Terrestrial Laser Scanning (TLS) in South African ecosystems

Savannas are heterogeneous ecosystems comprising a mix of woody vegetation and grasses. Most field-based inventory and remote sensing techniques are limited in accounting for lower stratum vegetation structure. Terrestrial Laser Scanning (TLS) offers a method for retrieving data for holistic Above-Ground Biomass (AGB) assessments and monitoring small and large-scale structural changes in vegetation. This thesis uses TLS for savanna vegetation analyses. First, non-destructive individual tree AGB was estimated using TLS data and 3D reconstructions based on Quantitative Structure Models (QSMs) on 969 trees. The 3D data were acquired using a Riegl VZ-1000 TLS. The results demonstrated that the AGB of savanna trees can be accurately modelled using QSMs and TLS. Secondly, savanna structural change varies spatially and temporally due to the interaction of biotic and abiotic drivers. An approach based on TLS and QSMs was implemented, allowing the investigation of complex tree parameters. The results indicated that integrating multi-temporal TLS with QSMs enables the precise quantification of structural gains and losses resulting from various interacting drivers, allowing for rapid assessments following an event. Lastly, the thesis discusses TLS data for individual tree analysis by comparing two segmentation methods based on the ecological theory for accurate tree extraction. The results indicated that both segmentation algorithms can accurately segment savanna trees, which is essential for efficient TLS data processing workflows. This work demonstrates that high-resolution TLS data and QSMs are crucial for developing tree-specific allometric equations for savannas and also allow for the precise quantification of tree structural gains and losses over time. The advancement of tree segmentation algorithms enables the accurate and rapid segmentation of large TLS-scanned plots. This work is essential for ecological monitoring and management of savanna ecosystems.