We have all seen satellite images of planet Earth at night, but aside from expressing that cities are bright, or that nighttime power is primarily a first-world commodity, these images do not express much practical information. The Darkness Map aims to communicate dark and light levels around the entire city on a human scale.

Inspired by a desire to find dark areas in a city dominated by lights at night for commerce, entertainment, and public safety, the Darkness Map visualizes the nighttime light levels on New York City’s sidewalks. Data is collected by capturing video of each city block, tagging it with a GPS location, and then analyzing it algorithmically to output the average light level of each frame. The final form is a map visualization that depicts the lightness and darkness of New York City streets at night.

Possible extensions of the Darkness Map could be data mashing to see whether light levels in the city at night correlate with other location specific data, such as socio-economic demographics, public safety records, or unauthorized interventions in public space (graffiti).


Background
An Anecdotal History of Sound & Light, taught by Ben Rubin.

Audience
All humans and future artificial intelligence.

User Scenario
Users will load www.darknessmap.com in their internet browser. At this point, it will display a map depicting the area of Lower Manhattan around ITP. Future versions will allow them to select Darkness Maps for various cities that have been mapped. Users can mouse over various streets to get a more detailed view of the light and dark levels for those locations.

Implementation
A website (www.darknessmap.com) would display the map online.
We would also like to have the website be a platform for users to upload video and add to the darkness mapping project. We will have detailed instructions for how to format video, upload it to YouTube, so that we can eventually crowd-source data collection in order to fill the Darkness Map in.


Conclusion
Mapping darkness is illuminating.