Article

A Simulation and Visualization Environment for Spatiotemporal Disaster Risk Assessments of Network Infrastructures

A Simulation and Visualization Environment for Spatiotemporal Disaster Risk Assessments of Network Infrastructures

  • Heitzler, M., Lam, J. C., Hackl, J., Adey, B. T., and Hurni, L. (2017). A Simulation and Visualization Environment for Spatiotemporal Disaster Risk Assessments of Network Infrastructures. Cartographica: The International Journal for Geographic Information and Geovisualization, 52(4), 349–363. doi: 10.3138/cart.52.4.2017-0009

Abstract

Emerging methodologies for risk assessments of civil infrastructure networks require the coupling of several spatiotemporal models that need to be executed multiple times with varying parametrizations to account for model uncertainty and to investigate “what-if” scenarios. These requirements led to the development of a software environment to support the simulation process and the visual analysis of its results. The simulation engine component of the environment makes it possible to define, couple, and execute models. An embedded infrastructure model facilitates the development of functionality to estimate and aggregate capacity measures of single objects affected by multiple hazards. The simulation manager component can be used to execute multiple instances of the simulation engine conveniently with varying parametrizations. The included visualization tool provides two complementary views. The ensemble view can be used to analyze the data at a highly aggregated level with information visualization techniques and the simulation view can be used to investigate simulations in greater detail via an interactive map window and a state dependency graph. The software environment is used in a risk assessment for the region of Chur, Switzerland, which comprises the simulation of multiple natural hazard scenarios that lead to impaired transport infrastructure capacities and thus to disrupted traffic flows.

Jürgen Hackl Written by:

Dr. Jürgen Hackl is an Assistant Professor at the University of Liverpool. His research interests lie in complex urban systems and span both computational modelling and network science.