PWM offline variable application based on UAV remote sensing 3D prescription map

Precision application in orchards enhancing deposition uniformity and environmental sustainability by accurately matching nozzle output with canopy parameters. This study provides a pipeline for creating 3D prescription maps using a UAV and performing offline variable application. It also evaluates the accuracy of ground altitude measurements at various flight heights. At a flight height of 30 m, with a three-dimensional reconstruction method without phase-control points, the root mean square error (RMSE) for ground altitude measurement was 0.214 m and the mean absolute error (MAE) was 0.211 m; for the canopy area, these values were 0.591 m and 0.541 m, respectively. As flight height increased, the accuracy of altitude measurements declined and tended to be underestimated. Moreover, during offline variable spraying, the shape of the spray area influenced deposition accuracy, with collision detection area of a line segment achieving greater precision than conical ones. Field tests showed that the offline variable application method reduced pesticide usage by 32.43 % and enhanced spray uniformity. This newly developed process does not require costly sensors on each sprayer and has potential for field applications. • Built 3D prescription map with a multispectral drone and performing variable-rate spraying by a tracked sprayer. • Offline spraying without using costly sensors, enabling sustainability pesticide application in precision agriculture. • Evaluated prebuilt 3D map altitude accuracy and offline spraying precision, enhancing orchard management efficiency.

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Publication Details

Journal
Artificial Intelligence in Agriculture
Published
2025-01-27
DOI
https://doi.org/10.1016/j.aiia.2025.01.011
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
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article

PWM offline variable application based on UAV remote sensing 3D prescription map

Yajia Liu, Leng Han, Miao He, Xiongkui He et al.
Artificial Intelligence in Agriculture
Remote Sensing and LiDAR Applications
article

PWM offline variable application based on UAV remote sensing 3D prescription map

Yajia Liu, Leng Han, Miao He, Xiongkui He, Zhichong Wang
article en

Abstract

Precision application in orchards enhancing deposition uniformity and environmental sustainability by accurately matching nozzle output with canopy parameters. This study provides a pipeline for creating 3D prescription maps using a UAV and performing offline variable application. It also evaluates the accuracy of ground altitude measurements at various flight heights. At a flight height of 30 m, with a three-dimensional reconstruction method without phase-control points, the root mean square error (RMSE) for ground altitude measurement was 0.214 m and the mean absolute error (MAE) was 0.211 m; for the canopy area, these values were 0.591 m and 0.541 m, respectively. As flight height increased, the accuracy of altitude measurements declined and tended to be underestimated. Moreover, during offline variable spraying, the shape of the spray area influenced deposition accuracy, with collision detection area of a line segment achieving greater precision than conical ones. Field tests showed that the offline variable application method reduced pesticide usage by 32.43 % and enhanced spray uniformity. This newly developed process does not require costly sensors on each sprayer and has potential for field applications. • Built 3D prescription map with a multispectral drone and performing variable-rate spraying by a tracked sprayer. • Offline spraying without using costly sensors, enabling sustainability pesticide application in precision agriculture. • Evaluated prebuilt 3D map altitude accuracy and offline spraying precision, enhancing orchard management efficiency.

Artificial Intelligence in AgricultureVol. 15(3)
China Agricultural University (CN)
Affordable and clean energy
Openalex Percentile: Top 99%
Remote Sensing and LiDAR Applications
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