Isochronic Singapore: A Dynamic City Transportation Map


Update: If you are interested in isochronic maps, I have more detailed explaination of the process in my graduate thesis Seeing Differently: Cartography for Subjective Maps Based on Dynamic Urban Data, and the source code (Processing) is on GitHub

Last year I made my first attempt at isochronic map for the City of Paris, where the distance on map is proportional to travel time. Well, maps evolve.

Senseable City Lab is having this exciting exhibition Live Singapore! at Singapore Art Museum. We collaborated with Singapore government and companies of telecommunication, power, seaport, land transportation, etc. to create graphic visualizations that reveal Singapore’s urban dynamics.

In March I received the GPS location record of Singapore taxis of August, 2010. All taxis report their coordinates and availability status every few minutes during operation. Comparing to an animation of dense moving dots all over the map, I’m more interested in the underlying patterns of these activities and how they relate to the structure of land use and road layout.

Our brilliant scientist Chrisian Sommer built a network from this massive data and estimated the shortest travel time between every pair of places on an hourly basis. The data quality this time is far better than what I had for Paris (which was retrieved from Google Directions). It is dynamic, and it reflects real traffic condition. I used 290 control points over the city to distort the map. Selecting any of these points as origin, the other points will move away or towards it according to the travel time it takes to get there.

Isochronic Singapore - Screenshots Collage

The final app runs on a big display controlled by a Magic Trackpad. Visitors can click anywhere on the map to see its animation through the month. This video demos the maps for the central business district and the airport. It is quite interesting to see the response to road density, the expansion of congested area and the travel time explosion when rush hour comes.

This isochronic map is one of the series of cognitive maps I’m developing – beyond objective projections, we are enabled to see what the city looks and feels to its residence. Maps may not be static anymore, but reflect the dynamic nature of contemporary cities. Also, maps can be dependent on the user (location-based in this case) – they are now about individuals.

Followed by an introduction teaser to the whole event. I also did the anthropogenic heating one. The other beautiful visualizations are credited to Aaron Siegel and Oliver Senn.

Tools used: R, Processing, Illustrator

Collaborators: Christian Sommer, Kristian Kloeckl

Visualizing A Real-time Trivia Game


On April 10th, 2011 MIT held the Next Century Convocation as a centerpiece of its 150 anniversary celebration. 10,000 people attended the event at the Boston Convention and Exhibition Center. Before the program began guests participated in a trivia game designed by our team.

The game was a crowdsourcing experience, with participants asking their own questions to the crowd. Participants sent text messages to a short number through Ken’s awesome mSurvey system. Messages ending with “?” were recognized as questions and appeared on the screen with a sequential number. Messages started with “Q+number” followed by a space are recognized as answers to that question. Questions and answers were displayed in real-time, on a 90-foot screen.

My goal in designing this vis was to enable direct feedback to the users, invoke conversation among them and encourage participation. Considering the dimensions of the space, it was critical to keep the interface simple and learnable. Our team came up with this idea of “questions competing for answers” – each question moved from the left edge of screen to the right, gradually accelerating if nobody responded to it, till it was out of sight. When an answer came in, it was attached to the target question and therefore slowed it down. Each question left a trail behind it, whose width was related to speed. So the more popular questions would stay longer on the screen. It was a competition for both good questions and interesting answers.

Screenshot from the game:
Screenshot from the Trivial Game at MIT150 Convocation

Picture at the event:
Live photo at the convocation

I was a bit unhappy that the video staff insisted on adding moving backgrounds to the visualization. Then during the real run, we encountered some technical problem , causing the answers mismatched for a while (in fact a bug in the setup-at-the-last-minute message censorship system – censorship sucks, I knew it better than anyone). Anyway both the team and the guests had a lot of fun with the game. Some of us were sleepless for a few days to make this work, especially our great leader Ken, who’s been suffering from a fever since then – I hope he gets better now. ♥

Tools used: Processing

Visualization: Xiaoji Chen, Yanni Loukissas
Backend: Kenfield Griffith, Reid Williams
And thanks to the rest of the team: Michael Berry, Kristyn Maiorca, Ella Peinovich who made this happen

Power Chart of Chinese Provinces


Economist just posts an interactive visualization Chinese Equivalents on their website. It’s a very interesting approach. (Somehow I feel it has an psychological side-effect by saying one province is equivalent to France while it’s neighbor is equivalent to Kenya, though noted in terms of population.)

I got curious how we can visualize how actually important the Chinese provinces are. I was reading Gastner & Newman’s paper Diffusion-based method for producing density-equalizing maps (PNAS 2004) at the time. So I set out to make my first density-equalizing map.

Newman’s code on his website deals with raster image only. I also tried to implement a diffusion simulator in Processing, but it was hard to preserve all the details of a vector map. Below is my first shot. It took (quite) some manual effort to remove the bad points. Still seeking solutions. Anyway, enjoy.

You can recognize in this map how unbalanced China is – the west is barely occupied due to challenging natural environment, and population keeps flowing from the middle towards the economic centers (Beijing and the southeast coast). They become both productivity and pressure for big cities.

What about looking at the provinces from a social network’s perspective? In the following graph I measured how often each two provinces appear in the same media coverage. It is clear now that Beijing is the absolute, mono-center of all China. The social power is not proportional to a province’s population. The south and the east coast get far more attention than inland provinces, which is a sad fact.

Tools used: Processing, Tulip, Illustrator

 

Redrawing the Map of Great Britain from a Network of Human Interactions


This paper has been published on PLoS ONE: full text

Do regional boundaries defined by governments respect the natural way that people interact across space? The URB team of SENSEable City Lab analyzed 12 billion anonymized landline calls in Great Britain to illustrate the true connections between places. The strength of connection is defined by the frequency and period of phone calls. It is revealed that people tend to communicate with those that are geographically close to them. Therefore, it is possible to identify clusters of connections as regional groups. It is fun to compare these new boundaries with existing ones and see how much people really love each other.

The visualization challenge here is the extra dense connections. An ideal vis solution should show clearer and finer pattern as data accumulates, not the opposite. Mauro Martino worked with the team from the beginning and derived the primary concept. I hopped on board later and finished with the final video to elaborate the whole idea. Processing is not able to handle this scale of objects (especially in animation) so a lot of pre-processing was done exclusively for each scene.

For those who cannot use YouTube, click this instead:

 

The research has also been covered by BBC and The Economist.

Collaborators in visualization: Mauro Martino, Francesco Calabrese
Tools used: Processing, R, Premiere

A Very Supernatural Map of United States


Uh… This is purely out of boredom. In welcome of the Season 6 of CW show Supernatural, I took a look at the path Sam and Dean have traveled. Guess which state hosted the most monsters?

Congratulations to Illinois! Then there goes South Dakota, Nebraska, Kansas, Pennsylvania, Ohio, Iowa, Indiana, Colorado, Missouri, Wisconsin, Oklahoma, Minnesota and California. The supernatural communities, be them spirits, creatures, mutants, psychics, witches, demons, angels or gods, definitely share taste in choosing playgrounds.

Click here to play with the interactive map:

I’m aware that there are a few fictional towns in the show. Coordinates are selected from the first result returned by Google Maps, so, if a circle falsely falls on your neighborhood, don’t panic! Corrections welcomed.

I am also aware that my lines between cities show shortcuts rather than actual trips. But you see, the brothers don’t always drive; they travel in time, in dream, in spirit forms; they have been zapped here and there by angels, demons and god himself. No such data is available as far as I know. Though I’d love to, watching the 5 seasons all over again is not in my short-term plan.

Data source: The Supernatural Wiki, Google Maps
Tools used: Google Maps API