Abstract
Purpose
Apple tree volume is an important factor in apple quality control and spraying strategies. The measurement is a laborious task because of the complex structure of the apple tree. This study developed a technology for accurately estimating the apple tree volume from unmanned aerial vehicle-based multi-view three-dimensional reconstruction data using a novel concave hull by slices algorithm.
Method
The CloudCompare software was used to preprocess the 3D data and extract a single tree. The 3D point cloud data of the tree were divided into truncated cone-type small slices of a specific thickness. The area of each slice was calculated using the proposed concave hull by slices algorithm. The tree volume was calculated by summing the volume of slices. The proposed method was verified on ten apple trees by comparing the results obtained using the proposed method with those calculated by two existing methods.
Results
The proposed method provided the most accurate tree volume, while avoiding the influence of gaps and holes in the tree. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) were 8.07% and 0.55 m3, respectively.
Conclusion
These results indicate that the concave hull by slices method can be used to calculate the tree volume from 3D point cloud data more effectively. Tree volume mapping was achieved by combining the tree volume with the tree position.
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Funding
This work was supported by the Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry (IPET) through the Advanced Production Technology Development Program, funded by the Ministry of Agriculture, Food and Rural Affairs (MAFRA) (32003003).
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Dong, X., Kim, WY. & Lee, KH. Drone-Based Three-Dimensional Photogrammetry and Concave Hull by Slices Algorithm for Apple Tree Volume Mapping. J. Biosyst. Eng. 46, 474–484 (2021). https://doi.org/10.1007/s42853-021-00120-y
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DOI: https://doi.org/10.1007/s42853-021-00120-y