Forest vertical structure characterization using ground inventory data for the estimation of forest aboveground biomass

Abstract

A common method for estimating forest biomass is to measure forest height and apply allometric equations. However, changing forest density or structure heterogeneity increases the variability of the known allometric relationship. Here, we investigated the potential of allometric relationships based on vertical forest structure for biomass inversions with a global potential. First, vertical biomass profiles, which were calculated from ground forest inventory data, were used to model forest vertical structure. Then, a vertical structure ratio based on Legendre polynomials was proposed as a structural descriptor and its sensitivity to biomass was evaluated. Finally, we developed a structure-to-biomass inversion expression that could be extrapolated for aboveground biomass estimations. This is a case study based on inventory data from the Traunstein and Ebersberg test sites, two temperate forests located in southeastern Germany with different forest structural conditions. Results from the structure-to-biomass inversion algorithm show a clear improvement with respect to traditional height-to-biomass expressions, with increasing correlation factor (r2) from 0.52 to 0.73 for Traunstein and from 0.51 to 0.76 for Ebersberg and reducing the root mean square errors from 75.32 to 47.56 Mg·ha−1 and from 73.25 to 48.31 Mg·ha−1, respectively.