Estimation of stand variables in Pinus radiata D. Don plantations using different LiDAR pulse densities

This study aimed to verify the validity of linear, power function and exponential models to estimate stand variables in Galician Atlantic forests of Pinus radiata D. Don using Light Detection and Ranging (LiDAR). These forests differ in structure and species composition from boreal forests, in which this methodology is fully developed. The models tested use LiDAR-derived canopy height and intensity distribution metrics as explanatory variables to predict the following stand attributes: mean height, dominant height, stand basal area, stand volume, stand crown biomass, stand stem biomass and stand aboveground biomass. Exponential models performed best in most cases, with goodness-of-fit statistics similar to those reported in the international literature for boreal forests. The coefficient of determination ranged from 0.44 (for stand crown biomass) to 0.87 (for dominant height), and the root mean square error/mean·100 ranged from 8.2 per cent (for dominant height) to 31.6 per cent (for stand stem biomass). Model precision did not essentially vary after reducing 94 per cent of the original point cloud, i.e. when laser pulse density was reduced from 8 pulses m−2 to only 0.5 pulses m−2.