Improving emergency preparedness to cascading disasters: A case‐driven risk ontology modelling. (29th September 2020)

• Record Type: Journal Article
• Authors: Yu, Feng; Fan, Bo; Li, Xiangyang
• Other Names: De Nicola Antonio guestEditor.; Karray Hedi guestEditor.; Matta Nada guestEditor.
• Is Part Of: Journal of contingencies and crisis management. Volume 28:Number 3(2020:Sep.)
• Page Start: 194
• Page End: 214
• Publication Date: 2020-09-29
• Subjects: cascading disaster risks -- case‐driven method -- emergency preparedness -- ontology modelling; Crisis management -- Periodicals; 658
• DOI: 10.1111/1468-5973.12314
• Languages: English
• ISSNs: 0966-0879

Abstract

Abstract: With the acceleration of urbanization, cascading disaster risks (CDR) as a typical risk mode have become the main threat to cities. After experiencing several cascading disasters, such as typhoon Lekima, how to clarify the basic features of CDR and achieve risk modelling has turned to be increasingly significant for building resilient city. However, the complexity of CDR brings about the difficulty to quickly map such risk mode depending entirely on expertise. Therefore, this paper attempts to provide a CDROntology system built by concepts and relations, and make full use of the historical cases to drive the modelling of the target CDR with case‐based reasoning. Firstly, we describe the basic structure and content of CDR and give a three‐level CDROntology system with the explanation of modelling primitives. Then, taking CDROntology system as the basis, a case‐driven selection process is proposed to provide the modelling source for the target CDR. Furthermore, set covering and manual correction methods are adopted to model the evolutionary risk chain and the specific risk scenario of the target case. Finally, a case study is given to illustrate the use of CDROntology system and case‐driven method for building a predictive risk model in typhoon‐triggered cascading disasters.