Abstract

Accurate estimates of tree diameter, height, volume, and biomass are important for numerous economic and ecological applications. In this study, we report exponential equations to predict tree DBH (cm), stem volume over bark (VOB, m(3)), and total above-stump biomass (TASB, kg) using three varying levels of input data for Pinus radiata D. Don, Eucalyptus globulus Labill., and Eucalyptus nitens (H.Deane Maiden) Maiden planted trees. The three sets of input data included: (1) tree height (HT, m), (2) tree HT and ground projected living crown area (CA, m(2)), and (3) tree HT, CA, and additional stand parameters. The analysis was performed using a large dataset covering the range of distribution of the species in central Chile and included stands of varying ages and planting densities. The first set of equations using only HT were satisfactory with Adj-R-2 values ranging from 0.78 to 0.98 across all species and variables. For all three species, estimation of DBH, VOB, and TASB as a function of HT improved when CA was added as an additional independent variable, increasing Adj-R-2 and reducing RMSE. The inclusion of stand variables, such as age and stand density, also resulted in further improvement in model performance. The models reported in this study are a robust alternative for DBH, VOB, and TASB estimations on planted stands across a wide range of ages and densities, when height and CA are known, especially when input data are derived from remote sensing techniques.