One of the greatest challenges in the REDD+ mechanism is to effectively and accurately measure and monitor forest above-ground biomass (AGB) and its changes in tropics. The most accurate method of estimating AGB is to physically sample trees, however it is time and resource consuming. Another approach is applying allometric equations, widely used for estimating AGB in homogeneous systems. Due to the complexity and the great number of different tree species in tropical forests, and despite of the many studies, not much has been achieved. Airborne and space-borne sensors have been used for regional-scale estimations. Nevertheless, resolution and accuracy are insufficient to derive detailed AGB estimates and these method have limitations due to closed canopies and high-biomass density, mainly because AGB is a 3D measurement, while most remote sensing datasets are 2D structured.
Terrestrial Laser Scanning (TLS) with automatic data processing techniques has emerged as a potential technique, able to bind conventional forest inventory and remote sensing. Not only has TLS been used to estimate AGB from 3D reconstruction, but it also has an unexplored potential where tree architecture plays a major role. The aim of this PhD study is to assess the ability of TLS to derive tree characteristics in a more accurate, non-destructive and objective approach. For this, three topics will be discussed and methods will be developed: 1) biomass estimation; 2) biomass change and 3) plant scaling modelling.
TLS, in combination with automated data processing techniques, poses as a powerful alternative to the present techniques for estimating tree characteristics in tropical forest trees. Further, TLS has the ability to capture tree structure in a fast and replicable way. For these reasons, the main goal of this PhD programme is to assess the ability of TLS to derive tree characteristics in a more accurate, non-destructive and objective approach.
In order to assess the potential of TLS in tropical forest, I proposed three research objectives (Figure 1). Under the first research objective I will estimate biomass from different approaches. Under the second research objective I will assess biomass change from two perspectives: selectively harvested plots and canopy gaps. These two research objectives explore TLS’s potential to estimate biomass from tree modelling. However, TLS has an unexplored potential to describe the complex shape and structure of trees, especially in research where tree architecture plays a major role. Thus, under my third research objective I will assess TLS potential to estimate plant-scaling laws in tropical forest trees. Research under the third research objective could become a landmark in forest ecology, where very little has been investigated on how TLS can improve present methods for calculating branch and tree architecture.