2020 年 15 巻 7 号 p. 970-974
The Global Centre for Disaster Statistics (GCDS) in Tohoku University was established in April 2015. One of its main missions is to support the Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) in the monitoring and evaluation of progress by providing support at a national level for building the capacity to develop nationwide statistics on disaster damage and by establishing an improved global database for such statistics. The objective of this study was to find clues for the effective measurement of disaster damage utilizing disaster statistics. In disaster loss databases, we often encounter so many observed variables that it is difficult to establish how severe each disaster was in total. Thus, it was considered that introducing a whole new compound indicator to estimate the scale of each disaster properly would be beneficial. In this context, the authors conducted a principal component analysis (PCA) to introduce new compound indicators. The material data for the analysis were retrieved via the global disaster-related database (GDB) provided by the GCDS. Consequently, it was posited that the score of the first principal component, calculated by a PCA, could be an effective indicator to estimate the specific impact of a disaster. We believe that the findings and proposal of a new indicator in this study will contribute to the literature in that new clues to establish an evidence-based criteria and threshold of disaster data collection are provided.
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