Other features of his research project are the use of large data sets and cheap computing power to explore outstanding problems related to urban systems. For example, he developed an urban growth pattern monitoring project for the whole United States by using LandSat satellite images. Using high-resolution employment and transportation data sets, he also studied the relationship among economic opportunities, travel accessibility and environmental impact. He is currently developing machine learning algorithms to use high-resolution satellite images to identify and describe irregular settlements in India. Recently, we have worked with private sector partners and colleagues from other universities to study how to create water-saving plans using high-resolution (temporal) data of smart meters. These projects directly constitute a critical examination of the concept of "smart city". Dr. Kaza's interdisciplinary training in architecture, mathematics and planning enables him to have fruitful cooperation with researchers from different fields, including economics, computer science, civil engineering, geography and political science. His research is supported by the National Science Foundation, Ministry of National Defense, Environmental Protection Agency, Market Transformation Institute, World Bank, Urban Institute and Omidyar Network.