Silvilaser 2019 - Poster Presentations »
Tropical tree biomass equations from terrestrial LiDAR
Large uncertainties in tree and forest carbon estimates undermine countries’ efforts to accurately estimate aboveground biomass (AGB) for national monitoring, measurement, reporting and verification of emission reductions in forested landscapes. Biomass estimates, although much improved, still rely on destructive sampling; large trees are under-represented in datasets; crown dimensions are typically not considered, and allometric models are often inaccurate when transferred between regions – which all leads to uncertainties and systematic errors in biomass estimations.
We earlier used terrestrial laser scanning (TLS) to test the accuracy of existing models (Calders et al., 2015; Gonzalez et al., 2018), and now we propose the use of TLS to develop local allometric models without felling trees. Here we (1) assessed the accuracy of TLS-derived tree metrics (diameter at breast height - DBH, height, crown width, and AGB) and (2) developed local allometric models to estimate tree AGB in Guyana based on tree parameters obtained from TLS point clouds from 72 tropical trees and wood density. We validated our methods and models with data from 26 destructively harvested trees.
We found that TLS-derived DBH was slightly lower, total tree height was higher, and crown width and AGB were not different from field-measured values, even with the presence of hollow and irregularly shaped trees. The assessed pantropical models underestimated AGB by 5 to 13 %. An older pantropical model —Chave et al. (2005) without height— consistently performed best among the pantropical models tested (R2 = 0.89). Our best TLS-derived allometric models included crown diameter, and provided more accurate AGB estimates (R2 = 0.92–0.93) than traditional pantropical models (R2 = 0.85–0.89). Our methods also demonstrate that tree height is difficult to measure, and the inclusion of height in allometric models consistently worsened AGB estimates.
Our study has advanced the use of TLS methods to estimate tree metrics and explored the accuracy of field and TLS-derived methods to develop local allometric models. Interestingly, our study shows that locally developed models are not always better than pantropical models, but this could not be known without destructive or TLS-derived validation data on true AGB. Our findings support our goal of improving tropical forest biomass estimates and can be applied to upcoming remote sensing missions such as GEDI and BIOMASS.