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Articles by Anssi Krooks
Category : Research note
article id 1125,
category
Research note
(2014).
Predicting tree structure from tree height using terrestrial laser scanning and quantitative structure models.
Silva Fennica
vol.
48
no.
2
article id 1125.
https://doi.org/10.14214/sf.1125
Highlights:
The analysis of tree structure suggests that trees of different height growing in similar conditions have similar branch size distributions; There is potential for using the tree height information in large-scale estimations of forest canopy structure.
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Author Info
We apply quantitative structure modelling to produce detailed information on branch-level metrics in trees. Particularly we are interested in the branch size distribution, by which we mean the total volume of branch parts distributed over the diameter classes of the parts. We investigate the possibility of predicting tree branch size distributions for trees in similar growing conditions. The quantitative structure model enables for the first time the comparisons of structure between a large number of trees. We found that the branch size distribution is similar for trees of different height in similar growing conditions. The results suggest that tree height could be used to estimate branch size distribution in areas with similar growing conditions and topography.
- Krooks, Finnish Geodetic Institute, Geodeetinrinne 2, FI–02431 Masala, Finland E-mail: Anssi.Krooks@fgi.fi
-
Kaasalainen,
Finnish Geodetic Institute, Geodeetinrinne 2, FI–02431 Masala, Finland
E-mail:
Sanna.Kaasalainen@fgi.fi
- Kankare, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 Helsinki, Finland E-mail: ville.kankare@helsinki.fi
- Joensuu, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 Helsinki, Finland E-mail: marianna.joensuu@alumni.helsinki.fi
- Raumonen, Tampere University of Technology, Department of Mathematics, P.O. Box 553, Tampere, FI-33101, Finland E-mail: Pasi.Raumonen@tut.fi
- Kaasalainen, Tampere University of Technology, Department of Mathematics, P.O. Box 553, Tampere, FI-33101, Finland E-mail: Mikko.Kaasalainen@tut.fi
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