New York photographer Jeff Chien-Hsing Liao has an upcoming solo exhibition at the Museum of the City of New York next month called Assembled Realities. I just heard about it through CityLab.

Here’s a bit of background on his work:

Pushing the boundaries of traditional documentary photography, Liao (b. 1977) creates large-scale panoramas by combining multiple exposures of the same location taken over the course of several hours. The resulting composite photographs are often fantastical; complex, hyper-real views that no single shot—or the eye—could capture.

And here’s two more of his photos:

For higher resolution versions, click here.

I love how his photos begin to distort reality and how they focus your attention – in many cases – on New York’s vibrant street life. I thought you might all enjoy them as well.

Here’s further evidence that technology is starting to infiltrate into many other industries, including architecture. London-based architect and designer Pernilla Ohrstedt is currently working on an exhibition for Dezeen and MINI Frontiers that will architecturally visualize the 3D data that driverless cars collect in order to navigate around.

I had never thought of this before, but as a byproduct of driverless cars, we’re about to start collecting detailed replicas of all of our cities – well beyond the static images we currently have with Google Streetview. In order to navigate by themselves, driverless cars are constantly scanning their surroundings to create a “point cloud” replica of the built environment. This point cloud basically tells the car where they are, where they should drive, and what obstacles might be around.

It could look something like this:

Already there are firms like ScanLAB emerging to provide 3D scanning, publishing, and visualization services. But this is obviously just the tip of the iceberg. I can only imagine what innovation will emerge from the passive collection of all this data once driverless cars become commonplace in our cities.

As one example, it could be a way for us to systematically measure the correlation between the qualities of a street and the vibrancy of its street life. Is there a perfect width? An ideal traffic volume? A right scale? All of this data could make city building more of a science (and perhaps less political).

My hope though is that this data would be open and accessible to all, so that clever entrepreneurs could build on top of it.

What are some of your ideas?

Images: Dezeen