Titlebook: Risk Assessment, Modeling and Decision Support; Strategic Directions Ann Bostrom (Associate Dean of Research & Associat Book 2008 Springer-

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Perspectives on Visualizing Uncertainty in Natural Hazards,st make difficult personal choices in the face of vast quantities of data that have been produced for other purposes. Ellen Peters draws on empirical studies to show that “Less is More” in the presentation of information. She also argues that visualizations should be tailored to specific decision ne

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Conclusion,a significant leap forward in our ability to model the effects of earthquakes on the built environment. This rapid progress in risk modeling is based upon significant advances in engineering, and information and sensor technologies that have resulted from significant research investments by the Nati

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A Brief History of Seismic Risk Assessment,ter agreed entirely when he heard those words in 1984, but two more decades later the perspective is greatly improved, at least as regards seismic risk assessment. In fact, as we shall see, in many ways we were just on the verge of seismic risk analysis and assessment in 1984, whereas today we have very significant capabilities.

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Perspectives on the History of Seismic Risk Assessment, how Europe, Japan, and the United States interacted in the development of seismic research and building codes. Finally, Dennis Mileti urges practitioners to take sociological perspectives into account, as losses that extend beyond traditionally assessed risk are harder to quantify, but no less important.

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Seismic Risk Mitigation Decisions Under Uncertainty,cilities to seismic shaking. With a complete description of these uncertainties, complete seismic risk curves (loss vs. annual frequency of occurrence) can be developed. These seismic risk curves can form the basis for informed decisions about seismic risk mitigation.

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Modeling Seismic Mitigation Strategies,t risk to mitigate for the hazard. At the same time, advanced software tools have emerged to allow stakeholders to more accurately assess their hazard risk exposures. These include the proprietary catastrophe models used by the insurance and reinsurance industries and the federal government’s model, HAZUS..

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Perspectives on Loss Estimation Models and Metrics, — including network, engineering and building data, and measures of social and economic changes — have the potential to strengthen loss estimation models and metrics. Network data, data on non-economic losses, and additional input from sociologists and social models are seen as essential elements, currently missing from existing methodology.