This project uses recent advances in remote sensing and computer vision to develop an alternative approach to obtaining useful data for urban researchers and policy makers.
Our projects contribute to new information and analysis on sustainable economic growth by combining our expertise in areas such as economics and public policy, spatial analysis, geography and geographic information science. These projects have used methodological tools such as econometrics, image processing, machine learning, and optimization techniques.
We focus on land use and housing issues in Chinese cities with the aim to provide policy recommendations that help improve land use practices.
Using mobile phone data from Colombia, this project explores the relationship between social networks, socioeconomic class, and residential mobility.
Using interdisciplinary methods, we propose innovative strategies to address socioeconomic challenges around commuting and social mobility.
We focus on two dimensions of urban footprint growth: the expansion of the urban extent and the dynamics of growth within the city.
Through this research, we examine the industrial transformation in Bangalore, a megacity with a substantial services-based economy.
This research aims to contextualise land based financing instruments in relation to the institutional, market and governance conditions prevailing in the Indian urban context.