By Alvaro Iván Lau Sarmiento (Peru)
Tropical forests are some of the most complex terrestrial ecosystems in the world. It is crucial to assess its spatial structure, since it plays a major role in the exchange process of matter and energy between atmosphere and terrestrial above-ground carbons stocks and influences many biophysical processes. In order to accurate model these processes, tree allometry and branch architecture is needed, since researches are able to construct models which statistically infer tree parameters from these measurements. During these decades, researches regarding tropical forest have been concentrated on developing automated algorithms for forest inventories. T-LiDAR offers a potential for assessing vegetation structure, due to its capability to provide objective and consistent measurements. The main objective of this research is to evaluate if T-LiDAR is an alternative for measuring forest parameters in tropical forest. In order to do that, this research analysed the performance of T-LiDAR in a tree model approach, the QSM approach, in order to derive tree parameters, such as DBH, tree height, number of branches. Then, this research tested these parameters in a plant-scaling exponent metabolism, the WBE plant-scaling model. Our results
supported the use of T-LiDAR for assessing tropical trees structure. T-LiDAR can deliver a reliable 3D point cloud, which can be used for tree modelling. The branches resulting from the QSM approach were very accurate, compared to the original point cloud. For tree modelling, the QSM performance showed a high accuracy, with a low RMSE (up to 1.26 cm for radius parameter) for the first branches level, decreasing for smaller branches and top of the canopy; due to the fuzziness of the point cloud at far distances. Finally, the tree scaling metabolism derived from T-LiDAR scans revealed that the exponents found are not consistent with the theoretical values. This research is the first step on using T-LiDAR data from tropical forest into plant ecology and other ecological branches.
Keywords: Tree modelling; terrestrial LiDAR; plant scaling metabolism; tropical forest