Modelling variation in Pinus radiata stem volume and outerwood stress-wave velocity from LiDAR metrics

Linear and non-linear models were developed to predict TSV and V. Models of TSV were developed from the full dataset that included 163 plots while models of V were developed from a subset of 32 plots in which V had been measured.The best statistical models that included only LiDAR data, explained 60% and 37% of the variation in TSV and V, respectively. Addition of measured stand density to both models significantly improved the R2 to, respectively, 0.76 and 0.70 for TSV and V. The root-mean square error for the final models of TSV and V were, respectively, 64.0 m3 ha-1 and 0.086 km s-1.At the forest level LiDAR metrics were found to be useful for predicting both V and TSV. Further research should examine the link between LiDAR metrics and V across broader ranges of V to confirm these findings.