Airborne laser estimation of forest biomass and leaf area and their relationship

Abstract

Accurate estimates of forest biomass and leaf area over extensive areas are crucial since they not only indicate carbon stock and rate of carbon sequestration but also predict future carbon budget. For this purpose, no other method of remote sensing can match Airborne Laser Altlmetry (ALA), which captures vertical profile of forest by combining the laser pulse reflections from canopy and ground. Although the functional relationship of this laser-generated profile area (8) and biomass (TV) is well established; W = a5 (a being regression coefficient), the relationship with Leaf Area Index (LA!) is still at infancy. In this research, I have derived LA! - S relationship, determined parameters of it and biomass equations based on ground truth measurement of actual leaf area and biomass. Subsequently LA! and biomass of Ehime University Experimental Forest (384 ha) were estimated by applying parameterized equations to the ALA data covering the entire forest. Using theoretical background of Beer-Lamberts law and dimensional analysis, regression of LA! on S was derived; LA! = L(l - e-bS), with L being the upper limit of LA! and b intrinsic rate of LA! increase. The laser data used in this study was obtained in September 2005 through a total of seven North-South laser profiling transect of about 4000m long and approximately 250m apart. Ground-measured biomass and LA! of 19 plots laid along laser transects were used to calibrate S, they were obtained by applying allometric equations developed from destructively sampled trees on the censused stern diameter at breast height (dbh) in each plot. Since ground survey was done in 2010, Gompertz growth equation, parameterized by existing study site forest inventory was used to adjust ground measures to correspond with laser estimates. Parameterized function of LA! on S was established in the form; LA! = 10.66(1 - e-O.096S) with a log-transformed significant correlation of 0.6 (p = 0.017) while that of Won Swas; W = 20.55, r = 0.8 (p < 0.0001). Ground-measured and laser estimated LAI were significantly correlated SInce; r = 0.6(p = 0.014) furthermore plot averages were 8.1 and 7.9 respectively. Actually, this proves legitimacy of the function which I derived. The RMSE of LA! estimated by derived LAl - S and ground based LAl - W relationships was the same at 1.6 showing also robustness of derived function. As expected from previous studies, laser estimate and ground-measured biomass were significantly correlated; r = 0.8 (p < 0.0001) . Entire estimation of forest biomass and LA! was 325.2 ton/ha and 8.3 respectively. In conclusion, I derived a function for LA! estimation of the entire forest. Moreover, forest biomass and LA! were estimated with high precision. However, research covers only a small area; hence future validation in larger areas may be necessary.