UAV-based photogrammetric point clouds and hyperspectral imaging for mapping biodiversity indicators in boreal forests

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversity of Helsinki-
Autor(es): dc.contributorNational Land Survey-
Autor(es): dc.contributorNational Resources Canada-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorCatarinense Federal Institute-
Autor(es): dc.contributorNational Land Survey of Finland-
Autor(es): dc.creatorSaarinen, N.-
Autor(es): dc.creatorVastaranta, M.-
Autor(es): dc.creatorNäsi, R.-
Autor(es): dc.creatorRosnell, T.-
Autor(es): dc.creatorHakala, T.-
Autor(es): dc.creatorHonkavaara, E.-
Autor(es): dc.creatorWulder, M. A.-
Autor(es): dc.creatorLuoma, V.-
Autor(es): dc.creatorTommaselli, A. M.G.-
Autor(es): dc.creatorImai, N. N.-
Autor(es): dc.creatorRibeiro, E. A.W.-
Autor(es): dc.creatorGuimarães, R. B.-
Autor(es): dc.creatorHolopainen, M.-
Autor(es): dc.creatorHyyppä, J.-
Data de aceite: dc.date.accessioned2025-08-21T16:35:29Z-
Data de disponibilização: dc.date.available2025-08-21T16:35:29Z-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2017-10-19-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.5194/isprs-archives-XLII-3-W3-171-2017-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/228411-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/228411-
Descrição: dc.descriptionBiodiversity is commonly referred to as species diversity but in forest ecosystems variability in structural and functional characteristics can also be treated as measures of biodiversity. Small unmanned aerial vehicles (UAVs) provide a means for characterizing forest ecosystem with high spatial resolution, permitting measuring physical characteristics of a forest ecosystem from a viewpoint of biodiversity. The objective of this study is to examine the applicability of photogrammetric point clouds and hyperspectral imaging acquired with a small UAV helicopter in mapping biodiversity indicators, such as structural complexity as well as the amount of deciduous and dead trees at plot level in southern boreal forests. Standard deviation of tree heights within a sample plot, used as a proxy for structural complexity, was the most accurately derived biodiversity indicator resulting in a mean error of 0.5 m, with a standard deviation of 0.9 m. The volume predictions for deciduous and dead trees were underestimated by 32.4 m3/ha and 1.7 m3/ha, respectively, with standard deviation of 50.2 m3/ha for deciduous and 3.2 m3/ha for dead trees. The spectral features describing brightness (i.e. higher reflectance values) were prevailing in feature selection but several wavelengths were represented. Thus, it can be concluded that structural complexity can be predicted reliably but at the same time can be expected to be underestimated with photogrammetric point clouds obtained with a small UAV. Additionally, plot-level volume of dead trees can be predicted with small mean error whereas identifying deciduous species was more challenging at plot level.-
Descrição: dc.descriptionDept. of Forest Sciences University of Helsinki, P.O. Box 27-
Descrição: dc.descriptionDept. of Remote Sensing and Photogrammetry Finnish Geospatial Research Institute FGI National Land Survey, Geodeetinrinne 2-
Descrição: dc.descriptionPacific Forestry Centre National Resources Canada, 506 West Burnside Road-
Descrição: dc.descriptionDept. of Cartography São Paulo State University, Roberto Simonsen 305-
Descrição: dc.descriptionCatarinense Federal Institute, Rodovia Duque de Caxias - km 6 - s/n-
Descrição: dc.descriptionDept. of Geography São Paulo State University, Roberto Simonsen 305-
Descrição: dc.descriptionCentre of Excellence in Laser Scanning Research Finnish Geospatial Research Institute FGI National Land Survey of Finland-
Descrição: dc.descriptionDept. of Cartography São Paulo State University, Roberto Simonsen 305-
Descrição: dc.descriptionDept. of Geography São Paulo State University, Roberto Simonsen 305-
Formato: dc.format171-175-
Idioma: dc.languageen-
Relação: dc.relationInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectForest Ecology-
Palavras-chave: dc.subjectForest Inventory-
Palavras-chave: dc.subjectForest Mensuration-
Palavras-chave: dc.subjectPhotogrammetry-
Palavras-chave: dc.subjectRemote Sensing-
Palavras-chave: dc.subjectSpectral Imaging-
Palavras-chave: dc.subjectUAS-
Título: dc.titleUAV-based photogrammetric point clouds and hyperspectral imaging for mapping biodiversity indicators in boreal forests-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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