The discipline of Science of Cities examines relationships between the physical form of cities and the social, cultural, economic, technological and spatial processes that give rise to this form. As technology evolves and changes, so do the ways in which we make and think about our cities. In this era of unprecedented and fast-accelerating changes, digital technologies are reshaping the ways in which we measure, sense, conceive of, design and plan for our cities. As a result, we collect and store large amounts of data on every aspect of the urban environment, but it is as yet unclear how this data can be used to inform evidence based planning and urban management. This unit of study will introduce the principles of science of cities and the tools, methods, algorithms and techniques on big urban data that enable transformative ways of thinking about, designing and planning for a fast urbanizing world. Emphasis will be placed on developing understanding of urban structure and fast and slow dynamics shaping this structure. This transdisciplinary unit of study will be relevant for designers, planners, geographers, economists, physicists and data scientists interested in modelling urban systems.
lecture 1 hr/week; tutorial 2 hrs/week
assessment 1 (individual) (25%), major project (group) (20%), major project (individual) (50%), tutorial exercises and class participation (individual) (5%)
Batty, M. (2015). The New Science of Cities. Cambridge, MA: MIT Press Townsend, A.M. (2013). Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia. New York: W.W. Norton Krugman, P. (1996). Confronting the mystery of urban hierarchy. Journal of the Japanese and International Economies, 10, pp. 399-418 Gabaix, X. (1999). Zipf's Law for Cities: An Explanation. The Quarterly Journal of Economics, 114(3), pp.739-767 Bettencourt, L., Lobo, J., Helbing, D., Kuhnert, C., and West, G.B. (2007). Growth, innovation, scaling and the pace of life in cities. PNAS, 104 (17), pp.7301-7306 Research and data reports, The Australian Bureau of Statistics (specific references provided through the unit)
Undergraduate-level mathematics and statistics, some experience with programming preferred