Current issue: 58(1)

Under compilation: 58(2)

Scopus CiteScore 2021: 2.8
Scopus ranking of open access forestry journals: 8th
PlanS compliant
Silva Fennica 1926-1997
1990-1997
1980-1989
1970-1979
1960-1969
Acta Forestalia Fennica
1953-1968
1933-1952
1913-1932

Articles containing the keyword 'Gibbs point process'

Category : Research article

article id 562, category Research article
Tero Kokkila, Annikki Mäkelä, Eero Nikinmaa. (2002). A method for generating stand structures using Gibbs marked point process. Silva Fennica vol. 36 no. 1 article id 562. https://doi.org/10.14214/sf.562
Keywords: spatial distribution; stand simulation; Gibbs point process; Markov chain Monte Carlo
Abstract | View details | Full text in PDF | Author Info
Stand growth modelling based on single tree responses to their surroundings requires a description of the spatial structure of a stand. While such detailed information is rarely available from field measurements, a method to create it from more general stand variables is needed. A marked Gibbs point potential theory combined with Markov chain Monte Carlo (MCMC) random process was used to create a spatial configuration for any given number of trees. The trees are considered as charges rejecting each other and building ‘potential energy’. As an analogue of the potential energy in physical systems, the potential of a stand is defined in terms of size-dependent tree-to-tree interactions that can be thought of as related to resource depletion and competition. The idea that bigger trees induce larger potentials brings 3-dimensional effects into the system. Any feasible spatial structure is a state of the system, and the related potential can be calculated. The probability that a certain state occurs is assumed to be a decreasing function of its potential. Because more regular structures have lower potentials, by adjusting the steepness of the probability distribution the spatial structure can be allowed to have a lot of randomness (naturally regenerated stands) or forced to be very regular (planted stands). The MCMC algorithm is a numerical method of finding stand configurations that correspond to the expected level of the potential, given the size distribution of trees and the shape of the probability density function. The method also allows us to take into account spatial variation in the terrain. Some spots can be defined to have lower basic potential than others (ditch, planting furrow, etc.) in order to create areas of higher than average stocking density. A preliminary test of the method was conducted on two measured stands. The results suggest that the method could provide an efficient and flexible means of mimicking variable stand structures.
  • Kokkila, University of Helsinki, Department of Forest Ecology, P.O. Box 27, FIN-00014 Helsingin yliopisto, Finland E-mail: tero.kokkila@helsinki.fi (email)
  • Mäkelä, University of Helsinki, Department of Forest Ecology, P.O. Box 27, FIN-00014 Helsingin yliopisto, Finland E-mail: am@nn.fi
  • Nikinmaa, University of Helsinki, Department of Forest Ecology, P.O. Box 27, FIN-00014 Helsingin yliopisto, Finland E-mail: en@nn.fi

Register
Click this link to register to Silva Fennica.
Log in
If you are a registered user, log in to save your selected articles for later access.
Contents alert
Sign up to receive alerts of new content
Your selected articles