Articles containing the keyword 'tree models'
Category : Article
The single tree growth models presented in this study were based on about 4,000 trees measured in 50 even-aged Scots pine (Pinus sylvestris L.) sample plots with varying density, spatial pattern of trees and stand age. Predictors that used information about tree locations decreased the relative standard error of estimate by 10 percentage points (15%), if past growth was not used as a predictor, and about 15 percentage points (30%) when past growth was one of the predictors. When ranked according to the degree of determination, the best growth models were obtained for the basal area increment, the next best for relative growth, and the poorest for diameter increment. The past growth decreased the relative standard error of estimate by 15–20 percentage points, but did not make the spatial predictors unnecessary. The degree of determination of the spatial basal area growth model was almost 80% if the past growth was unknown and almost 90% if the past growth was known. Variables that described the amount of removed competition did not improve the growth models.
The PDF includes an abstract in Finnish.
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Pukkala,
E-mail:
tp@mm.unknown
The study presents two methods of predicting tree dimensions in a Scots pine (Pinus sylvestris L.) stand if only the location of trees is known. The first method predicts the tree diameter from the spatial location of neighbours. In the second method the diameter distribution of a subarea is estimated from the local stand density. This distribution is then sampled to obtain diameters. In both methods the tree height is predicted with a spatial model on the basis of diameters and locations of trees. The main purpose of the presented models is to generate realistic stands for simulation studies.
The PDF includes an abstract in Finnish.
-
Pukkala,
E-mail:
tp@mm.unknown
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