Bayes trees and forests: combining precise empirical and theoretical tree models

  • Mikko Kaasalainen Tampere University of Technology
  • Ilya Potapov TUT
  • Pasi Raumonen TUT
  • Markku Åkerblom TUT
  • Risto Sievänen Metla
  • Sanna Kaasalainen FGI
Keywords: Tree models, empirical, tree models, theoretical, TLS, Bayesian inference


With the new analysis methods for TLS scans, there will be a growing and improving database of 3D descriptions of trees and forest stands. The attributes determining these descriptions can be represented as Bayesian probability distributions, with functional-structural models providing the prior information. These distributions can then be used to create versions of new realistic Bayes forests, where none of the trees are copied from data, but the structure of each is drawn from the data-based distributions. Repeated TLS measurements add a fourth dimension, time, to the mathematical modelling; in this way, we can simulate functional 4D Bayes forests. As in the modelling of the 3D structure, forest models and regularities of growth and mortality are used as prior information; conversely, the accumulating data and modelling results improve the theoretical models.

Author Biography

Mikko Kaasalainen, Tampere University of Technology
Professor, Department of Mathematics
1B Reconstructing and observing plant structure