2025/10/07 by Yannik Wardius, Christoph Gollob, Andreas Tockner +4 · 1 voice
Environmental Science · #Forest ecology and management #Remote Sensing and LiDAR Applications #Plant Water Relations and Carbon Dynamics
paper · pdf · doi:10.1080/13416979.2025.2568812
openalex publication_date 2025/10/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/06/15
Quercus serrata is a valuable deciduous oak native to East Asia. Despite its potential for producing high-quality wood, Quercus serrata remains underutilized in commercial forestry, mainly confined to traditional uses like shiitake mushroom cultivation. This study models its growth in Japan using Terrestrial Laser Scanning (TLS) data, applying crop tree models inspired by Central European practices on broadleaved species, and evaluating how varying automation levels in point cloud data processing affect model accuracy and forest management decisions. From data collected across 20 survey plots, we segmented 558 Quercus serrata trees, extracting parameters like diameter at breast height (at 1.3 m height, DBH), tree height (TH), crown diameter (CD), and branch-free bole length (BFBL) using semi-automated, automated, and manual measurements. We developed models for TH (semi-automated: pseudo R2 = 0.65, automated: pseudo R2 = 0.59), CD (semi-automated: pseudo R2 = 0.75, automated: pseudo R2 = 0.62), and BFBL (semi-automated: pseudo R2 = 0.33, automated: pseudo R2 = 0.27, manual: pseudo R2 = 0.49). Quercus serrata exhibited typical traits of a light-demanding oak, including early height growth and natural branch shedding. Using our models, we simulated forest management scenarios based on target DBH and annual radial increment (IR). We recommend adjusting tree spacing to address slow average IR (2.2 mm/yr) and implementing a two-phase system to enhance wood quality. Refining algorithms for BFBL measurements is critical, as discrepancies significantly impact management decisions like thinning timing and harvest volume.