Current automated forest investigation is facing a dilemma over how to achieve high tree- and plot-level completeness while maintaining a high cost and labor efficiency. This study tackles the challenge by exploring a new concept that enables an efficient fusion of aerial and terrestrial perspectives for digitizing and characterizing individual trees in forests through an Unmanned Aerial Vehicle (UAV) that flies above and under canopies in a single operation. The advantage of such concept is that the aerial perspective from the above-canopy UAV and the terrestrial perspective from the under-canopy UAV can be seamlessly integrated in one flight, thus grants the access to simultaneous high completeness, high efficiency, and low cost. In the experiment, an approximately 0.5 ha forest was covered in ca. 10 min from takeoff to landing. The GNSS-IMU based positioning supports a geometric accuracy of the produced point cloud that is equivalent to that of the mobile mapping systems, which leads to a 2–4 cm RMSE of the diameter at the breast height estimates, and a 4–7 cm RMSE of the stem curve estimates. Results of the experiment suggested that the integrated flight is capable of combining the high completeness of upper canopies from the above-canopy perspective and the high completeness of stems from the terrestrial perspective. Thus, it is a solution to combine the advantages of the terrestrial static, the mobile, and the above-canopy UAV observations, which is a promising step forward to achieve a fully autonomous in situ forest inventory. Future studies should be aimed to further improve the platform positioning, and to automatize the UAV operation.

中文翻译：

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上层和下层无人机激光扫描的无缝集成，用于森林调查

当前的自动化森林调查面临着如何在保持高成本和劳动效率的同时实现高树级和地块级完整性的难题。这项研究通过探索一种新概念解决了这一挑战，该新概念可以通过一次飞行中无人飞行器（UAV）有效地融合空中和地面视角，对森林中的树木进行数字化和特征化。这种概念的优点在于，可以将来自冠层以上无人机的空中视角和冠层下无人机的地面视角无缝集成在一个飞行中，从而可以同时获得高完整性，高效率和低成本。在实验中，大约0.5公顷的森林被覆盖 从起飞到着陆需要10分钟。基于GNSS-IMU的定位支持所产生的点云的几何精度，该精度与移动制图系统的几何精度相当，这导致在乳房高度估计处直径的2–4 cm RMSE和4–7 cm茎曲线估计值的RMSE。实验结果表明，综合飞行能够将上层冠层的高度完整性和地上层茎的高度完整性结合起来。因此，这是一种结合地面静态，移动和上方林冠无人机观测优势的解决方案，这是朝着实现完全自主的原地森林清单迈进的有希望的一步。未来的研究应旨在进一步改善平台定位，并使无人机操作自动化。