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Using machine learning on tree-ring data to determine the geographical provenance of historical construction timbers

  1. 1.
    SYSNO0570811
    TitleUsing machine learning on tree-ring data to determine the geographical provenance of historical construction timbers
    Author(s) Kuhl, E. (DE)
    Zang, C. (DE)
    Esper, Jan (UEK-B) [VS1] SAI, ORCID, RID
    Riechelmann, D. F. C. (DE)
    Büntgen, Ulf (UEK-B) [VS1] RID, ORCID, SAI
    Briesch, M. (DE)
    Reinig, F. (DE)
    Roemer, P. (DE)
    Konter, O. (DE)
    Schmidhalter, M. (CH)
    Hartl, C. (DE)
    Source Title Ecosphere . Roč. 14, č. 3 (2023). - : Wiley
    Article numbere4453
    Document TypeČlánek v odborném periodiku
    Grant EF16_019/0000797 GA MŠMT - Ministry of Education, Youth and Sports (MEYS), CZ - Czech Republic
    Institutional supportUEK-B - RVO:86652079
    Languageeng
    CountryUS
    Keywords artificial intelligence * dendrochronology * dendroprovenancing * European Alps * Extreme Gradient Boosting * Larix decidua * tree-ring density * tree-ring width
    Cooperating institutions Masarykova univerzita Brno (Czech Republic)
    URLhttps://esajournals.onlinelibrary.wiley.com/doi/10.1002/ecs2.4453
    Permanent Linkhttps://hdl.handle.net/11104/0342148
    FileDownloadSizeCommentaryVersionAccess
    Kuhl-2023-Using-machine-learning-on-treering-.pdf82.2 MBPublisher’s postprintopen-access
     
Number of the records: 1  

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