledge, but even simple things become very important if it’s personal to your own life. And this notion, we also followed with the next project “Isoscope”. This is a project done by some of my excellent students from the University of Applied Sciences in Potsdam and there we tried to visualise the variance of mobility in the city. And this was based on a historical technique to visualize travel time or how far you can go in a specific travel time. So this is Melbourne, in the 1920s, and the dark purple area in the city centre that you see now, the area you are able to reach within 10 minutes, the dark green one is then, in 20 minutes and so forth.

But, this only shows a single speed or so meaning, the speed must be constant all over the day which is for trains typically true. Now, this is of course not true for road traffic, cars, as I said, as I was sitting yesterday in the cab. So of course you are able to go further in the morning hours but not that far in the rush hour when there’s lots and lots of congestion. So, we now use this technique of isochrone maps, but instead of showing different travel times, we show the same travel time now over the day. And you see this now, this is an online tool you can also visit that and explore your own city. If we are panning over the timeline, over the day, you see how it shrinks in the day and how enlarges and expands at night. You can also select different travel times, you can also compare, for example, the working days, the week days and the weekend and so on. So this is based on sensor data from Nokia HERE, so we see here agglomeration of data from cars and from sensors in the road and so on. But the nice thing is that we published this on the web and then it was kind of nicely received in the media so we got tens of thousands of users in the first days and they of course gave us feedback. So, what we learned is that people like to also compare cities, they start to see some of the very transient structure or very temporary patterns which emerge. And this is still kind of based on a classic map.

But in the next project, we wanted to investigate how, first of all, how maps always represent the physical world. That is what we know. But there are ways of showing, or of distorting this space, depending on the purpose of a map and this very famous tube map here from Harry Beck, in the 1930s. He tried to solve the problem that the London tube or London underground system got larger and larger and became more complex, also visually in the geographical maps. So he straightened the lines, he equalized the distances between stops, in order to ease the task of getting from station A to station B. And the question now is: Do we understand that the areas here are shown differently, do we realise there’s some kind of fish-eye lens over the city centre and does that maybe even affect how we perceive our city?

So to investigate these kind of questions, we created this visualisation here for Shanghai metro and there you see the metro network plan, as it looks like in the tube stations, in the underground stations in Shanghai and this was exhibited there so it was for the local citizens. And we created a couple of different visualisations scenes, also an infographic poster showing some details. But this data here is based on the time plans so on the actual time schedule, meaning this is how it would look like in the perfect world, or how I imagine the perfect world in the mind of a transport planner.

So, in the morning now, they are all starting, all these little dots here are trains starting, running on their lines and we are following a single train, and now if we are zooming in a bit, then we suddenly see that these stops are all flashing, that they are all popping up and this is always the time when a train arrives at a station, there’s some activity. It’s of course a simplification. But what you can see now is that they are all flashing in unison, synchronously, again based on the time plan. So, what it kind of does, it is, it gives an impression of the pulse of the city, of the rhythm of the city, and we put that also in contrast, this rigidness with this very vibrant, colourful, human-scale, visual style.

But let’s go back to the geographical view. So, you see Huangpu river, you see the shoreline of Shanghai and now, let’s say we want to actually see how it looks like in the schematic view, so we transform it, we morph it to this schematic view and if you now observe the green line in the right bottom corner which goes to the upper, you see how this shrinks and now expands again. And this, in the geographical view, for me, as a rider of the train of an underground, subway train, it is not that important that I know if it’s 3 or 5 kilometers. It’s much more important that I know I have to get off the train in two stops.

So this notion of that precise geographical maps might not always be the most appropriate to reflect how we perceive space or how we move around on a personal level in a city, we also investigated in this project, “Liquidata”, also by some of my great students here and here we wanted to allow users, allow citizens to playfully explore their personal paths. So this was based on the famous psychogeographic map by Debord, and were he tried to find another way or a new way of displaying, of highlighting spaces and places where we, to which we are, to which we have some personal relation, to which we are maybe emotionally connected. This might be the bench in the park, where we had our first kiss, or it might be the bakery, with the nice smell in the morning and so, our project, was influenced, not only conceptually, but also visually, where we tried to come up with a new way, with a novel way of visualising or hightlighting these spaces which are relevant to our own lives.

Now, let’s see also, again, a visualization experiment, as I said in the design process, it is important to try out a visual language, to find a visual form. And this very organic way here, this very fuzzy and fluid metaphor of the mental map which we all might have if we are in a new city, also very imprecise, we try to here reflect this also in the style. But again, it’s just an experiment. So now, let me again guide you through the next video where we are showing this prototype. Now, let’s assume you went to Berlin and it is a new city for you, either for work of for leisure but let’s say now you have a couple of hours and you’re just stroll around, you just walk around and want to experience this city and you don’t actually want to just look on your little device through this looking glass and find maybe the best café in the vicinity, you’re just more interested to actually experience the city. But now, let’s assume, in the evening you go back to your hotel and in the lobby, there is this large tabletop, a public display and you put your mobile phone now onto this table and at that moment, you are sharing your personal paths, you are opening up all these spaces so it flows onto the map and uncovers the spaces you visited and now these little yellow dots here are points of interests, it might be a café you visited, it might be a gallery around the corner, you didn’t pass by. And now you can also use your personal device with the public device and I think that is also a nice metaphor for the personal and public space when we walk around. So with the private device, where you also know how to handle it, you can now select one of the points of interest, one of these little yellow dots here and if you found something which is interesting, maybe which you visited so you want to know a bit more about it and what others have thought about it. So now, you select it and you can dig into some comments, maybe others made or some reviews some others published on the web. So you just tap on it and select through these other ideas or comments people made, you can do the same for pictures, maybe people shared or uploaded to the web. And if you have been to the café and you liked it, the nice maybe façade, or the wallpaper, something, and you had a picture taken yourself, and you can just share and swipe it and put it to the public space, to the public table. So in that sense, you are also sharing your own experience. This also happens now when another person comes into the lobby, let’s say, has the same app, of course installed, and puts his or her phone onto the table and now you see overlappings, now you can also see how maybe you visited similar areas or maybe where you did not do it, and where you recommend others or where you discuss about your experience here.

So, all these four projects I showed you briefly are visualising different aspects of urban mobility. We’ve seen bus passengers and bus rides, we have seen car traffic here and the congestion, we have seen subway trains and this distortion of space on subway maps and we have seen traces or personal paths of pedestrians walking around in a city. But all of them have in common that we tried to incite curiosity, that we want to enable a casual exploration and that we want to support generating insights. So overall, really, we want to encourage people to reflect on how each of us individually and we all as a whole move around in cities. Thank you!

Till Nagel

Till Nagel

With a background in media and computer science, Dr. Till Nagel is a research affiliate with the FHP Urban Complexity Lab and the MIT SENSEable City Lab. His research interests are in geovisualisation, urban data, and interaction design, with a focus on how to engage broader audiences with interactive visualisations of tempo-spatial data.

Comments