Simulation of structural timber properties based on geographical data and stand-level forest inventory data. Issue 5 (17th August 2020)

• Record Type: Journal Article
• Authors: Vestøl, Geir I.; Fischer, Carolin; Høibø, Olav
• Is Part Of: Scandinavian journal of forest research. Volume 35:Issue 5/6(2020)
• Page Start: 286
• Page End: 295
• Publication Date: 2020-08-17
• Subjects: Bending strength -- density -- modulus of elasticity -- Monte Carlo simulation -- Norway spruce -- Picea abies; Forests and forestry -- Scandinavia -- Periodicals; Forests and forestry -- Periodicals; Forests and forestry -- Research -- Scandinavia -- Periodicals; 634.90948
• DOI: 10.1080/02827581.2020.1799067
• Languages: English
• ISSNs: 0282-7581

Abstract

ABSTRACT: A method for simulation of distributions of structural timber properties based on geographical data and stand-level forest inventory data is presented. The method is based on Monte Carlo simulation of randomly selected sites from volume distributions of standing timber, in our case from the Norwegian National Forest Inventory. Simulation models of density, modulus of elasticity and bending strength were estimated from data from 2369 boards of Norway spruce from 27 sites in Norway. The models were estimated as mixed models including covariate models with fixed effects of latitude, altitude, site index and stand age, random site effects and residual variances, representing the within-site variances. Correlations between the simulated properties were obtained by transformation of the random effects in the simulations. The transformations were based on Cholesky decomposition of the correlation matrices of the random site-effects and the residuals of the simulation models. The simulations provide distributions for timber from each selected site and from all selected sites within defined areas, with different limitations on geographical data and stand-level forest inventory data. Simulations of Norway spruce from Eastern Norway are presented for demonstration, comparing timber from maturity classes, altitudes and site indices.