Study on extraction of apple tree height at different flight altitudes using multispectral UAV
[Objective]The purpose of this study is to utilize multispectral unmanned aerial vehicle(UAV)imagery to rapidly,accurately,and non-destructively acquire height information of apple trees,ai-ming to achieve monitoring of apple tree growth conditions using UAV remote sensing technology and analyze the influence of UAV flight height on the extraction results of tree height.[Methods]The DJI Phantom 4 multispectral UAV was employed to acquire UAV imagery of apple trees at flight heights of 30,60,and 90 m,respectively.The acquired imagery was processed using DJI Terra software to generate digital orthophoto mod-els(DOM)and digital surface models(DSM).Based on the generated DOM and DSM,a digital elevation model(DEM)of the study area was created using the Kriging interpolation method.The difference between the DSM and DEM was used to generate the canopy height model(CHM)for extracting tree height.Regres-sion analysis and accuracy validation were conducted by comparing the extracted tree heights with field-meas-ured values.[Results]The average accuracy of tree height extraction at a flight height of 30 m was 88.49％,with an R2 value of 0.8378 and an RMSE of 0.403,1 m.At a flight height of 60m,the average accuracy of tree height extraction was 74.72％,with an R2 value of 0.657,7 and an RMSE of 0.884,6 m.At a flight height of 90 m,the average accuracy of tree height extraction was 56.20％,with an R2 value of 0.527,3 and an RMSE of 1.476,7 m.[Conclusion]The use of multispectral UAV remote sensing technology enables the extraction of apple tree height possible.The extraction accuracy decreases with an increase in UAV flight height.The best results are obtained at a flight height of 30 m,while the poorest results are obtained at a flight height of 90 m.Within appropriate flight heights,multispectral UAV remote sensing technology can rapidly,accurately,and non-destructively monitor the growth conditions of orchard fruit trees,thereby improving the management efficiency for orchard operators.
万方数据
维普
