Kim Calders

Nondestructive estimates of above‐ground biomass using terrestrial laser scanning

Summary: Allometric equations are currently used to estimate above-ground biomass (AGB) based on the indirect relationship with tree parameters. Terrestrial laser scanning (TLS) can measure the canopy structure in 3D with high detail. In this study, we develop an approach to estimate AGB from TLS data, which does not need any prior information about allometry. We compare these estimates against destructively harvested AGB estimates and AGB derived from allometric equations. We also evaluate tree parameters, diameter at breast height (DBH) and tree height, estimated from traditional field inventory and TLS data. Tree height, DBH and AGB data are collected through traditional forest inventory, TLS and destructive sampling of 65 trees in a native Eucalypt Open Forest in Victoria, Australia. Single trees are extracted from the TLS data and quantitative structure models are used to estimate the tree volume directly from the point cloud data. AGB is inferred from these volumes and basic density information and is then compared with the estimates derived from allometric equations and destructive sampling. AGB estimates derived from TLS show a high agreement with the reference values from destructive sampling, with a concordance correlation coefficient (CCC) of 0·98. The agreement between AGB estimates from allometric equations and the reference is lower (CCC = 0·68-0·78). Our TLS approach shows a total AGB overestimation of 9·68% compared to an underestimation of 36·57-29·85% for the allometric equations. The error for AGB estimates using allometric equations increases exponentially with increasing DBH, whereas the error for AGB estimates from TLS is not dependent on DBH. The TLS method does not rely on indirect relationships with tree parameters or calibration data and shows better agreement with the reference data compared to estimates from allometric equations. Using 3D data also enables us to look at the height distributions of AGB, and we demonstrate that 80% of the AGB at plot level is located in the lower 60% of the trees for a Eucalypt Open Forest. This method can be applied in many forest types and can assist in the calibration and validation of broad-scale biomass maps.s

Bias in lidar-based canopy gap fraction estimates

Leaf area index and canopy gap fraction (GF) provide important information to forest managers regarding the ecological functioning and productivity of forest resources. Traditional measurements such as those obtained from hemispherical photography (HP) measure solar irradiation, penetrating the forest canopy, but do not provide information regarding the three-dimensional canopy structure. Terrestrial laser scanning (TLS) is an active sensor technology able to describe structural forest attributes by measuring interceptions of emitted laser pulses with the canopy and is able to record the spatial distribution of the foliage in three dimensions. However, due to the beam area of the laser, interceptions are detected more frequently than using conventional HP, and GF is typically underestimated. This study investigates the effects of laser beam area on the retrieval of GF by using morphological image processing to describe estimation bias as a function of canopy perimeters. The results show that, using canopy perimeter, improvements in correlation between HP and TLS can be achieved with an increase in the coefficient of determination R 2 up to 28% (from an original R 2 of 0.66 to an adjusted R 2 of 0.85).

Effects of clumping on modelling LiDAR waveforms in forest canopies

Empirical relations are frequently used to derive leaf area index (LAI). Such relations often make assumptions that make it hard to link the derived LAI to realistic trees and forest canopies. In previous work we developed a set of analytical expressions to describe LiDAR waveforms with only a limited number of assumptions based on radiative transfer. These expressions were a function of crown macro-structure and LAI. The expressions were successfully tested when applied on crown archetypes, but showed significant error when applied to more realistic crowns. In this study, we analyse the effect of clumping on inferring LAI from realistic trees. Despite the potential of the expressions to detect subtle changes in LAI, absolute inferred LAI values can be significantly off. However, the strong correlation between true and inferred LAI (R2 >; 0.97) for the two test cases in this study, allows for calibration of the inferred LAI values.