Airborne LiDAR derived canopy height model reveals a significant difference in radiata pine ('Pinus radiata' D. Don) heights based on slope and aspect of sites.

Abstract

Accurate information on tree height distribution can provide a better understanding of forest productivity and biomass estimation. Airborne light detection and ranging remote sensing, also known as airborne laser scanning (ALS), has proven to be an effective tool for deriving tree height information in forests. While tree height has been reported to vary in response to many environmental factors, few researchers have demonstrated the effect of topography on tree height variation using ALS data. This study investigated the relationship between tree height variation and ALS-derived topographic aspect and slope factors within two even-aged radiata pine ('Pinus radiata' D. Don) plantation sites in Nundle, New South Wales, Australia. A total of 447 trees was sampled from 77 plots in two plantation age classes: 193 trees from a 34-year-old site and 254 trees from a 9-year-old site. ALS height estimates were highly correlated with field heights (R² = 0.90 and RMSE = 0.66 for 2002 and R² = 0.87 and RMSE = 1.49 for 1977 sites). ALS-derived slope and aspect metrics were shown to have a significant relationship with height variation across the stands. The slope (P<0.01) and aspect (P<0.001) were significant in the mixed linear models. Overall taller trees were found on slopes below 10° and on southerly aspects, while shorter trees dominated steeper slopes (>20°) and on northerly aspects. However, aspect gradient appeared to have more significant effect on tree heights than slope classes. These results were further verified using an additional 2,000 randomly located trees sampled across the plantations. The study demonstrates a significant relationship between tree height variation and ALS-derived ground aspect and slope categories which may have potential benefits for improving current wood resource inventories and future productivity models.