A study on the drivers of canopy reflectance variability in a boreal forest

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Hadi, Hadi
dc.contributor.author Rautiainen, Miina
dc.date.accessioned 2018-06-18T09:20:03Z
dc.date.available 2018-06-18T09:20:03Z
dc.date.issued 2018
dc.identifier.citation Hadi , H & Rautiainen , M 2018 , ' A study on the drivers of canopy reflectance variability in a boreal forest ' REMOTE SENSING LETTERS , vol 9 , no. 7 , pp. 666-675 . DOI: 10.1080/2150704X.2018.1458344 en
dc.identifier.issn 2150-704X
dc.identifier.issn 2150-7058
dc.identifier.other PURE UUID: 80bb7649-cb95-45ef-a9fc-39e5635717ea
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/a-study-on-the-drivers-of-canopy-reflectance-variability-in-a-boreal-forest(80bb7649-cb95-45ef-a9fc-39e5635717ea).html
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/21854296/A_study_on_the_drivers_of_canopy_reflectance_variability_in_a_boreal_forest.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/31922
dc.description.abstract The degree of which the observable canopy bidirectional reflectance factors (BRF) express plant trait variation at leaf and canopy scales is the fundamental physical basis underlying the use of optical remote sensing data for discriminating tree species and estimating forest biophysical variables. In this study, we quantified the relative contribution of variations in leaf optical properties (LOP), canopy structural properties, and understory reflectance, to canopy BRF variability in a boreal forest, at the spatial and spectral resolutions of Sentinel-2 (S2) Multi-Spectral Instrument. Our approach was based on physically-based forest reflectance model and global sensitivity analysis (SA) parameterized entirely with field measurements. Results showed LOP had dominant contribution to canopy BRF in shortwave infrared (SWIR) in multispecies forest areas, while canopy gap fraction in sensor's view direction (i.e. nadir) was consistently found as the main driver of canopy BRF in red. This implies the satellite-measured BRF in red is the most robust predictor of effective canopy cover (ECC), while BRF in SWIR are optimal for tree species classification based on interspecific differences in mean leaf traits. en
dc.format.extent 10
dc.format.extent 666-675
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries REMOTE SENSING LETTERS en
dc.relation.ispartofseries Volume 9, issue 7 en
dc.rights openAccess en
dc.subject.other 1171 Geosciences en
dc.title A study on the drivers of canopy reflectance variability in a boreal forest en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Built Environment
dc.contributor.department Department of Electronics and Nanoengineering en
dc.subject.keyword VEGETATION
dc.subject.keyword SENTINEL-2
dc.subject.keyword LEAVES
dc.subject.keyword MODEL
dc.subject.keyword INDEX
dc.subject.keyword AREA
dc.subject.keyword 1171 Geosciences
dc.identifier.urn URN:NBN:fi:aalto-201806183340
dc.identifier.doi 10.1080/2150704X.2018.1458344
dc.type.version publishedVersion

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