Department of Forestry, Faculty of Agricultural and Natural Resources, Lorestan University, Khorramabad, Lorestan, 68151-44316, Iran.
Department of Geodesy and Geoinformation, Technische Universität Wien, Vienna, Austria.
Environ Monit Assess. 2022 Jul 30;194(9):625. doi: 10.1007/s10661-022-10294-3.
Today, different methods are used to measure two-dimensional (2D) and three-dimensional (3D) attributes of trees. One of these methods, which is considered in recent years is using point clouds and a 3D model extracted from terrestrial photogrammetry (TP). This study aims to estimate the 2D and 3D attributes of urban trees at three levels of seedlings, single trees and sample plot using TP. Structure-from-Motion with Multi-View Stereo-photogrammetry (SfM-MVS) method was used to derive the point clouds and the 3D model. Comparing estimated values of diameter at the middle of trunk of seedlings and diameter at breast height (DBH) of trees, using TP with measured values showed that the values of RMSE% were < 2% at three levels of seedlings, single trees and sample plot. Furthermore, validation of the estimated values of total height and crown height attributes of seedlings and trees at three levels showed that the RMSE% did not exceed 4% and 5%, respectively. Considering the overlap of tree crowns with each other in the sample plot, the average diameter of the crown attribute was estimated only in seedlings and single tree levels with RMSE% = 6.51% and 9.34%, respectively. The validation of estimated values of stem volume of seedlings and trees at three levels showed that the lowest errors were returned from trees within a sample plot with RMSE% = 14.37%, whereas the highest rates of errors were achieved for seedlings with RMSE% = 20.99%. As an alternative to approaches such as employing laser scanners, this method is quick, inexpensive, non-destructive, and does not need specialized equipment.
目前，有多种方法可用于测量树木的二维（2D）和三维（3D）属性。近年来，其中一种方法是利用点云和从地面摄影测量（TP）中提取的 3D 模型。本研究旨在利用 TP 估算城市树木在幼苗、单株和样地三个层次的 2D 和 3D 属性。使用多视图立体摄影测量（SfM-MVS）方法的运动结构（SfM）方法用于推导出点云和 3D 模型。通过将幼苗树干中部直径和树木胸径（DBH）的实测值与 TP 估算值进行比较，结果表明在幼苗、单株和样地三个层次上，RMSE%值均<2%。此外，对幼苗和树木在三个层次上的总高度和冠高属性的估算值进行验证的结果表明，RMSE%分别不超过 4%和 5%。考虑到样地中树冠相互重叠，仅在幼苗和单株层次上估算了冠属性的平均直径，RMSE%分别为 6.51%和 9.34%。对幼苗和树木在三个层次上的树干体积估算值进行验证的结果表明，样地内树木的误差最小，RMSE%为 14.37%，而幼苗的误差最大，RMSE%为 20.99%。与使用激光扫描仪等方法相比，该方法快速、廉价、非破坏性，且不需要专门设备。
