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.

  • Credit: Social Computing Group at MIT Media Lab

<p xmlns="http://www.w3.org/1999/xhtml">MIT professor Sep Kamvar believes that these interactive maps (<a href="http://youarehere.cc/w/coffeeshops/san-francisco" target="_blank">San Francisco</a> and <a href="http://youarehere.cc/w/coffeeshops/brooklyn" target="_blank">Brooklyn, New York</a>, shown) of independent coffee shops are empowerment tools. “It starts to become clear where you might place a coffee shop if you’re a coffee shop entrepreneur,” he says. “I’m sure a lot of the big coffee chains have these in house. But making it public and accessible gives the entrepreneur the same access. If you give tools to a broad segment of the population, it leads to a rich and diverse ecosystem.”</p>

MIT professor Sep Kamvar believes that these interactive maps (San Francisco and Brooklyn, New York, shown) of independent coffee shops are empowerment tools. “It starts to become clear where you might place a coffee shop if you’re a coffee shop entrepreneur,” he says. “I’m sure a lot of the big coffee chains have these in house. But making it public and accessible gives the entrepreneur the same access. If you give tools to a broad segment of the population, it leads to a rich and diverse ecosystem.”

Credit: Social Computing Group at MIT Media Lab

“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.”

Credit: Social Computing Group at MIT Media Lab

  • A good map, MIT’s Kamvar says, “comes from the heart rather than the head.” He was motivated to generate new maps because he “realized there was so much about everyday feeling that was inspired by design. I just wanted to show more of that.” (Greenery maps for Cambridge, Mass., and Washington, D.C., shown.)

    Credit: Social Computing Group at MIT Media Lab

    A good map, MIT’s Kamvar says, “comes from the heart rather than the head.” He was motivated to generate new maps because he “realized there was so much about everyday feeling that was inspired by design. I just wanted to show more of that.” (Greenery maps for Cambridge, Mass., and Washington, D.C., shown.)

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.

  • MIT Sustainable Design Lab’s solar map of Cambridge, Mass.: The different hues represent the level of solar energy-generating potential with brighter hues indicating more optimal locations and conditions for photovoltaic panels. The left sidebar estimates the optimal system size for solar energy potential at a specific address and provides information on cost, payback time, the building’s physical properties, and carbon offset information.

    Credit: MIT Sustainable Design Lab

    MIT Sustainable Design Lab’s solar map of Cambridge, Mass.: The different hues represent the level of solar energy-generating potential with brighter hues indicating more optimal locations and conditions for photovoltaic panels. The left sidebar estimates the optimal system size for solar energy potential at a specific address and provides information on cost, payback time, the building’s physical properties, and carbon offset information.

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.

MIT Sustainable Design Lab performed a case study of this hypothetical Boston neighborhood, first using Rhinoceros modeling software to define the layout of buildings, trees, parks, and courtyards. The Lab’s own urban modeling interface (UMI) tool then calculates the energy use of each individual building by drawing from publicly available climate and solar-radiation data while taking into account the effect of neighboring objects such as other buildings and trees. Buildings with high energy-generation capacity are reddest in color.

MIT Sustainable Design Lab performed a case study of this hypothetical Boston neighborhood, first using Rhinoceros modeling software to define the layout of buildings, trees, parks, and courtyards. The Lab’s own urban modeling interface (UMI) tool then calculates the energy use of each individual building by drawing from publicly available climate and solar-radiation data while taking into account the effect of neighboring objects such as other buildings and trees. Buildings with high energy-generation capacity are reddest in color.

Credit: MIT Sustainable Design Lab