Quantification of Tropical Forest Biomass with Terrestrial LiDAR and 3D Tree Quantitative Structure Modelling
Research output: Other conference contribution › Paper, poster or abstract › Scientific
|Publication status||Published - May 2016|
|Event||Living Planet Symposium 2016 - Prague, Czech Republic|
Duration: 9 May 2016 → 13 May 2016
|Conference||Living Planet Symposium 2016|
|Period||9/05/16 → 13/05/16|
Terrestrial LiDAR Scanner (TLS) data, in contrast, has been demonstrated to be more accurate for inferring forest aboveground biomass (AGB) in a non-destructive and more direct estimation approach . The method consists of measuring tree wood volume by modelling the 3D tree architecture reconstructed with TLS data  and converted to biomass using specific wood density. This novel approach was first applied and validated in an open Eucalyptus forest in Australia . However, the application of this method for tropical forest present major challenges, mostly related to the high levels of occlusion due to large vegetation density and structural complexity. This is especially acute for very large trees that tend to be emerging above the main canopy, increasing the level of occlusion. To the best of our knowledge, the current study is the first one validating the accuracy of the use of TLS data and the 3D tree QSM to assess AGB in tropical forest.
Twenty nine plots where stablished in three study sites: in the south-western Amazon, (Peru), north-eastern Amazon (Guyana) and southern Borneo (Indonesia). Forest inventory data was collected in the 29 plots where 38 trees were harvested in total. Plots of 30x50m (9 in Peru) and 30x40m (10 in Indonesia and 10 in Guyana) were installed around a major tree to be harvested. For validation of individual AGB of harvested trees, a reference dataset was produced by estimating the tree volume from detailed geometric measurements of the stem and all branches (until 10 cm diameter), and converted to biomass using its specific wood basic density. TLS data was acquired in the 29 plots before and after harvest using a Riegl VZ 400 scanner. To compare with current methods, AGB estimations were computed using the most local specific allometric models and the most recent pan-tropical models .
Preliminary results were calculated for the first site (Peru). The AGB estimates by the TLS-QSM model outperformed the allometric models tested (see Table 1 in supplementary information). The gain in the accuracy achieved by the TLS-QSM method in relation to the pan-tropical allometric model  was a 9.8% decrease in CV RMSE. This represents a similar gain in accuracy as the one reported by Calders et al . Moreover, the bias of the TLS-QSM method was lower than the allometric methods, minimizing the underestimation of AGB of large trees.
We conclude that the proposed method (TLS-QSM) can be used to estimate AGB of large trees in tropical forests more accurately than allometric models tested, even under very unfavourable conditions (very large and complex tree crowns, within a great vegetation density, and above the main forest canopy).