Routing from many places to a single destination can also be done on a small scale. This helped us find out some characteristics of cities around the world.
The idea behind the "Urban Mobility Fingerprint" is to calculate routes to a single destination (A) from many departure points (B). The points (B) are located on a radius around the destination. The size of the radius is defined by travel time with different transportation modes. All these routes together then create the "Urban Mobility Fingerprint"
Once the routes are drawn, all starting points are rotated and aligned on to one ideal connection line. The direct line between these two dots is the ideal connection between the two locations. The length of the routes is scaled to fit the connecting ideal line. We call the resultant graph the "Street DNA".
Since in reality street connections never follow a perfectly straight line, deviations are unavoidable. The Street DNA graph shows exactly these situations. The color-coding helps to identify to what compass point routes are aligned on the map.
The outline is created by connecting all locations (B) that are reached within the same travel time. These lines are called isochrones. The color of each route is defined by the compass direction it follows, making it easier to relate routes within the fingerprint graph.
We created the Urban Mobility Fingerprint and Street DNA graphs for several cities around the world. The 13 examples we selected are supposed to resemble a large diversity of cultural backrounds around the globe, combined with objectively compelling street networks.
As well as different cultural backgrounds, we also looked for characteristic places and iconic street topography. Coastal locations like San Francisco, Dubai's Palm Island or Manhattan show extreme deviations from the ideal connections we experience while travelling through our cities.
Berlin is the largest city in Germany. 15 minutes travel time from the center of the city brings you to the outer parts of the inner city. Berlin was once been divided by the Berlin Wall, but this is not noticeable anymore.
Dubai is located on the coast of the United Arab Emirates. It is characterized by its car centered layout, and thus has a very young and modern infrastructure, formed and built by human hands. A prime example is Palm Island created in the Persian Gulf.
Jerusalem is a divided city. A massive wall and many checkpoints define the cityscape. We chose Jerusalem to explore whether the street network might represent the political situation of the Middle East.
London as the capital of the United Kingdom has been the largest city in the world during large parts of its urban history. The nearly ideal Street DNA shows very direct connections, created by a dense street network.
Venice Beach used to be a standalone city on the coast near Los Angeles. The massive street grid surrounding downtown L.A. connects Venice with other neighboring urban areas and creates a car centered city like few others.
Moscow is the largest city in Russia. It is located inland. Its fingerprint and DNA is comparable to other inland metropoles and capitals of western Europe. Its size allows a travel time of 15 minutes while not leaving heavily urbanized areas.
The Parliament of New Delhi is located in a relatively young part of the Indian capital. Older parts of Delhi (south and north of A) show a much more tangled network. Yet again less deviation is observed in the old parts of the city.
Manhattan's street network is characterized by bottlenecks connecting it to other boroughs. Brooklyn Bridge, Battery Tunnel, Queensboro Bridge and other connecting paths create a very interesting Street DNA pattern. It is far from optimum, but imposed on and defined by the natural landscape of the area.
Similar to other inland metropoles Paris also shows a densely woven street network. The Street DNA shows connections closely aligned to the optimal in every direction. The Fingerprint shows some outliers, connected by highways leading out of the city.
Unlike other inland metropoles Rome's Street DNA does not show a very direct connection network. The street network of Rome is heavily influenced by the areas topography.
San Francisco's distinct city structure shows a very interesting Mobility Fingerprint and Street DNA. Hills and bridges to remote locations create bottlenecks that are recognizable as the travel patterns of the city and surrounding area.
Just like other cities surrounded by water, Stockholm also shows a distinct pattern in Fingerprint and Street DNA, especially travelling eastward.
Tokyo's Street DNA has only a few major roads connecting the center to the outer parts. It seems like there is a specific street to take, depending on the designated compass direction of a route.