Research on the detection method of fruit tree canopy structure information based on two-dimensional LiDAR
The acquisition of information regarding fruit tree canopy structure is essential for optimizing variable spray operations.In order to enable real-time data collection on canopy structure,a two-dimensional(2D)ground laser radar was employed to scan fruit trees with varying Leaf Area Index(LAI)in this study.Three-dimensional(3D)point cloud images of the fruit trees was generated by using MATLAB software,and was consistent with the actual tree morphology,which indicated a strong correlation between the point cloud data and structural information of the fruit tree.The results revealed that the relative errors of tree height and tree width measured by utilizing 2D LiDAR were 2.22％and 4.11％,respectively.However,the accuracy of tree thickness was found to be influenced by LAI,the relative measurement errors for thickness increased from 5.3％to 41.1％when LAI increased from 0 to 3.68.The predictive models for LAI were developed for frontal and dorsal scans,with equations of y=1.265x—0.313 7 and y=1.230 5x—0.338,respectively.F-test results highlighted significant differences among the samples,with model goodness of fit exceeding 0.9.This study offers valuable technical insights and model support for decision-making in orchard variable spray operations.
fruit treevariable sprayleaf area indexLiDARpoint cloud
万方数据
维普
