Proposal for Holistic Assessment of Urban System Resilience to Natural Disasters

Urban system is a complex mix of interdependent components and dynamic interactions between them that enable it to function effectively. Resilience of urban system indicates the ability of a system to resist, absorb, accommodate to and recover from the effects of a hazard in a timely and efficient manner. In the relevant literature, most studies consider individual components separately. On the other hand, the purpose of this paper is to assess the urban system as a whole, considering all relevant components and their interactions. The goal is a study of possibilities for holistic evaluation of urban system resilience to natural disasters. Findings from the preliminary study are presented: (i) the definition of urban system and categorization of its components, (ii) a set of attributes of individual components with impact on disaster resilience of the entire system and (iii) review of different methods and approaches for resilience assessment. Based on literature review and extensive preliminary studies a new conceptual framework for urban resilience assessment is proposed. In the presented paper, a conceptual model of urban system by abstraction of its components as nodes (buildings), patches-specific nodes with spatial properties (open space), links (infrastructures) and base layer (community) is created. In the suggested model, each component is defined by its own quantitative attributes, which have been identified to have an important impact on the urban system resilience to natural disasters. System is presented as a mathematical graph model. Natural disaster is considered an external factor that affects the existing system and leads to some system distortion. In further analyses, mathematical simulation of various natural disasters scenarios is going to be carried out, followed by comparison of the system functionality before and after the accident. Various properties of the system (accessibility, transition, complexity etc.) are going to be analysed with graph theory. The final result is going to be an identification of critical points and system bottlenecks as basis for further actions of risk mitigation.