Estimation of the volume of coarse woody debris in eucalyptus forest using LiDAR derived forest structure variables

CWD (coarse woody debris) plays an important role in nutrient cycling, habitat for species and more recently carbon accounting in forest ecosystems. LiDAR (light detection and ranging) technology has demonstrated utility in capturing forest structure information. This paper proposes an indirect method of assessing downed CWD using LiDAR derived forest structure variables. Fieldwork was conducted to measure CWD volume in an Eucalyptus forest in Tasmania. A GLM (generalized linear model) to statistically estimate CWD volume in the Eucalyptus forest was developed using a LiDAR derived FCS (forest characterisation scheme): the openings above the ground, low and medium vegetation, canopy cover, presence of understorey and mid-storey vegetation and high trees, and the vertical canopy density of high trees. Five structural variables were selected for the best model based on AIC (Akaike's Information Criterion) by stepwise selection. The applicability of the model was then compared to the outcome of model using field derived variables such as diameter at breast height of trees. The results show that the model using LiDAR derived variables better estimated the amount of CWD. It is concluded that LiDAR derived forest structural variables has the potential to predict the amount of downed CWD in Eucalyptus forest.