Abstract
Information on fruit tree canopies is important for decision making in orchard management, including irrigation, fertilization, spraying, and pruning. An unmanned aerial vehicle (UAV) imaging system was used to establish an orchard three-dimensional (3D) point-cloud model. A row-column detection method was developed based on the probability density estimation and rapid segmentation of the point-cloud data for each apple tree, through which the tree canopy height, H, width, W, and volume, V, were determined for remote orchard canopy evaluation. When the ground sampling distance (GSD) was in the range of 2.13 to 6.69 cm/px, the orchard point-cloud model had a measurement accuracy of 100.00% for the rows and 90.86% to 98.20% for the columns. The coefficient of determination, R2, was in the range of 0.8497 to 0.9376, 0.8103 to 0.9492, and 0.8032 to 0.9148, respectively, and the average relative error was in the range of 1.72% to 3.42%, 2.18% to 4.92%, and 7.90% to 13.69%, respectively, among the H, W, and V values measured manually and by UAV photogrammetry. The results showed that UAV visual imaging is suitable for 3D morphological remote canopy evaluations, facilitates orchard canopy informatization, and contributes substantially to efficient management and control of modern standard orchards.
Highlights
The canopy is the part of a fruit tree in contact with light and the external environment, and it represents the main site for photosynthesis and respiration
It is urgent that research on the measurement technology of canopy information in modern standard orchards is strengthened and a solid foundation is established for efficient orchard management and control
Based on the orchard point-cloud model generated by a unmanned aerial vehicle (UAV) photogrammetry system, the normal vectors of the ground fitted plane in the model were determined by sampling the ground point clouds in this study
Summary
The canopy is the part of a fruit tree in contact with light and the external environment, and it represents the main site for photosynthesis and respiration. Canopy information of fruit trees reflects the growth status and yield potential of fruit trees [1] and serves as an important basis for decision making in the production processes [2], including orchard canopy pruning [3], irrigation and fertilization [4], drug spraying [5], and management during flowering [6]. Traditional orchard management methods have a low degree of informatization, which leads to various problems, including low production efficiency, excessive use of water/fertilizers/pesticides, and serious pollution problems [2,4,5]. It is urgent that research on the measurement technology of canopy information in modern standard orchards is strengthened and a solid foundation is established for efficient orchard management and control.
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