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dc.contributor.authorSaad, Rami
dc.contributor.authorEyvindson, Kyle
dc.contributor.authorGong, Peichen
dc.contributor.authorLämås, Tomas
dc.contributor.authorStåhl, Göran
dc.date.accessioned2018-01-25T12:13:59Z
dc.date.available2018-01-25T12:13:59Z
dc.date.issued2017
dc.identifier.citationSaad, R., Eyvindson, K., Gong, P., Lämås, T., & Ståhl, G. (2017). Potential of using data assimilation to support forest planning. <i>Canadian Journal of Forest Research</i>, <i>47</i>(5), 690-695. <a href="https://doi.org/10.1139/cjfr-2016-0439" target="_blank">https://doi.org/10.1139/cjfr-2016-0439</a>
dc.identifier.otherCONVID_27123583
dc.identifier.otherTUTKAID_74470
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/56904
dc.description.abstractUncertainty in forest information typically results in economic and ecological losses as a consequence of suboptimal management decisions. Several techniques have been proposed to handle such uncertainties. However, these techniques are often complex and costly. Data assimilation (DA) has recently been advocated as a tool that may reduce the uncertainty, thereby improving the quality of forest planning results. It offers an opportunity to make use of all new sources of information in a systematic way and thus provides more accurate and up-to-date information to forest planning. In this study, we refer to literature on handling uncertainties in forest planning, as well as related literature from other scientific fields, to assess the potential benefits of using DA in forest planning. We identify five major potential benefits: (i) the accuracy of the information will be improved; (ii) the information will be kept up to date; (iii) the DA process will provide information with estimated accuracy; (iv) stochastic decision making can be applied whereby the accuracy of the information can be utilized in the decision making process; and (v) DA data allows for the analysis of optimal data acquisition decisions.
dc.language.isoeng
dc.publisherNational Research Council of Canada
dc.relation.ispartofseriesCanadian Journal of Forest Research
dc.subject.othersuboptimal loss
dc.titlePotential of using data assimilation to support forest planning
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-201801241321
dc.contributor.laitosBio- ja ympäristötieteiden laitosfi
dc.contributor.laitosDepartment of Biological and Environmental Scienceen
dc.contributor.oppiaineEkologia ja evoluutiobiologiafi
dc.contributor.oppiaineEcology and Evolutionary Biologyen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.date.updated2018-01-24T13:15:15Z
dc.type.coarjournal article
dc.description.reviewstatuspeerReviewed
dc.format.pagerange690-695
dc.relation.issn0045-5067
dc.relation.numberinseries5
dc.relation.volume47
dc.type.versionacceptedVersion
dc.rights.copyright© the Authors, 2017. This is a final draft version of an article whose final and definitive form has been published by National Research Council of Canada. Published in this repository with the kind permission of the publisher.
dc.rights.accesslevelopenAccessfi
dc.subject.ysometsäsuunnittelu
dc.subject.ysokaukokartoitus
dc.subject.ysooptimointi
dc.subject.ysobayesilainen menetelmä
dc.subject.ysoepävarmuus
jyx.subject.urihttp://www.yso.fi/onto/yso/p1863
jyx.subject.urihttp://www.yso.fi/onto/yso/p2521
jyx.subject.urihttp://www.yso.fi/onto/yso/p13477
jyx.subject.urihttp://www.yso.fi/onto/yso/p17803
jyx.subject.urihttp://www.yso.fi/onto/yso/p1722
dc.relation.doi10.1139/cjfr-2016-0439


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