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

The aim of this study was to test different stem volume predictorsthat are capable of utilizing laser scanning-based canopy heightmetrics as independent variables. The three laser scanning-basedmethods compared were (1) a direct prediction model for thestem volume at plot level, (2) a volume prediction system basedon the modelled percentiles of the basal area diameter distribution,and (3) a parameter prediction method used to determinate Weibull-basedbasal area diameter distributions for the plot-level stem volumeprediction. The predicted volumes were also compared with field-measuredvolumes obtained with the Finnish conventional inventory bycompartments. The best results were obtained with the firstmethod, i.e. the model that predicts plot-level stem volumesdirectly, which is logical. Furthermore, the simulated reductionof point density of laser data had no effect on the accuracyof stem volume predictions. The percentile-based modelling ofdiameter distributions was applied, in particular, to the determinationof non-homogenous stand structure; using this method, it iseven possible to fit multimodal distributions. In terms of theaccuracy of the predicted plot-level stem volumes, the volumeprediction method based on modelled percentiles of basal areadiameter distributions was the second best, whereas the volumeprediction method based on the parameter prediction of the Weibull-basedbasal area diameter distributions resulted in slightly worseresults. However, the accuracies of the three laser-based volumeprediction methods tested were superior to the published resultsof spectral value-based remote sensing studies implemented usingdata collected from Finland. Furthermore, the accuracy of plot-levelstem volume estimates calculated from field assessments wasconsiderably weaker than the accuracy of the three volume predictionmethods that utilized measures obtained with laser scanning.