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Open AccessArticle

Growth Height Determination of Tree Walls for Precise Monitoring in Apple Fruit Production Using UAV Photogrammetry

1
Leibniz Institute for Agricultural Engineering and Bioeconomy, 14469 Potsdam, Germany
2
Technische Universität Berlin, Institut für Konstruktion, Mikro- und Medizintechnik, FG Agromechatronik, 10623 Berlin, Germany
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(10), 1656; https://doi.org/10.3390/rs12101656
Received: 30 March 2020 / Revised: 14 May 2020 / Accepted: 19 May 2020 / Published: 21 May 2020
(This article belongs to the Special Issue 3D Point Clouds for Agriculture Applications)
In apple cultivation, spatial information about phenotypic characteristics of tree walls would be beneficial for precise orchard management. Unmanned aerial vehicles (UAVs) can collect 3D structural information of ground surface objects at high resolution in a cost-effective and versatile way by using photogrammetry. The aim of this study is to delineate tree wall height information in an apple orchard applying a low-altitude flight pattern specifically designed for UAVs. This flight pattern implies small distances between the camera sensor and the tree walls when the camera is positioned in an oblique view toward the trees. In this way, it is assured that the depicted tree crown wall area will be largely covered with a larger ground sampling distance than that recorded from a nadir perspective, especially regarding the lower crown sections. Overlapping oblique view images were used to estimate 3D point cloud models by applying structure-from-motion (SfM) methods to calculate tree wall heights from them. The resulting height models were compared with ground-based light detection and ranging (LiDAR) data as reference. It was shown that the tree wall profiles from the UAV point clouds were strongly correlated with the LiDAR point clouds of two years (2018: R2 = 0.83; 2019: R2 = 0.88). However, underestimation of tree wall heights was detected with mean deviations of −0.11 m and −0.18 m for 2018 and 2019, respectively. This is attributed to the weaknesses of the UAV point clouds in resolving the very fine shoots of apple trees. Therefore, the shown approach is suitable for precise orchard management, but it underestimated vertical tree wall expanses, and widened tree gaps need to be accounted for. View Full-Text
Keywords: oblique view; structure from motion (SfM); 3D point cloud; unmanned aerial vehicle (UAV); LiDAR; site-specific; precision fruticulture; orchard; apple trees oblique view; structure from motion (SfM); 3D point cloud; unmanned aerial vehicle (UAV); LiDAR; site-specific; precision fruticulture; orchard; apple trees
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MDPI and ACS Style

Hobart, M.; Pflanz, M.; Weltzien, C.; Schirrmann, M. Growth Height Determination of Tree Walls for Precise Monitoring in Apple Fruit Production Using UAV Photogrammetry. Remote Sens. 2020, 12, 1656.

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