Mini Special Issue on the Role of Quantitative Questionnaire Surveys on the “Build Back Better” Component of the Sendai Framework for Disaster Risk Reduction (2015–2030): The Life Recovery Survey Five Years After the Great East Japan Earthquake
Haruo Hayashi, Keiko Tamura, and Reo Kimura
President, National Research Institute for Earth Science and Disaster Resilience (NIED)
3-1 Tennodai, Tsukuba, Ibaraki, Japan
Risk Management Office, Niigata University
8050 Ikarashi 2-no-cho, Nishi-ku, Niigata, Japan
Graduate School of Human Science and Environment, University of Hyogo
1-1-12 Shinzaike-honcho, Himeji, Hyogo, Japan
This special issue focuses on “Build Back Better,” which is the key concept of the Sendai Framework for Disaster Risk Reduction (2015–2030). The Sendai Framework for Disaster Risk Reduction provides United Nations member states and economies concrete actions to protect their economic development achievements from disaster risk. However, how “Build Back Better” can be measured and linked to disaster risk reduction remain unclear.
Three papers here analyze the results of the “Life Recovery Survey Five Years After the 2011 Great East Japan Earthquake,” which was conducted in June of 2016. The first Life Recovery Survey was conducted four years after the 1995 Great Hanshin-Awaji Earthquake to document the extent to which the disaster victims had been able to rebuild their lives. Subsequently, the survey was conducted every two years until ten years after the earthquake. The survey was also conducted in the areas affected by the 2004 Niigata Chuetsu Earthquake and the 2007 Niigata Chuetsu-Oki Earthquake. Five years after the Great East Japan Earthquake of 2011, the present authors conducted a survey to document the actual situation of the disaster victims in Iwate, Miyagi, and Fukushima prefectures, which were the hardest hit by the disaster.
In addition, we analyzed the history of Nankai Trough earthquakes with the goal of preparing for the next Nankai Trough earthquake, which is predicted to occur in the near future. These results make it possible to identify issues and make recommendations on the kinds of systems that should be implemented.
It is our hope that this special issue will provide basic data to elucidate these issues.
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