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Open AccessArticle

Leaf Canopy Layers Affect Spectral Reflectance in Silver Birch

Department of Environmental and Biological Sciences, University of Eastern Finland, 111, 80101 Joensuu, Finland
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Remote Sens. 2019, 11(24), 2884; https://doi.org/10.3390/rs11242884 (registering DOI)
Received: 30 September 2019 / Revised: 19 November 2019 / Accepted: 30 November 2019 / Published: 4 December 2019
(This article belongs to the Section Forest Remote Sensing)
The availability of light within the tree canopy affects various leaf traits and leaf reflectance. We determined the leaf reflectance variation from 400 nm to 2500 nm among three canopy layers and cardinal directions of three genetically identical cloned silver birches growing at the same common garden site. The variation in the canopy layer was evident in the principal component analysis (PCA), and the influential wavelengths responsible for variation were identified using the variable importance in projection (VIP) based on partial least squares discriminant analysis (PLS-DA). Leaf traits, such as chlorophyll, nitrogen, dry weight, and specific leaf area (SLA), also showed significant variation among the canopy layers. We found a shift in the red edge inflection point (REIP) for the canopy layers. The canopy layers contribute to the variability in the reflectance indices. We conclude that the largest variation was among the canopy layers, whereas the differences among individual trees to the leaf reflectance were relatively small. This implies that within-tree variation due to the canopy layer should be taken into account in the estimation of intraspecific variation in the canopy reflectance. View Full-Text
Keywords: canopy layers; cardinal directions; spectral reflectance; leaf traits; NDVI; PRI; SLA; silver birch canopy layers; cardinal directions; spectral reflectance; leaf traits; NDVI; PRI; SLA; silver birch
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MDPI and ACS Style

Deepak, M.; Keski-Saari, S.; Fauch, L.; Granlund, L.; Oksanen, E.; Keinänen, M. Leaf Canopy Layers Affect Spectral Reflectance in Silver Birch. Remote Sens. 2019, 11, 2884.

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