Näytä suppeat kuvailutiedot

dc.contributor.authorTuominen, Sakari
dc.contributor.authorBalazs, Andras
dc.contributor.authorSaari, Heikki
dc.contributor.authorPölönen, Ilkka
dc.contributor.authorSarkeala, Janne
dc.contributor.authorViitala, Risto
dc.date.accessioned2015-10-12T07:02:15Z
dc.date.available2015-10-12T07:02:15Z
dc.date.issued2015
dc.identifier.citationTuominen, S., Balazs, A., Saari, H., Pölönen, I., Sarkeala, J., & Viitala, R. (2015). Unmanned aerial system imagery and photogrammetric canopy height data in area-based estimation of forest variables. <i>Silva fennica</i>, <i>49</i>(5), Article 1348. <a href="https://doi.org/10.14214/sf.1348" target="_blank">https://doi.org/10.14214/sf.1348</a>
dc.identifier.otherCONVID_24911615
dc.identifier.otherTUTKAID_67272
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/47286
dc.description.abstractIn this paper we examine the feasibility of data from unmanned aerial vehicle (UAV)-borne aerial imagery in stand-level forest inventory. As airborne sensor platforms, UAVs offer advantages cost anG Àe[iEiliW\ RveU WUaGiWiRnal PanneG aiUcUafW in fRUesW UePRWe sensinJ aSSlicaWiRnsin sPall aUeas but they lack range and endurance in larger areas. On the other hand, advances in the processing of digital stereo photography make it possible to produce three-dimensional (3D) forest canopy data on the basis of images acquired using simple lightweight digital camera sensors. In this study, an aerial image orthomosaic and 3D photogrammetric canopy height data were derived from the images acquired by a UAV-borne camera sensor. Laser-based digital terrain model was applied for estimating ground elevation. Features extracted from orthoimages and 3D canopy height data were used to estimate forest variables of sample plots. K-nearest neighbor method was used in the estimation, and a genetic algorithm was applied for selecting an appropriate set of features for the estimation task. Among the selected features, 3D canopy features were given the greatest weight in the estimation supplemented by textural image features. Spectral aerial photograph features were given very low weight in the selected feature set. The accuracy of the forest estimates based on a combination of photogrammetric 3D data and orthoimagery from UAV-borne aerial imaging was at a similar level to those based on airborne laser scanning data and aerial imagery acquired using purpose-built aerial camera from the same study area.fi
dc.language.isofin
dc.publisherSuomen Metsätieteellinen Seura
dc.relation.ispartofseriesSilva fennica
dc.subject.otherforest inventory
dc.subject.otherunmanned aerial system
dc.subject.otherUAV
dc.subject.otheraerial imagery
dc.subject.otherphotogrammetric surface model
dc.subject.othercanopy height model
dc.titleUnmanned aerial system imagery and photogrammetric canopy height data in area-based estimation of forest variables
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-201510073320
dc.contributor.laitosTietotekniikan laitosfi
dc.contributor.laitosDepartment of Mathematical Information Technologyen
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineMathematical Information Technologyen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.date.updated2015-10-07T09:15:05Z
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.relation.issn0037-5330
dc.relation.numberinseries5
dc.relation.volume49
dc.type.versionpublishedVersion
dc.rights.accesslevelopenAccessfi
dc.relation.doi10.14214/sf.1348
dc.type.okmA1


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