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M.Sc Johanna Stötzer
Dr. rer.nat. Sina Keller
Prof. Dr.-Ing. Stefan Hinz


Center for Disaster Management and Risk Reduction Technology (CEDIM) des KIT


Institut für Regionalwissenschaften (IfR)
CEDIM Partner





Project description

Vulnerability of critical road infrastructure increasingly comes to the fore of transportation planning research. Natural hazards, such as earthquakes and floods, threaten road infrastructure and thus, the society that depends on them.

Within the IPF-KRITIS project, a generic, multi-scale concept to analyse the vulnerability of critical road infrastructure is developed. This concept follows a modular approach: Its basic module evaluates the accessibility of emergency facilities by calculating an accessibility and remoteness index (ARI). Additional modules provide the opportunity to calculate the index based on a grid and to generate a degraded network scenario. The developed basic model has already been applied to the Maule region in central Chile (see figure). Additional modules will be realized and thereupon linked to the basic module.

One data base of the project is represented by OpenStreetMap. This data serves as basis for modeling the road network and the emergency facility location. An exemplary implementation uses the open source software PostgreSQL, PostGIS and pgRouting.

The IPF is responsible for the following tasks:

  • Integration of social parameters for the interaction and linkages between humans and critical road infrastructure in a disaster case (cooperation with IfR)
  • Development and implementation of a simulation concerning disaster-following consequences on road infrastructure. Possible disasters include tsunamis, earthquakes and floodings (cooperation with other CEDIM partners)
  • Development and implementation of further vulnerability indexes
  • Development and application of an index for intra-urban road infrastructure


The project is supposed to provide a decision-aid tool for regional planning of a road infrastructure. Furthermore, vulnerable nodes and links in the road network are to be identified. In a disaster case, the model will provide a quick overview of the disaster extends. This will enable the disaster management of the affected regions to react strategically.

  Fig.: Accessibility and Remoteness Index for the Maule region in central Chile. Green symbolises a high accessibility, red a high remoteness.