Application of big data of service population for measuring community resilience

Abstract

Modern society is continuously exposed to the risks and damages of various kinds of disasters, and there is a demand for disaster resilience evaluation and improvement policies to cope with them. In order to overcome the limitations of existing indicator constructing methods for disaster resilience, this study proposes an evaluation method of disaster resilience using big data of mobile service population. Big data of service population perform various analysis in temporal and spatial scales in comparison with existing Census statistics, they show demographic characteristics of community more accurately. This study applied the proposed big data resilience indicators to Busan Metropolitan City with comparing to existing indicators. And found that proposed method can analyze the community resilience more effectively than the existing methods. Finally, big data indicators are found to be possible to assess the resilience of the community in further study and to use it as an alternative to overcome the limitations of existing research methods.