Bayes trees and forests: combining precise empirical and theoretical tree models
Keywords:
Tree models, empirical, tree models, theoretical, TLS, Bayesian inference
Abstract
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.
Published
2013-06-03
Issue
Section
1B Reconstructing and observing plant structure
Authors who publish with this proceedings volume agree to the following terms:
- Authors retain copyright and grant the Conference organisers right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this proceedings volume.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the proceeding's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this proceedings volume.