Rchr
J-GLOBAL ID：202101011809303298   Update date: Jan. 30, 2024

Ooi Masahiro

オオイ マサヒロ | Ooi Masahiro
Affiliation and department：
National Research Institute for Earth Science and Disaster Prevention

About National Research Institute for Earth Science and Disaster Prevention


Research theme for competitive and other funds  (2)：
  • 2016 - 2017 General study on the 2016 Kumamoto earthquake and related activities
  • 2015 - 2017 Development of a disaster risk index for contributing to restructuring national land use.
Papers (11)：
  • Applicability of 3D grid modelling for urban subsurface grounds. Journal of JGS. 2022. 70. 5. 14-18
  • KUBO Tomohiro, SUZUKI Wataru, OOI Masahiro, TAKAHASHI Narumi, ASAO Kazumi, YOSHIOKA Kaoru. Study on Conducting Tabletop Exercise to Respond a Major Tsunami Disaster for Local Governments. Journal of Japan Association for Earthquake Engineering. 2020. 20. 7. 7_158-7_176
  • Tomohiro Kubo, Wataru Suzuki, Masahiro Ooi, Narumi Takahashi, Kazumi Asao, Kaoru Yoshioka. Application of a Real-Time Tsunami Forecast System to the Disaster Response of Local Governments during a Major Tsunami Disaster. Geosciences. 2019. 9. 2. 102-102
  • OOI Masahiro, FUJIWARA Hiroyuki, KAWAI Shinichi. Development of Integrated Geophysical and Geological Information Databases for Earthquake Disaster Prevention. Journal of JAEE. 2013. 13. 1. 1-16
  • 森川 信之, 藤原 広行, 河合 伸一, 青井 真, 功刀 卓, 石井 透, 早川 譲, 小林 京子, 大井 昌弘, 先名 重樹, et al. 2003年十勝沖地震の観測記録を用いた強震動予測手法の検証. 防災科学技術研究所 研究資料. 2007. 303. 1-1
ｍore...
MISC (11)：
  • 大井昌弘. 3Dモデルを活用し、災害に強いまちづくりへ. SOCIAL INNOVATION NEWS. 2020. 7. 12-15
  • 久保 智弘, 鈴木 亘, 大井 昌弘, 高橋 成実. 7408 津波予測情報を活用した津波災害対応の確立. 都市計画. 2018. 2018. 881-882
  • 先名重樹, 森川信之, 河合伸一, 大井昌弘, 藤原広行. 千葉県における常時微動観測によるS波速度構造モデルの推定. 日本地震学会秋季大会講演予稿集. 2010. 2010
  • 先名重樹, 神薫, 宮本賢治, 佐藤仙一, 須崎敦史, 森川信之, 河合伸一, 大井昌弘, 藤原広行. 千葉県における常時微動観測による地震動のスペクトル増幅率の推定. 物理探査学会学術講演会講演論文集. 2009. 121st
  • 藤原広行, 河合伸一, 青井真, 森川信之, 先名重樹, 大井昌弘, 早川譲, 遠山信彦, 松山尚典, 岩本鋼司, et al. 内陸地震の強震動評価のための全国深部地盤速度構造モデル. 日本地震学会秋季大会講演予稿集. 2008. 2008
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Lectures and oral presentations  (4)：
  • Reatime Tsunami Inundation Prediction System using S-net data for Chiba Prefecture
    (2022)
  • Realtime Earthquake Damage Prediction System for Chiba Prefecture
    (2022)
  • Estimation of the ground structure by microtremors observation at the developed embankment site
    (2022)
  • Development of monitoring systems using seismic intensity meters equipped with a MEMS acceleration sensor
    (2020)
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