2018 Volume 16 Issue 2 Pages 247-259
In order for a region to implement effective and appropriate disaster prevention measures, it is important to formulate measures against disasters based on regional characteristics. Under the conventional approach, however, practitioners of disaster prevention activities (such as municipalities and local residents) gather comprehensive information on the area themselves, and interpret regional characteristics; this approach requires a significant amount of time and effort to identify the appropriate countermeasure method. Therefore, in order to empower disaster prevention practitioners to select effective and appropriate countermeasures, we developed the "Regional Characteristics Information Tool". This tool concentrates information cross-sectionally on the geographical area where the practitioner is active and provides information based on a relative evaluation of disaster characteristics. In addition, in order to clarify the effectiveness of this tool, a hearing survey was conducted on disaster prevention officials in municipalities that are intended users as well as local disaster prevention leaders. Responders confirmed that the natural and social characteristics, as well as the risk of disasters are presented in an easy-to-understand manner with regard to disaster characteristics in the user's active area, and that this helped them to better understand disaster characteristics. On another front, we received a comment that users wanted to review disaster prevention measures by browsing information regarding local social dynamics such as: population density, number of population during the day and night, and membership numbers of voluntary disaster prevention bodies. This indicates that practitioners need more detailed information on regional characteristics. This tool, by providing a comparison of information between regions, has the potential to contribute to further consideration and practice of disaster prevention measures. To this end, it will be necessary to promote utilization and distribution of open data, and to identify mechanisms to scoop up regional information.
