Abstract

BackgroundCurrent 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.ResultsIn 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.ConclusionsResults 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.

Highlights

  • Precise knowledge of the distribution of tree size, species, health, and growth is essential to all decisions that are relevant to forest ecosystems, ranging from the forest resource management to the protection of climate and biodiversity

  • Correctness, (2021) 8:10 completeness, efficiency and cost are equivalently important for the reference data collection, which directly determines the correctness of the decisions and policies that are reached, and is vital for forest owners, wood industries, ecological and environmental scientists, and governmental decision-makers in the field of bioeconomy, sustainability, and the climate and biodiversity protection

  • The feasibility of increasing stem visibility in above-canopy UAV laser scanning (ULS) using a low flight height was tested, and was reported to be capable to provide diameter at breast height (DBH) or volume estimates for big (DBH > 20 cm) trees or big branches with a comparable accuracy as that of the terrestrial laser scanning (TLS) systems in a few cases, e.g., (Brede et al 2017, 2019; Wieser et al 2017). These results indicated that the above canopy ULS is capable to provide stem parameters to certain extent, but was limited to sparse and matured forest stand

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Summary

Introduction

Precise knowledge of the distribution of tree size, species, health, and growth is essential to all decisions that are relevant to forest ecosystems, ranging from the forest resource management to the protection of climate and biodiversity. Possible systematic errors are found in some of the most important tree attributes using conventional methods, e.g., in tree height estimates (Wang et al 2019a; Jurjević et al 2020) These limitations and challenges inspired new advancements in the forest field data collection through remote sensing technologies. 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, grants the access to simultaneous high completeness, high efficiency, and low cost

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