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Improving terrestrial evapotranspiration estimation across China during 2000–2018 with machine learning methods

Tietueen suppeat tiedot
dc.contributor.authorYin, Lichang
dc.contributor.authorTao, Fulu
dc.contributor.authorChen, Yi
dc.contributor.authorLiu, Fengshan
dc.contributor.authorHu, Jian
dc.contributor.departmentid4100311110
dc.contributor.organizationLuonnonvarakeskus
dc.date.accessioned2022-01-19T08:42:36Z
dc.date.accessioned2025-05-28T13:43:30Z
dc.date.available2022-01-19T08:42:36Z
dc.date.issued2021
dc.description.vuosik2021
dc.format.bitstreamfalse
dc.format.pagerange18 p.
dc.identifier.olddbid494033
dc.identifier.oldhandle10024/551483
dc.identifier.urihttps://jukuri.luke.fi/handle/11111/24164
dc.language.isoen
dc.okm.corporatecopublicationei
dc.okm.discipline1171
dc.okm.internationalcopublicationon
dc.okm.openaccess0 = Ei vastausta
dc.okm.selfarchivedei
dc.publisherElsevier
dc.relation.articlenumber126538
dc.relation.doi10.1016/j.jhydrol.2021.126538
dc.relation.ispartofseriesJournal of hydrology
dc.relation.issn0022-1694
dc.relation.issn1879-2707
dc.relation.volume600
dc.source.identifierhttps://jukuri.luke.fi/handle/10024/551483
dc.subject.ysoEvapotranspiration
dc.subject.ysoMachine learning
dc.subject.ysoprocess-based ET
dc.subject.ysoET integration
dc.subject.ysoChina
dc.subject.ysoGaussian process regression
dc.tehOHFO-EI-OHFO
dc.titleImproving terrestrial evapotranspiration estimation across China during 2000–2018 with machine learning methods
dc.typepublication
dc.type.okmfi=A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä|sv=A1 Originalartikel i en vetenskaplig tidskrift|en=A1 Journal article (refereed), original research|

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