FGA: An Allometric Model for Revealing the Relationship Between Fractal Geometry and AGB Estimation

Above-ground biomass (AGB) is an important indicator for studying and understanding the ecological environment. However, the traditional AGB estimation methods using terrestrial LiDAR data still suffer from biases for different tree species or forest sites as well as low accuracy using the tree metrics. To overcome these challenges, this paper developed a novel model based on fractal geometry. Firstly, a theory was built to reveal the relationship between fractal geometry and AGB estimation. To realize this, three different theories were involved, including fractal theory, traditional AGB estimation theory and stem form factor theory. The allometric AGB estimation equation was then developed based on fractal geometry parameters (i.e., fractal dimension and intercept). To test the proposed model, 101 individual trees located at different forest sites with corresponding harvested reference AGBs were adopted. Experimental results show that the proposed model can achieve better AGB results when compared with traditional allometric equations built upon tree metrics. All the utilized accuracy indicators revealed that the proposed method was the best. Relative root mean square error (RMSE) was improved by 53%, 22% and 18% when compared with traditional allometric models built upon diameter at breast height (DBH), tree height and the combined two variables (DBH and tree height). Furthermore, the performance of the developed model was also analyzed towards different tree species and different leaves on or off conditions. Results indicated that the developed model can produce satisfactory performance.