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The aim of this study was to test different stem volume predictors that are capable of utilizing laser scanning-based canopy height metrics as independent variables. The three laser scanning-based methods compared were (1) a direct prediction model for the stem volume at plot level, (2) a volume prediction system based on the modelled percentiles of the basal area diameter distribution, and (3) a parameter prediction method used to determinate Weibull-based basal area diameter distributions for the plot-level stem volume prediction. The predicted volumes were also compared with field-measured volumes obtained with the Finnish conventional inventory by compartments. The best results were obtained with the first method, i.e. the model that predicts plot-level stem volumes directly, which is logical. Furthermore, the simulated reduction of point density of laser data had no effect on the accuracy of stem volume predictions. The percentile-based modelling of diameter distributions was applied, in particular, to the determination of non-homogenous stand structure; using this method, it is even possible to fit multimodal distributions. In terms of the accuracy of the predicted plot-level stem volumes, the volume prediction method based on modelled percentiles of basal area diameter distributions was the second best, whereas the volume prediction method based on the parameter prediction of the Weibull-based basal area diameter distributions resulted in slightly worse results. However, the accuracies of the three laser-based volume prediction methods tested were superior to the published results of spectral value-based remote sensing studies implemented using data collected from Finland. Furthermore, the accuracy of plot-level stem volume estimates calculated from field assessments was considerably weaker than the accuracy of the three volume prediction methods that utilized measures obtained with laser scanning.

Estimation of stem volume using laser scanning-based canopy height metrics