With Machine Learning, a New Tool can Scan Sidewalks from Satellite Images
Researchers, Maryam Hosseini and Andres Sevtusk, from the Department of Urban Studies and Planning, Massachusetts Institute of Technology (MIT), Fabio Miranda, from the Department of Computer Science, University of Illinois at Chicago (UIC), Roberto M. Cesar Jr., from the University São Paulo, and Claudio T. Silva, from the Department of Computer Science and Engineering, New York University, and the Center for Data Science, New York University, have recently unveiled a new tool that uses satellite images to map out sidewalks and crosswalks using machine learning. Titled Tile2Net, the researchers have stated that the program is "the first open-source scene classification model for pedestrian infrastructure from sub-meter resolution aerial tiles," which means that they use Google Maps to get accurate measurements of sidewalks and crosswalks.