When Sep Kamvar moved from the San Franciso Bay Area to Cambridge, Mass., in 2012 to establish the Social Computing Group at the Massachusetts Institute of Technology (MIT) Media Lab, he noticed that his new environment felt different for some reason—and it wasn’t just the colder weather. Was it something physical, such as the widths of the sidewalks and bike lanes, and the number of trees? Or was it something cultural, such as the proximity of a good espresso?
Kamvar resolved to find out. He and his students began by accessing the host of publicly accessible data to map the urban landscape. Their ambitions extend far beyond Cambridge: They plan to document 100 U.S. cities with 100 maps, for a total of 10,000 maps.
“Not only can maps tell stories,” says Kamvar, the LG associate professor of media arts and sciences, “but stories have a big impact on the way the world is shaped. Part of the idea with these maps is to make them accessible: All of these thousands of micro stories that make up a city.”
The first map, released March 31, illustrates bicycle crashes in Cambridge, pairing data from police reports with Google Maps Geolocation API data and Street View images. Within the week, the team then released bike-crash maps for San Francisco, Los Angeles, Chicago, Austin, Texas, and Portland, Ore., and then maps of independent coffee shops for these cities as well as for Seattle and Brooklyn, New York. “The beginning of the process always starts with an idea, something that feels important,” Kamvar says.
Next up was street greenery. The idea came to mind after Kamvar had “been walking around the city and noticed this quality of filtered light. So we decided it would be interesting to make a map of filtered light and the quality of light,” he says. “The next step was finding the data source that corresponds with that. In this case, we used Google Street View data.”
See more of MIT Media Lab's Social Computing Group’s growing catalog of maps here.
Across the campus, the Sustainable Design Lab in MIT’s Department of Architecture is also leading a map-making effort. Christoph Reinhart, the professor who heads the laboratory, is mapping the solar energy-generating potential of entire neighborhoods and cities building by building. “We know how to make buildings energy efficient, but the next frontier is the city,” Reinhart says.
Reinhart and his team generated a topographical model of Cambridge using GIS (Graphical Information Systems) information as well as data from a publicly funded LiDAR (Light Detection and Ranging) survey to map each building’s suitability for solar panels, including its footprint and scale, and the presence of other buildings and trees that may block or reflect sunlight.
Stuart Dash, Cambridge city’s director of community planning, sees great potential for big data. He and his office frequently work with MIT to identify new mapping possibilities and analytics. “The value is not making a pretty map but one with strong data, to help you understand an issue more clearly,” Dash says. He cautions, however, that the data is only as good as its ability to effect change. “You have to get the right map to the right person for the right conversation.”
Check out your building’s solar potential at the Mapdwell Project.