Department of Global Agricultural Sciences, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan.
Department of Agronomy, Faculty of Agriculture, University of Jaffna, Jaffna 40000, Sri Lanka.
Sensors (Basel). 2023 Dec 18;23(24):9907. doi: 10.3390/s23249907.
Old plantations are iconic sites, and estimating stand parameters is crucial for valuation and management. This study aimed to estimate stand parameters of a 115-year-old Japanese larch ( (Lamb.) Carrière) plantation at the University of Tokyo Hokkaido Forest (UTHF) in central Hokkaido, northern Japan, using unmanned aerial vehicle (UAV) photogrammetry. High-resolution RGB imagery was collected using a DJI Matrice 300 real-time kinematic (RTK) at altitudes of 80 and 120 m. Structure from motion (SfM) technology was applied to generate 3D point clouds and orthomosaics. We used different filtering methods, search radii, and window sizes for individual tree detection (ITD), and tree height (TH) and crown area (CA) were estimated from a canopy height model (CHM). Additionally, a freely available shiny R package (SRP) and manually digitalized CA were used. A multiple linear regression (MLR) model was used to estimate the diameter at breast height (DBH), stem volume (V), and carbon stock (CST). Higher accuracy was obtained for ITD (F-score: 0.8-0.87) and TH (R: 0.76-0.77; RMSE: 1.45-1.55 m) than for other stand parameters. Overall, the flying altitude of the UAV and selected filtering methods influenced the success of stand parameter estimation in old-aged plantations, with the UAV at 80 m generating more accurate results for ITD, CA, and DBH, while the UAV at 120 m produced higher accuracy for TH, V, and CST with Gaussian and mean filtering.
旧种植园是标志性的地点,估计林分参数对于评估和管理至关重要。本研究旨在利用无人机(UAV)摄影测量技术估算日本北海道大学北海道森林(UTHF)中一座 115 年生日本落叶松((Lamb.)Carrière)人工林的林分参数。在 80 和 120 米的高度使用 DJI Matrice 300 实时动态(RTK)采集高分辨率 RGB 图像。应用运动结构(SfM)技术生成 3D 点云和正射影像图。我们使用不同的滤波方法、搜索半径和窗口大小进行单木检测(ITD),并从冠层高度模型(CHM)估算树高(TH)和冠幅面积(CA)。此外,还使用了免费的 shiny R 包(SRP)和手动数字化的 CA。使用多元线性回归(MLR)模型估算胸径(DBH)、树干体积(V)和碳储量(CST)。ITD(F 分数:0.8-0.87)和 TH(R:0.76-0.77;RMSE:1.45-1.55 m)的精度高于其他林分参数。总体而言,无人机的飞行高度和所选的滤波方法会影响老龄种植林中林分参数估算的成功,在 80 米高度的无人机更适合 ITD、CA 和 DBH 的测量,而在 120 米高度的无人机使用高斯和均值滤波可以获得更高的 TH、V 和 CST 精度。