Open AccessMini Special Issue on NIED Frontier Research on Science and Technology for Disaster Risk Reduction and Resilience 2021
Author(s) -
H. Hayashi,
Hiroyuki Fujiwara
Publication year - 2021
Publication title -
journal of disaster research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.332
H-Index - 18
eISSN - 1883-8030
pISSN - 1881-2473
DOI - 10.20965/jdr.2021.p1045
Subject(s) - resilience (materials science) , disaster risk reduction , scope (computer science) , flood myth , natural disaster , work (physics) , computer science , landslide , geomatics , risk analysis (engineering) , emergency management , natural hazard , forensic engineering , data science , geography , environmental planning , engineering , business , political science , cartography , meteorology , geotechnical engineering , physics , law , thermodynamics , mechanical engineering , archaeology , programming language
We are very pleased to publish this Mini Special Issue, dedicated to NIED Frontier Research on Science and Technology for Disaster Risk Reduction and Resilience 2021. Three papers and one survey report are included. Miura et al. indicate the scope of disaster prevention covered by the new courses of study in the field of disaster prevention. By visualizing the contents of classification and analysis, they propose how to handle the scope of disaster prevention in disaster prevention learning in consideration of the comprehensiveness to solve the problems. In the second paper, a case study on flood damage in Hitoyoshi, Kumamoto Prefecture, Mizui and Fujiwara analyze a method of immediately determining the amount of waste disposal work and the number of residents and disaster volunteers required in the event of a disaster. Fujiwara et al. study the feasibility of estimating damage to large-spanned building structures by conducting shake table tests on a small gymnasium model with simulated damage and measuring the natural frequencies and mode shapes. Onoue et al., in a work published as a survey report, present a method for analyzing slope displacement by using the distance image data of a depth camera. They indicate the possibility of detecting minute changes that can precede slope failure. We hope this issue provides information useful to all readers who study natural disasters.