Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, 16500 Praha, Czech Republic.
Sensors (Basel). 2018 Jul 12;18(7):2245. doi: 10.3390/s18072245.
We evaluated two unmanned aerial systems (UASs), namely the DJI Phantom 4 Pro and DJI Mavic Pro, for 3D forest structure mapping of the forest stand interior with the use of close-range photogrammetry techniques. Assisted flights were performed within two research plots established in mature pure Norway spruce ( (L.) H. Karst.) and European beech ( L.) forest stands. Geotagged images were used to produce georeferenced 3D point clouds representing tree stem surfaces. With a flight height of 8 m above the ground, the stems were precisely modeled up to a height of 10 m, which represents a considerably larger portion of the stem when compared with terrestrial close-range photogrammetry. Accuracy of the point clouds was evaluated by comparing field-measured tree diameters at breast height (DBH) with diameter estimates derived from the point cloud using four different fitting methods, including the bounding circle, convex hull, least squares circle, and least squares ellipse methods. The accuracy of DBH estimation varied with the UAS model and the diameter fitting method utilized. With the Phantom 4 Pro and the least squares ellipse method to estimate diameter, the mean error of diameter estimates was -1.17 cm (-3.14%) and 0.27 cm (0.69%) for spruce and beech stands, respectively.
我们评估了两种无人机系统（UAS），即 DJI Phantom 4 Pro 和 DJI Mavic Pro，用于使用近景摄影测量技术对森林林分内的三维森林结构进行测绘。在两个成熟的纯挪威云杉（(L.) H. Karst.）和欧洲山毛榉（ L.）林分中建立的两个研究地块内进行了辅助飞行。地理标记的图像用于生成代表树干表面的地理参考 3D 点云。在离地 8 米的飞行高度，精确地建模了高达 10 米的树干，与地面近景摄影测量相比，这代表了树干的相当大的一部分。通过将地面实测的胸径（DBH）与使用四种不同拟合方法（包括边界圆、凸壳、最小二乘圆和最小二乘椭圆方法）从点云中得出的直径估计值进行比较，评估了点云的精度。DBH 估计的准确性随 UAS 模型和所使用的直径拟合方法而变化。使用 Phantom 4 Pro 和最小二乘椭圆方法来估计直径，云杉和山毛榉林分的直径估计的平均误差分别为-1.17 厘米（-3.14%）和 0.27 厘米（0.69%）。
