In this project, the PI and his team will develop a new simulation framework to interactively model and visualize socio-economic and geometric characteristics of urban areas. The framework will consist of a synergistic collaboration of three different areas: behavioral urban modeling, probabilistic graphical modeling, and visualization and computer graphics. In machine learning and statistics, the area of probabilistic graphical modeling offers a flexible framework to build, estimate and simulate from models of substantial complexity and scale, with partially observed data. By accounting for uncertainty and interdependencies, including aspects of dynamic equilibrium that arise in modeling the complex spatio-temporal dynamics of urban areas, the PI argues there is significant potential for breakthroughs in modeling large-scale urban systems. Similarly, by integrating behavioral and geometrical dimensions of urban areas, he expects to exploit the power of behavioral simulations more effectively by filling in geometric details that behavioral models are not well suited to manage, and at the same time provide a powerful framework to generate 2D and 3D geometric representations of urban areas that are behaviorally and geometrically consistent. The PI will take advantage of massive datasets available for urban areas, including parcel and building inventories, business establishment inventories, census data, household surveys, and GIS data on physical and political features, and will fuse these data into a coherent and consistent database to support his modeling objectives. This data fusion will address imputation of missing data, accounting for complex spatial and relational connections among the data sources. The PI will evaluate the accuracy and usability of his system through several deployments in diverse contexts. The PI has elicited engagement from the Urban Land Institute, the European Research Council, and the Council for Scientific and Industrial Research. Several organizations in the San Francisco Bay Area in California and the Puget Sound region in Washington will serve as testbeds for the research. Finally, the PI will collaborate with other NSF-funded research projects, such as the Drought Research Initiative Network, in order to investigate correlations between urban development and water/drought.
Broader Impacts: The results of this multidisciplinary project will have a transformative effect on the area of urban simulation, in that they will enable non-professionals as well as the general public to better understand urban phenomena. City planners, researchers, students, and citizens will be able to efficiently simulate urban processes not previously possible, and to visualize the effects of adopting different urban policies on urban livability and sustainability outcomes, and to address local and global concerns regarding equity, infrastructure, and economic development. The framework will provide interactive desktop and web-based interfaces for configuring urban scenario inputs to a simulation that may reach petabytes in data size, and to visualize the simulation results using 2D aerial views, 3D city walkthroughs, and choroplethic maps and tables of indicators portraying the simulated area. Thus, the work will also advance the fields of visualization and computer graphics, through development of new techniques for large-scale urban modeling and rendering. The PI will develop an open-source system to make the results of this research widely available.
The research objective of this project was to create an integrated hierarchical framework that models the behavioral and geometrical evolution of an urban environment. Our synergistic collaboration between urban simulation, machine learning, and visualization and computer graphics has led to increases in the accuracy and the scope of events that can be efficiently simulated and predicted in an urban landscape. It has enabled users – city planners, researchers, students, and citizens – to efficiently simulate urban processes not previously possible and to visualize the effects of adopting different urban policies on urban livability and sustainability outcomes. The outcomes during this four year project include new scientific results, formation of future urban scientists, creation of international collaborations, generation of new funding for follow-on work, and commercialization. In particular: Behavioral-Geometric Simulation. We have tightly integrated traditional socio-economic simulation with 3D urban modeling and visualization. This has enabled more accurate simulation and realism 3D previews of the effect of urban policies and actions. Integrated City Simulation. We developed novel linkages between urban socio-economic simulation, traffic simulation, and weather simulation. This has led to follow-on work that will provide new tools for concerned citizens and experts to address worldwide issues of urban sustainability. Deployment. We generated an example deployment of novel projected-developed visualization tools to the San Francisco area, spanning nine-counties and over 7 million people. This was made possible by additional funding by the target urban area. Collaborations. The project generated international, and still on-going, collaborations with Switzerland, France, Japan, and other US universities. Commercialization. The project led to one of the Purdue graduate students, and the PI on our UC Berkeley collaborative research partner, to co-found a startup company, Synthicity.com, commercializing urban simulation and visualization. The Purdue portion of this collaborative project has resulted in over 27 top venue publications (including to ACM SIGGRAPH/TOG, Eurographics/CGF, TVCG, Environment & Planning, and TRB), 21 national and international talks, several book chapters, research for 7 PhD dissertations, 1 MS, several awarded national and international research fellowships and internships to project personnel, and over $2.3M in additional NSF and non-NSF research funding to perform follow-on work.
