Forest inventories provide significant monitoring information on forest health, biodiversity, resilience against disturbance, as well as its biomass and timber harvesting potential. For this purpose, modern inventories increasingly exploit the advantages of airborne laser scanning (ALS) and terrestrial laser scanning (TLS). Although tree crown detection and delineation using ALS can be seen as a mature discipline, the identification of individual stems is a rarely addressed task. In particular, the informative value of the stem attributes—especially the inclination characteristics—is hardly known. In addition, a lack of tools for the processing and fusion of forest-related data sources can be identified. The given thesis addresses these research gaps in four peer-reviewed papers, while a focus is set on the suitability of ALS data for the detection and analysis of tree stems. In addition to providing a novel post-processing strategy for geo-referencing forest inventory plots, the thesis could show that ALS-based stem detections are very reliable and their positions are accurate. In particular, the stems have shown to be suited to study prevailing trunk inclination angles and orientations, while a species-specific down-slope inclination of the tree stems and a leeward orientation of conifers could be observed.