Development of Indicator for Urban Resilience

In general, it is known that extreme weather events (KELLER S & ATZL A, 2014) and floods (ARKELL B & G.DARCH, 2006) have a serious impact on several critical infrastructure (CI) but specifically to the road network. The road network is one of the most important CI for the fire and rescue services. Research on transport network reliability and resilience to disasters demonstrates, a disruption to particular nodes of that network can have different degrees of disruption throughout (SAKAKIBARA H et al., 2004). Therefore it is essential to proceed to road network analysis methods (GIL J & STEINBACH P, 2008) by adopting vulnerability and criticality assessments with geographic context (JENELIUS E et al., 2006). The vulnerability of the road network under area covering disruptions (such as flooding, forest fires etc.) in contrast to single link failures, indicated that the impacts of this kind of events are largely determined by the population concentration, more precisely the travel demand within, in and out of the disrupted area itself, while the density of the road network is of small influence (JENELIUS E, 2010). Generally we are aiming to advance our understanding; from the prevailing focus of recent studies on ‘what can be damaged’ to ‘how can it operate best under sub-optimal conditions’ at a minimal standard basis in order to restore capacities. Therefore we are narrowing down the focus from all possible CI sectors, branches and object classes (US, German, etc.) to those CI primarily used by emergency managers in a crisis. The city of Cologne (Germany) is used as a case study since it is river-flood prone and thousands of people had been affected in the floods in 1993 and 1995. Components of vulnerability and resilience assessments are selected with a focus of analyzing exposure to floods and steps of analysis are demonstrated using a Geographic Information System. Methodologically we are aiming to show how criticality of infrastructure can be analyzed and how static vulnerability assessments can be improved by adding routing calculations. Specifically, we are adding value to the knowledge that should be taken in to account for an effective emergency response in an extreme flood scenario through the use of specific tools of network analysis in an ArcGIS environment and for the improvement of static vulnerability assessments. We are utilizing free open source data (geodata) created by projects like OpenStreetMap provided and maintained from the community of Geofabrik (https://www.geofabrik.de/en/), the city of Cologne (http://www.offenedaten-koeln.de/dataset) and the international commission of the Rhine (http://www.iksr.org/) about actual damages, flood extent and vulnerability of the population in urban areas.