Supporting data for "Bayes Forest: a data-intensive generator of morphological tree clones"

Dataset type: Software
Data released on August 14, 2017

Potapov I; Järvenpää M; Åkerblom M; Raumonen P; Kaasalainen M (2017): Supporting data for "Bayes Forest: a data-intensive generator of morphological tree clones" GigaScience Database. http://dx.doi.org/10.5524/100337

DOI10.5524/100337

Detailed and realistic tree form generators have numerous applications in ecology and forestry. For example, varying morphology of trees contribute differently to formation of landscapes, natural habitats of species, and eco-physiological characteristics of the biosphere.
Here, we present an algorithm for generating morphological tree “clones” based on the detailed reconstruction of the laser scanning data, statistical measure of similarity, and a plant growth model with simple stochastic rules. The algorithm is designed to produce tree forms, i.e. morphological clones, similar (and not identical) in respect of tree-level structure, but varying in fine-scale structural detail. Although we opted for certain choices in our algorithm, individual parts may vary depending on the application, making it a general adaptable pipeline. Namely, we showed that a specific multi-purpose procedural stochastic growth model can be algorithmically adjusted to produce the morphological clones replicated from the target, experimentally measured tree. For this, we developed a statistical measure of similarity (structural distance) between any given pair of trees, which allows for the comprehensive comparing of the tree morphologies by means of empirical distributions describing geometrical and topological features of a tree. Finally, we developed a programmable interface to manipulate data required by the algorithm.
Our algorithm can be used in a variety of applications for exploration of the morphological potential of the growth models (both theoretical and experimental), arising in all sectors of plant science research.

Additional details

Read the peer-reviewed publication(s):

(PubMed: 29020742)

Additional information:

https://github.com/inuritdino/BayesForest





Sample IDTaxonomic IDCommon NameGenbank NameScientific NameSample Attributes
Norway maple tree4025 Norway mapleAcer platanoides Description:Laser scan of a maple tree, 2011
Geographic location (latitude and longitude):60Â...
Geographic location (country and/or sea,region):Fi...
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Displaying 1-1 of 1 Sample(s).




File NameSample IDData TypeFile FormatSizeRelease Date 
GitHub archivearchive157.78 KB2017-08-09
Mixed archiveGZIP7.58 MB2017-08-09
ImageJPG246.66 KB2017-08-09
ReadmeTEXT2.33 KB2017-08-09
Displaying 1-4 of 4 File(s).
Funding body Awardee Award ID Comments
Academy of Finland M Kaasalainen 250215 Centre of Excellence in Inverse Problems
Date Action
August 14, 2017 Dataset publish
October 2, 2017 Manuscript Link added : 10.1093/gigascience/gix079
November 9, 2022 Manuscript Link updated : 10.1093/gigascience/gix079