Zobrazeno 1 - 10
of 194
pro vyhledávání: '"Oishi, Satoru"'
Prediction of the extent and probability of debris flow under rainfall conditions can contribute to precautionary activities through risk quantification. To this end, quantifying the debris-flow risk against rainfall involves three components: predic
Externí odkaz:
http://arxiv.org/abs/2211.06837
Autor:
Yokoya, Naoto, Yamanoi, Kazuki, He, Wei, Baier, Gerald, Adriano, Bruno, Miura, Hiroyuki, Oishi, Satoru
We propose a framework that estimates inundation depth (maximum water level) and debris-flow-induced topographic deformation from remote sensing imagery by integrating deep learning and numerical simulation. A water and debris flow simulator generate
Externí odkaz:
http://arxiv.org/abs/2006.05180
Akademický článek
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Autor:
Syarifuddin, Magfira, Jenkins, Susanna F., Taisne, Benoit, Oishi, Satoru, Basuki, Ahmad, Iguchi, Masato
Publikováno v:
In Journal of Volcanology and Geothermal Research April 2022 424
Autor:
Okazaki, Megumi1 (AUTHOR) okazaki_m@storm.dpri.kyoto-u.ac.jp, Oishi, Satoru2 (AUTHOR), Awata, Yasuhiro3 (AUTHOR), Yanase, Tomoro4 (AUTHOR), Takemi, Tetsuya5 (AUTHOR)
Publikováno v:
Atmospheric Science Letters (John Wiley & Sons, Inc. ). Jun2023, Vol. 24 Issue 6, p1-11. 11p.
Autor:
Syarifuddin, Magfira, Oishi, Satoru, Nakamichi, Haruhisa, Maki, Masayuki, Hapsari, Ratih Indri, Mawandha, Hanggar Ganara, Aisyah, Nurnaning, Basuki, Ahmad, Loeqman, Agoes, Shimomura, Makoto, Iguchi, Masato
Publikováno v:
In Journal of Volcanology and Geothermal Research 1 November 2020 405
Autor:
Chen, Jian, Takeyama, Tomohide, O-tani, Hideyuki, Yamanoi, Kazuki, Oishi, Satoru, Hori, Muneo
Publikováno v:
In Computers and Geotechnics January 2020 117
Probabilistic Prediction Method of Erosion Volume and Deposition Area from Rainfall Observation Data
Publikováno v:
E3S Web of Conferences, Vol 415, p 05030 (2023)
We propose a methodology to estimate the spatial distribution of the probability of sediment deposition due to debris flow from rainfall data by combining the probability prediction of erosion volume based on an ordinal logistic regression and a sedi
Externí odkaz:
https://doaj.org/article/da670c319f99412596fec7c40db90e65
Publikováno v:
In Engineering Geology 14 August 2019 258
Publikováno v:
In Advances in Water Resources December 2017 110:249-262