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What good are unmanned aircraft systems for agricultural remote sensing and precision agriculture?

机译:用于农业遥感和精确农业的无人机系统有什么用?

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摘要

Remote sensing from unmanned aircraft systems (UAS) was expected to be an important new technology to assist farmers with precision agriculture, especially crop nutrient management. There are three advantages using UAS platforms compared to manned aircraft platforms with the same sensor for precision agriculture: (1) smaller ground sample distances, (2) incident light sensors for image calibration, and (3) canopy height models created from structure-from-motion point clouds. These developments hold promise for future data products. In order to better match vendor capabilities with farmer requirements, we classify applications into three general niches: (1) scouting for problems, (2) monitoring to prevent yield losses, and (3) planning crop management operations. The three different niches have different requirements for sensor calibration and have different costs of operation. Planning crop management operations may have the most environmental and economic benefits. However, a USDA Economic Research Report showed that only about 20% of farmers in the USA have adopted variable rate applicators; so, most farmers in the USA may not have the technology to benefit from management plans. In the near-term, monitoring to prevent yield losses from weeds, insects, and diseases may provide the most economic and environmental benefits, but the costs for data acquisition need to be reduced.
机译:预计无人机系统(UAS)的遥感技术将成为一项重要的新技术,可以帮助农民进行精准农业,尤其是作物养分管理。与配备有用于精确农业的相同传感器的有人驾驶飞机平台相比,使用UAS平台具有三个优势:(1)较小的地面样本距离;(2)用于图像校准的入射光传感器;(3)由“结构-距离”创建的机盖高度模型运动点云。这些发展为未来的数据产品带来了希望。为了使供应商的功能与农民的需求更好地匹配,我们将应用程序划分为三个基本方面:(1)探查问题;(2)进行监控以防止产量损失;以及(3)规划作物管理操作。这三个不同的利基市场对传感器校准有不同的要求,并且具有不同的运行成本。计划作物管理作业可能会带来最大的环境和经济效益。但是,美国农业部《经济研究报告》显示,在美国,只有约20%的农民采用了可变利率施药器。因此,美国大多数农民可能没有从管理计划中受益的技术。在短期内,进行监测以防止杂草,昆虫和疾病引起的产量损失可能会带来最大的经济和环境效益,但需要降低数据采集成本。

著录项

  • 来源
    《International journal of remote sensing》 |2018年第16期|5345-5376|共32页
  • 作者单位

    USDA ARS, Beltsville Agr Res Ctr, Hydrol & Remote Sensing Lab, 10300 Baltimore Ave,Bldg 007,Room 104, Beltsville, MD 20705 USA;

    USDA ARS, Beltsville Agr Res Ctr, Hydrol & Remote Sensing Lab, 10300 Baltimore Ave,Bldg 007,Room 104, Beltsville, MD 20705 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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