In the year 2008 urban dwellers for the first time ever outnumbered rural ones. By 2030 twice as many people will live in cities than in 1970. This shift in population has also led to a shift in the landscape of risk, with cities becoming the major source of global risk. Current risk assessment models fall short in characterizing the spatial and temporal dynamics of the urban environments in terms of rapidly changing local exposure and vulnerability. We propose to develop a quantitative approach for forecasting risk in rapidly changing urban environments. The two main components of the proposed approach are (a) dynamic time-dependent exposure models and (b) time dependent vulnerability model that consider the main processes influencing the vulnerability of the built environment over time: structural deterioration, incremental expansion of buildings, and evolving building practices. The models and advanced technologies to be developed through this research include stochastic spatial and temporal exposure methods, novel remote-sensing based techniques for urban analysis, statistical pattern recognition methods and probabilistic analysis of incremental building expansion and vulnerability to enable risk forecast over time.
The proposed research will enable risk forecasts that are consistent with the population and urban building growth patterns of regions exposed to extreme events. The tools developed will enable policy-makers, municipal governments and planners to take steps towards reducing future risk. Research results will be integrated into current risk assessment models, such HAZUS, the software used by FEMA and the Department of Homeland Security for planning and managing disasters, and the Global Earthquake Model (GEM is a worldwide nonprofit earthquake consortium developing open source tools for earthquake hazard and risk assessment) that will enable them to better model and forecast the complex dynamics of urban risk. Numerous components of the research will further be part of a new Stanford interdisciplinary undergraduate class on urban risk, taught by research team members. The project team has a strong record in working with underrepresented groups and actively participates in Stanford's Engineering Diversity Program that provides teaching, research and mentoring opportunities for students from underrepresented groups. Undergraduates will be included in the project through NSF's REU program and Stanford's research to undergraduate students program supported by the Vice Provost on Undergraduate Education (VPUE).
