Determining an optimal model for processing lidar data at the plot level: Results for a Pinus radiata plantation in New South Wales, Australia

Abstract

Small-footprint, discrete return airborne laser scanning (ALS or lidar) data is increasingly being used by forest managers to assist forest inventories. In this study, airborne lidar and plot-based data were collected from a 5 000 ha study site within Green Hills State Forest, a Pinus radiata D.Don plantation in southern New South Wales, Australia. A series of area-based lidar metrics were extracted and modelled against four inventory attributes (mean tree height, stem density, basal area and stand volume) obtained from 63 ground plots. For all response variables, regression tree models had the best model fit compared to Random Forest and Bayesian Model Averaging modelling techniques. The be..