Photo via El País.

New research by 28-year-old Frederico Baylé and 31-year-old Damián Silvani has led to the development of new technology, an automatic detection map, that uses satellite imagery and other sources of open data (data that is freely available to anyone who wants to use it, even me or you) to visualize and monitor the spread of villas – Argentina’s shantytowns- on a national scale.

Baylé, who has a degree in Economics from the University of Buenos Aires and a Masters in Data Exploitation and Knowledge Discovery, first developed the technology while completing his Masters’ thesis. Focusing only on the La Matanza district in the Greater Buenos Aires area, he found that using satellite imagery, he could look for certain indicators that meant an area had a higher probability of being a slum: “The distribution of the roofs is very disorderly, there are internal streets, the roofs are crooked, they are shiny materials, they are usually in flooded terrain, in wetlands, or on the train tracks, for example.” Baylé cross-referenced these observations with other open data to develop an algorithm for determining where villas existed.

The darker the red, the higher the probability of being a villa. Photo via I, data reuser, by Federico Baylé
The darker the red, the higher the probability of being a slum. (Photo via I, Data Reuser, by Federico Baylé.)

Baylé’s research technique proved very effective. After graduating, he teamed up with Silvani, a computer science student, and together they founded Dymaxion Labs, with a focus on using satellite imagery and geospatial data to provide real-time data. They expanded the mapping technology that Baylé had created for La Matanza to analyze the entire country, allowing them to provide the public with up-to-date information of the evolution of Argentina’s undeveloped neighborhoods.

This new data source provides public organizations with new understandings of how and why villas evolve as they do. Organizations can use this information to make smarter decisions about how to mitigate the further spread of villas. Not only is this great news for Argentina, but Baylé sees potential for benefits of his technologies that reach outside of Argentina. He is “excited about the possibility of escalating processing to other countries.”

Baylé owes much of his success to the availability of open data, and he emphasizes the importance of researcher’s publishing their data for others to use. He believes that “data-driven policy is critical to successful outcomes.” Following Bayle’s logic, the more open data there is to analyze, the higher the probability that new policies will lead to successful outcomes.

One of the issues that companies like Dymaxion Labs (Google has its own project that provides real-time visualization of villas) attempt to address is whats referred to as “Reverse Invisibilization.” Underdeveloped villas tend to be segregated from more developed parts of the cities, so it is easy for city dwellers to forget about their less fortunate counterparts. To combat this problem, companies like Dymaxion Labs and Google use their technology to “promote the visibility of [these] neighborhoods and their inhabitants and promote the processes of urban integration.”