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

0570811 - ÚVGZ 2024 RIV US eng J - Journal Article
Kuhl, E. - Zang, C. - Esper, Jan - Riechelmann, D. F. C. - Büntgen, Ulf - Briesch, M. - Reinig, F. - Roemer, P. - Konter, O. - Schmidhalter, M. - Hartl, C.
Using machine learning on tree-ring data to determine the geographical provenance of historical construction timbers.
Ecosphere. Roč. 14, č. 3 (2023), č. článku e4453. ISSN 2150-8925. E-ISSN 2150-8925
R&D Projects: GA MŠMT(CZ) EF16_019/0000797
Research Infrastructure: CzeCOS IV - 90248
Institutional support: RVO:86652079
Keywords : artificial intelligence * dendrochronology * dendroprovenancing * European Alps * Extreme Gradient Boosting * Larix decidua * tree-ring density * tree-ring width
OECD category: Environmental sciences (social aspects to be 5.7)
Impact factor: 2.7, year: 2022
Method of publishing: Open access
https://esajournals.onlinelibrary.wiley.com/doi/10.1002/ecs2.4453

Permanent Link: https://hdl.handle.net/11104/0342148