Abstract. Tree volume estimation is fundamental to forest management and inventory, yet traditional methods rely on allometric equations that introduce significant uncertainties due to generalized relationships and measurement limitations. This study evaluates the accuracy of mobile personal laser scanning (PLS) technology for tree volume estimation in pedunculate oak (Quercus robur L.) forests through a controlled comparison framework. Field work was conducted in January 2025 under optimal leaf-off conditions in a lowland oak stand in central Croatia. Three morphologically typical mature oak trees were selected within a single plot to enable controlled comparison while minimizing environmental variability. Data was acquired using PLS Faro Orbis Scanner, emphasizing complete stem coverage from multiple azimuths to support robust SLAM trajectory estimation and minimize occlusion effects. Three principal volume estimation approaches were evaluated: (i) sectioning volume obtained after felling, serving as the operational reference; (ii) PLS Schumacher-Hall volume, computed from LiDAR derived DBH and total height using established allometric relationships; and (iii) PLS Trunk Volume, computed directly from point cloud data using LiDAR360's trunk slicing workflow. Following PLS data acquisition, target trees were felled and bucked into contiguous sections, with length and end diameters recorded for each section to compute reference volumes. The sectioning dataset was treated as an operational reference rather than absolute ground truth, acknowledging potential reconstruction errors due to field conditions and occasional stem breakage. The study reveals important trade offs between measurement accuracy, operational efficiency, and methodological complexity, with sectioning volume providing the most direct measurement approach by eliminating remote sensing processing uncertainties. The research establishes a robust methodological framework for evaluating PLS performance in oak forests while highlighting both significant potential and current limitations of mobile laser scanning for operational forest inventory applications.
Seitz et al. (Tue,) studied this question.