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Takeshi Komai

Biographic Data

ID8348737
NAMETakeshi Komai
GIVEN NAMESTakeshi
FAMILY NAMEKomai
SIGNATUREKOMAI T
AFFILIATIONSTohoku University
ORCID0000-0003-2244-5177
VERIFIEDYes
TOTAL WORKS8
TOTAL CITATIONS0
WORKS AS AUTHOR8
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2023
LATEST PUBLICATION YEAR2023
H-INDEX0
  • Overview of the Special Issue “Progress of Earth and Data Sciences Research into Tsunami Deposits, and Contribution to Tsunami Disaster Prevention (Part I)

    Open Access•Noriyoshi Tsuchiya, Takeshi Komai et al.•ARTICLE•Journal of Geography (Chigaku…•2023

  • Preface of the Special Issue “Progress of Earth and Data Sciences Research into Tsunami Deposits, and Contribution to Tsunami Disaster Prevention (Part I)

    Open Access•Noriyoshi Tsuchiya, Takeshi Komai et al.•ARTICLE•Journal of Geography (Chigaku…•2023

  • Preface of the Special Issue “Progress of Earth and Data Sciences Research into Tsunami Deposits, and Contribution to Tsunami Disaster Prevention (Part II)

    Open Access•Noriyoshi Tsuchiya, Takeshi Komai et al.•ARTICLE•Journal of Geography (Chigaku…•2023

  • Estimating Layer Boundaries of Mixed-layer Tsunami Deposits with a XRF Core Scanner

    Open Access•Kengo Nakamura, Tatsu KUWATANI et al.•ARTICLE•Journal of Geography (Chigaku…•2023

    From the perspective of disaster prevention, it is necessary to clarify the distribution and historical frequency of tsunami deposits. However, tsunami deposits are disturbed by earthquakes and tsunamis. Therefore, it is difficult to identify the layers of deposits. Layers deposited during disturbances are dated and grain-size distribution is measured. Using the results of geochemical data and principal component analyses with detailed elemental …

  • Overview of the Special Issue “Progress of Earth and Data Sciences Research into Tsunami Deposits, and Contribution to Tsunami Disaster Prevention (Part II)

    Open Access•Noriyoshi Tsuchiya, Takeshi Komai et al.•ARTICLE•Journal of Geography (Chigaku…•2023

  • Statistical Correlation for Geological Layers Using XRF Core Scan Data

    Open Access•Tatsu KUWATANI, Toshimoto SAKAI et al.•ARTICLE•Journal of Geography (Chigaku…•2023

    A method is developed to quantitatively correlate geological layers based on similarities in the shape of the statistical frequency distribution of a large volume of multi-element count data obtained with an X-ray fluorescence (XRF) core scanner. A distance measure between probability distributions called Jensen–Shannon divergence is adopted as a criterion for similarities in statistical distributions with the assumption of a Gaussian distributio…

  • Machine Learning-based Geochemical Discrimination Method for Tsunami Deposits and a Simple Determination System

    Open Access•Shuta SATO, Takeshi Komai et al.•ARTICLE•Journal of Geography (Chigaku…•2023

    In order to establish a discrimination method for tsunami deposits, a machine learning analysis is conducted for geochemical data to determine paleo-tsunami deposits. Column samples containing tsunami deposits are collected at Noda village, Iwate prefecture, and Wakabayashi-ku, Sendai city, and the distribution of element concentrations are continuously measured. The model is trained by Multilayer perceptron using Noda samples as training data. C…

  • Estimation of Sedimentary Area of Tsunami Deposits and Evaluation of Heavy Metals Related to the Great East Japan Earthquake

    Open Access•Yoshishige Kawabe, Junko HARA et al.•ARTICLE•Journal of Geography (Chigaku…•2023

    The physical and chemical properties of tsunami deposits of the Great East Japan Earthquake on March 11, 2011, are investigated. In addition, environmental impact assessments are conducted based on estimations of tsunami deposit areas. The contents of heavy metals in tsunami deposits are similar to those in common soils. The leaching values of arsenic and lead are slightly higher than those of general soils. Large volumes of silt and clayey tsuna…

No prominent works on this page.

