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Smart Agriculture ›› 2021, Vol. 3 ›› Issue (3): 129-138.doi: 10.12133/j.smartag.2021.3.3.202105-SA008

• 智能管理与控制 • 上一篇    下一篇

利用无人机影像监测不同生育阶段玉米群体株高的精度差异分析

杨进(), 明博, 杨飞, 许红根, 李璐璐, 高尚, 刘朝巍, 王克如, 李少昆()   

  1. 中国农业科学院作物科学研究所/农业农村部作物生理生态重点实验室,北京 100081
  • 收稿日期:2021-05-31 修回日期:2021-08-08 出版日期:2021-09-30
  • 基金项目:
    国家重点研发计划项目(2016YFD0300605);国家现代农业产业技术体系建设专项(CARS-02-25);中国农业科学院农业科技创新工程项目(CAAS-ZDRW202004)
  • 作者简介:杨 进(1995-),女,硕士,研究方向为精准农业及农业信息化。E-mail:1121506915@qq.com
  • 通信作者: 李少昆(1963-),男,博士,研究员,研究方向为玉米精准栽培与管理。电话:010-82108891。E-mail:lishaokun@caas.cn

The Accuracy Differences of Using Unmanned Aerial Vehicle Images Monitoring Maize Plant Height at Different Growth Stages

YANG Jin(), MING Bo, YANG Fei, XU Honggen, LI Lulu, GAO Shang, LIU Chaowei, WANG Keru, LI Shaokun()   

  1. Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Labrary of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs, Beijing 100081, China
  • Received:2021-05-31 Revised:2021-08-08 Online:2021-09-30
  • Foundation items:National Key Research and Development Program of China(2016YFD0300605);Special Fund Project for the Construction of Modern Agriculture Industry Technology System(CARS-02-25);Chinese Academy of Agricultural Sciences Innovation Project(CAAS-ZDRW202004)
  • About author:YANG Jin, E-mail:1121506915@qq.com
  • Corresponding author:LI Shaokun, E-mail:lishaokun@caas.cn

摘要:

为明确利用无人机影像监测玉米群体株高的精度及其影响因素,本研究基于无人机搭载光学成像设备构建大田玉米群体数字高程模型(Digital Elevation Model,DEM),研究不同生育时期下玉米群体株高监测的精度差异。针对3个玉米品种、8个播期处理构建的株高差异化群体,用多旋翼无人机搭载高清RGB相机和多光谱成像设备,采集试验区高清RGB和多光谱影像,获取玉米群体数字高程信息DEM和各处理区植株高度,分析不同品种和播期处理下基于无人机和人工测量株高间的相关关系。试验结果表明,高清RGB相机和多光谱成像设备获取的DEM均能反映玉米群体的高度差异。高清RGB相机的株高监测精度优于多光谱成像设备,但株高监测精度不足,难以反映玉米群体的较小株高差异。不同生育阶段对玉米株高监测精度具有较大影响,生育前期冠层尚未全部覆盖地表或生育后期植株衰老叶片枯黄下垂时,受裸露地表影响,群体株高被严重低估。本研究分析了影响无人机搭载成像设备监测玉米株高精度的因素,可为该方法应用于大田生产提供借鉴意义。

关键词: 精度差异, 无人机, 株高测定, 玉米, 多光谱

Abstract:

The digital elevation model (DEM) of maize population in field was constructed by using optical imaging equipment mounted on unmanned aerial vehicle (UAV) to study the accuracy difference of maize population height monitoring at different growth stages. Three cultivars and eight sowing date treatments were set up to structure maize population with different plant heights. A multi-rotor UAV with high-definition digital camera and multispectral imaging sensor was used to take RGB images and multispectral images in the experiment area on July 25th and August 27th, 2018, which were the biggest and smallest differences in plant height. The DEM data of maize population and canopy height were obtained with image pose correction, image mosaic, point cloud generation, and space reconstruction, et al. The canopy height and plant height were normalized, and the correlation between different cultivars and sowing date was analyzed based on UAV and manual plant height measurement. The feasibility of using DEM data of maize canopy to monitor the difference of plant height was clarified. The results showed that the height difference of maize population could be reflected by the digital elevation information obtained from high-definition RGB camera and multispectral camera. The plant height monitoring accuracy of HD RGB camera was higher than that of multispectral camera. However, the monitoring accuracy of plant height was not enough under the ready-made image equipment and treatment method. So, it was difficult to reflect the smaller plant height difference of maize population. Growth stage had a great influence on the monitoring of maize plant height. When the canopy of early growth stage has not completely covered the surface or the leaf yellow and withered in the later stage of growth. The plant height of the population affected by the exposed surface was seriously underestimated. In this study, the effects of UAV imaging equipment on monitoring maize plant height were analyzed. The influence factors can be used as reference for the application of the method in field production.

Key words: accuracy difference, UAV, monitoring plant height, maize, multispectral

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