Development of Big Data Analysis Techniques based on an Evacuation Model during Earthquake Disasters
| Project/Area Number |
15H04032
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Structural engineering/Earthquake engineering/Maintenance management engineering
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| Research Institution | University of Yamanashi |
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Principal Investigator |
HADA Yasunori 山梨大学, 大学院総合研究部, 准教授 (70360849)
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| Co-Investigator(Kenkyū-buntansha) |
関谷 直也 東京大学, 大学院情報学環・学際情報学府, 准教授 (30422405)
廣井 悠 東京大学, 大学院工学系研究科(工学部), 准教授 (50456141)
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥17,550,000 (Direct Cost: ¥13,500,000、Indirect Cost: ¥4,050,000)
Fiscal Year 2017: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2016: ¥5,460,000 (Direct Cost: ¥4,200,000、Indirect Cost: ¥1,260,000)
Fiscal Year 2015: ¥9,620,000 (Direct Cost: ¥7,400,000、Indirect Cost: ¥2,220,000)
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| Keywords | ビッグデータ / 防災 / 減災 / 避難 / 地震 / 震災 / 構造工学・地震工学 / 自然災害 |
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| Outline of Final Research Achievements |
In this study, we analyzed the relationship between human behavior and big data in earthquake disasters, and we developed the big data analysis techniques that can interpret the evacuation behavior quantitatively and qualitatively.
First, we surveyed the change of the trend before and after the foreshock and main shock using mobile special statistics to grasp evacuation behaviors in wide area beyond the area of municipalities in the 2016 Kumamoto earthquake. Secondly, the questionnaire data as a qualitative survey and the big data as a quantitative survey are structured and verified by evacuation simulation in megacities in earthquake disasters. Third, the difficulty of the depiction of disasters is discussed focused on the depiction of social phenomena and the depiction of psychological phenomena.
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| Academic Significance and Societal Importance of the Research Achievements |
震災時の人間行動は極めて多様であり、これをリアルタイムで把握することができれば、きめ細かい被災者支援活動を戦略的に行う事が可能となる。また、将来発生する震災を想定し、事前にシミュレーションを行う事により、適切な事前計画の検討が可能となる。本研究では、こうした課題を解決するためにビッグデータに着目し、震災時の市町村界を超える広域避難行動の実態を明らかにするとともに、質的調査と量的調査を有機的に構造化する手法を構築し、その有効性を示した点に学術的、社会的意義がある。また、災害<Disaster>の描写の試みの困難さについて、社会現象の描写と心理現象の描写に絞って論じた学術的研究はほとんどない。
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Report
(4 results)
Research Products
(19 results)
