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

IF 12.4 Q1 AGRICULTURE, MULTIDISCIPLINARY
Leng Han , Zhichong Wang , Miao He , Yajia Liu , Xiongkui He
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引用次数: 0

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.
基于无人机遥感三维处方图的PWM离线变量应用
精确应用于果园,通过精确匹配喷嘴输出与冠层参数,提高沉积均匀性和环境可持续性。本研究提供了一个使用无人机创建3D处方地图并执行离线变量应用的管道。它还评估了不同飞行高度下地面高度测量的准确性。在飞行高度为30 m时,采用无相位控制点的三维重建方法,地面高度测量的均方根误差(RMSE)为0.214 m,平均绝对误差(MAE)为0.211 m;冠层面积分别为0.591 m和0.541 m。随着飞行高度的增加,高度测量的精度下降,往往被低估。此外,在离线变量喷涂过程中,喷涂区域的形状影响沉积精度,线段的碰撞检测区域比锥形的碰撞检测区域精度更高。田间试验结果表明,采用离线可变施药方法可减少32.43%的农药用量,提高喷雾均匀性。这种新开发的工艺不需要在每个喷雾器上安装昂贵的传感器,具有现场应用的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Artificial Intelligence in Agriculture
Artificial Intelligence in Agriculture Engineering-Engineering (miscellaneous)
CiteScore
21.60
自引率
0.00%
发文量
18
审稿时长
12 weeks
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