INDIVIDUAL TREE AGB ESTIMATION BASED ON FRACTAL PARAMETERS AND TREE VOLUME

Abstract

Forest is an important component of ecosystem. To estimate forest above-ground biomass (AGB) accurately, this paper proposed an individual tree AGB estimation method based on fractal geometry and individual tree volume. In this study, fractal parameters, such as fractal dimension and intercept were first calculated. And then, a fast tree volume estimation method based on point clouds voxelization was proposed. By combining fractal parameters, tree volume and specific wood density together, an individual tree AGB estimation method was developed. The datasets of three different tree species with harvest referenced AGB values were used for evaluating the performance of the developed model. Experimental results showed that the coefficient of determination (R2) of the developed model was 0.853. Compared with other four traditional allometric models, the proposed model performs the best no matter which accuracy indicator was adopted.