  • Overview of the Special Issue “Progress of Earth and Data Sciences Research into Tsunami Deposits, and Contribution to Tsunami Disaster Prevention (Part I)

    Open Access•Noriyoshi Tsuchiya, Takeshi Komai et al.•ARTICLE•Journal of Geography (Chigaku…•2023

  • Preface of the Special Issue “Progress of Earth and Data Sciences Research into Tsunami Deposits, and Contribution to Tsunami Disaster Prevention (Part I)

    Open Access•Noriyoshi Tsuchiya, Takeshi Komai et al.•ARTICLE•Journal of Geography (Chigaku…•2023

  • Preface of the Special Issue “Progress of Earth and Data Sciences Research into Tsunami Deposits, and Contribution to Tsunami Disaster Prevention (Part II)

    Open Access•Noriyoshi Tsuchiya, Takeshi Komai et al.•ARTICLE•Journal of Geography (Chigaku…•2023

  • Estimating Layer Boundaries of Mixed-layer Tsunami Deposits with a XRF Core Scanner

    Open Access•Kengo Nakamura, Tatsu KUWATANI et al.•ARTICLE•Journal of Geography (Chigaku…•2023

    From the perspective of disaster prevention, it is necessary to clarify the distribution and historical frequency of tsunami deposits. However, tsunami deposits are disturbed by earthquakes and tsunamis. Therefore, it is difficult to identify the layers of deposits. Layers deposited during disturbances are dated and grain-size distribution is measured. Using the results of geochemical data and principal component analyses with detailed elemental …

  • Overview of the Special Issue “Progress of Earth and Data Sciences Research into Tsunami Deposits, and Contribution to Tsunami Disaster Prevention (Part II)

    Open Access•Noriyoshi Tsuchiya, Takeshi Komai et al.•ARTICLE•Journal of Geography (Chigaku…•2023

  • Statistical Correlation for Geological Layers Using XRF Core Scan Data

    Open Access•Tatsu KUWATANI, Toshimoto SAKAI et al.•ARTICLE•Journal of Geography (Chigaku…•2023

    A method is developed to quantitatively correlate geological layers based on similarities in the shape of the statistical frequency distribution of a large volume of multi-element count data obtained with an X-ray fluorescence (XRF) core scanner. A distance measure between probability distributions called Jensen–Shannon divergence is adopted as a criterion for similarities in statistical distributions with the assumption of a Gaussian distributio…

  • Machine Learning-based Geochemical Discrimination Method for Tsunami Deposits and a Simple Determination System

    Open Access•Shuta SATO, Takeshi Komai et al.•ARTICLE•Journal of Geography (Chigaku…•2023

    In order to establish a discrimination method for tsunami deposits, a machine learning analysis is conducted for geochemical data to determine paleo-tsunami deposits. Column samples containing tsunami deposits are collected at Noda village, Iwate prefecture, and Wakabayashi-ku, Sendai city, and the distribution of element concentrations are continuously measured. The model is trained by Multilayer perceptron using Noda samples as training data. C…

  • Estimation of Sedimentary Area of Tsunami Deposits and Evaluation of Heavy Metals Related to the Great East Japan Earthquake

    Open Access•Yoshishige Kawabe, Junko HARA et al.•ARTICLE•Journal of Geography (Chigaku…•2023

    The physical and chemical properties of tsunami deposits of the Great East Japan Earthquake on March 11, 2011, are investigated. In addition, environmental impact assessments are conducted based on estimations of tsunami deposit areas. The contents of heavy metals in tsunami deposits are similar to those in common soils. The leaching values of arsenic and lead are slightly higher than those of general soils. Large volumes of silt and clayey tsuna…

Geology (8 works) · Geology (8 works) · earthquake and tectonic studies (7 works) · Geology and Paleoclimatology Research (6 works) · Earth science (4 works) · Emergency management (3 works) · Geochemistry (3 works) · Geochemistry and Geologic Mapping (3 works) · Geography (3 works) · Political science (3 works)

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