Tag: Computer Algorithms

As urbanization advances around the globe, the quality of the urban physical environment will become increasingly critical to human well-being and to sustainable development initiatives. However, measuring and tracking the quality of an urban environment, its evolution and its spatial disparities is difficult due to the amount of on-the-ground data needed to capture these patterns. To address this issue, Yong Suk Lee, assistant professor of technology, economy and global affairs in the Keough School of Global Affairs at the University of Notre Dame, and Andrea Vallebueno from Stanford University used machine learning to develop a scalable method to measure urban decay.