Forest inventory provides the fundamental information for all decision-making that are relevant to human interventions in forest ecosystems, including harvest planning, complementing nationally to 20 Be annual business. The wood quality information can be used for developing resource-efficient methods for optimizing tree acquisition, cutting and sawing. High benefits (at the level of 0.5Be ) can be obtained if quality of individual trees, indicated by attributes such as stem curve, size distribution, and damages can be characterised, and if accuracy and spatial coverage of volume estimations can be improved. In this project, we automate forest field inventory methodologies using unmanned aerial vehichle (UAV) laser scanning to derive tree quality information. The method allows further derivation of a number of quality-related attributes previously unavailable from inventory improving decision making in this nationally important industry.