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dc.contributor.authorRäty, Janne
dc.contributor.authorPackalen, Petteri
dc.contributor.authorKotivuori, Eetu
dc.contributor.authorMaltamo, Matti
dc.date.accessioned2020-01-09T08:13:20Z
dc.date.available2020-01-09T08:13:20Z
dc.date.issued2020
dc.identifier.urihttps://erepo.uef.fi/handle/123456789/7904
dc.description.abstractAn area-based approach (ABA) is the most common method used to predict forest attributes with airborne laser scanning (ALS) data. Individual-tree detection (ITD) offers an alternative to ABA; however, few studies have examined the selection of these two alternatives for the prediction of diameter distributions. We predicted diameter distributions by applying ABA and ITD in coniferous-dominated boreal forests using ALS data and examined their predictive performance based on the shapes of the diameter distributions (Gaussian, bimodal, and reverse-J). We proposed an ABA–ITD fusion for diameter distribution prediction. Firstly, the fusion was optimized and its potential was evaluated using an error index. Secondly, we offer two alternatives to incorporate the fusion into ALS-based forest inventories. Our results indicate that ITD is more prone to errors than ABA and that the predictive performance of ITD is more sensitive than ABA to the shape of the diameter distribution. The results show that ITD outperforms ABA with Gaussian diameter distributions. In contrast, ABA was seen as preferable to ITD with bimodal- or reverse-J-shaped diameter distributions. The findings indicate that ABA–ITD fusion has potential for predicting diameter distributions, although the predictive capability of ITD is limited compared with that of ABA.
dc.language.isoenglanti
dc.publisherCanadian Science Publishing
dc.relation.ispartofseriesCanadian journal of forest research-revue canadienne de recherche forestiere
dc.relation.urihttp://dx.doi.org/10.1139/cjfr-2019-0102
dc.rightsAll rights reserved
dc.subjectarea-based approach
dc.subjectindividual-tree detection
dc.subjectmultispectral ALS
dc.subjectnearest neighbor imputation
dc.subjecttree size distribution
dc.titleFusing diameter distributions predicted by an area-based approach and individual-tree detection in coniferous-dominated forests
dc.description.versionfinal draft
dc.contributor.departmentSchool of Forest Sciences, activities
uef.solecris.id67078822en
dc.type.publicationTieteelliset aikakauslehtiartikkelit
dc.rights.accessrights© Authors
dc.relation.doi10.1139/cjfr-2019-0102
dc.description.reviewstatuspeerReviewed
dc.format.pagerange113-125
dc.publisher.countryKanada
dc.relation.issn0045-5067
dc.relation.volume2020; 50
dc.type.okmA1
uef.solecris.openaccessEi


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