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Tree crown biomass is rarely assessed individually in forest monitoring, but when it is to be reported, standard conversion factors are commonly used for predicting crown biomass as a function of stem biomass. Further, in the conventional methods, the predicted total tree biomass is assigned exclusively to the stem position. In reality, however, tree and in particular crown biomass is spatially distributed over the entire crown projection area. In this study, we investigated the "Horizontal Biomass Distribution (HBD)" model, which serves to depict this biomass as a spatial distribution over the crown projection area: here, the individual tree crown biomass is modeled as a continuous distribution within the area defined by the crown projection. We examined two empirical HBD prediction models: (1) Weibull distribution; and (2) Segmented polynomial regression; which describe the biomass contained up to a given crown radius on the horizontal projection of individual trees, i.e., spatial distribution of crown biomass as a function of the horizontal distance from the stem. The approach was demonstrated using terrestrial laser scanning (TLS) on a sample of 33 urban trees from eight species. We found that (1) the segmented polynomial regression model revealed better performance in defining the HBD for various tree species; (2) a certain variability in HBD patterns was observed between the sample trees, with the variability being more pronounced between species groups than within species; and (3) the methodological approaches using TLS proxies are suitable and convenient to non-destructively assess the HBD, which would be otherwise impractical by direct measurements.
Bazezew et al. (Thu,) studied this question.