Data for investigating structural complexity of individual Scots pine trees
Date
2021-01-05Author(s)
Unique identifier
10.5281/zenodo.4419878Metadata
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Citation
Saarinen, Ninni,University of Helsinki, University of Eastern Finland. Calders, Kim,Ghent University. Kankare, Ville,University of Eastern Finland, University of Helsinki. Yrttimaa, Tuomas,University of Eastern Finland, University of Helsinki. Junttila, Samuli,University of Eastern Finland, University of Helsinki. Luoma, Ville,University of Helsinki. Huuskonen, Saija,Natural Resources Institute Finland. Hynynen, Jari,Natural Resources Institute Finland. Verbeeck, Hans,Ghent University. , Data for investigating structural complexity of individual Scots pine trees, 2021, 10.5281/zenodo.4419878.Abstract
Tree functional traits together with processes such as forest regeneration, growth, and mortality affect forest and tree structure. Forest management inherently impacts these processes. Moreover, forest structure, biodiversity, resilience, and carbon uptake can be sustained and enhanced with forest management activities. To assess structural complexity of individual trees, comprehensive and quantitative measures are needed, and they are often lacking for current forest management practices. Fractal analysis and a single scale, independent metric called box dimension offer means for assessing structural complexity of individual trees. Terrestrial laser scanning (TLS) point clouds provide three-dimensional (3D) information on trees that can be utilized in generating the box dimension metric. This data set includes information needed for generating the box dimension from 741 individual Scots pine (Pinus sylvestris L.) trees from 9 sample plots with different thinning treatments located in southern boreal forests. The thinning treatments include two intensities of thinning and control treatment (i.e., no thinning treatment since the establishment). The data set can be used in characterizing structural complexity of individual Scots pine trees of various size as well as assessing effects of various thinning treatments on it. Please see the data descriptor for more information on the data structure and its possibilities. Please keep the designated corresponding author informed of any plans to use the data. Consultation or collaboration with the original investigators is strongly encouraged. Publications and data products that make use of the data must include proper acknowledgement.
Subjects
box dimension growth and yield forest management silviculture terrestrial laser scanning ground-based LiDAR forest ecology tree structureLink to the original item
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