湖北农业科学 ›› 2022, Vol. 61 ›› Issue (20): 179-181.doi: 10.14088/j.cnki.issn0439-8114.2022.20.034

• 信息工程 • 上一篇    下一篇

基于无人机遥感技术的玉米长势监测研究

陈成, 杨栋淏, 李亚强, 辛京达, 王建雄   

  1. 云南农业大学水利学院/云南省高校农业遥感与精准农业工程研究中心,昆明 650500
  • 收稿日期:2021-10-11 出版日期:2022-10-25 发布日期:2022-11-23
  • 通讯作者: 王建雄(1975-),男,教授,主要从事地理信息和遥感信息研究,(电子信箱)jianxiongw@126.com。
  • 作者简介:陈 成(1996-),男,云南昆明人,在读硕士研究生,研究方向为资源与环境遥感,(电话)15288118241(电子信箱)28231233@qq.com。
  • 基金资助:
    国家自然科学基金项目(41867040); 云南省自然科学基金项目(2020Y0177,2020Y186)

Study on maize growth monitoring based on UAV remote sensing technology

CHEN Cheng, YANG Dong-hao, LI Ya-qiang, XIN Jing-da, WANG Jian-xiong   

  1. College of Water Resources, Yunnan Agricultural University/Agricultural Remote Sensing and Precision Agriculture Engineering Research Center of Yunnan Provincial Universities, Kunming 650500, China
  • Received:2021-10-11 Online:2022-10-25 Published:2022-11-23

摘要: 利用大疆P4 Multispectral无人机对云南省昆明市安宁市3块种植不同品种玉米的试验地获取该区域玉米整个生长周期的光谱数据并对其进行长势监测,基于光谱数据构建玉米的归一化植被指数(Normalized difference vegetation index,NDVI)来评价玉米的长势情况。结果表明,玉米5个不同生长阶段中,试验地块1的玉米品种LD556要优于另外2个试验地块的玉米品种(XL、JD16),其中试验地块1 NDVI均值与最大值均高于另外2个试验地块。通过多光谱无人机对玉米的生长监测试验,相比较传统的地面监测要更加快捷与高效,能很大程度上减少财力与人力成本,也在一定程度上推动了精准农业的发展。

关键词: 玉米, 无人机遥感技术, 多光谱, 长势监测

Abstract: Using DJI P4 Multispectral UAV, the spectral data of maize in the whole growth period were obtained and the growth status was monitored in 3 experimental fields with different maize varieties in Anning, Kunming, Yunnan. Based on the spectral data, the normalized difference vegetation index (NDVI) of corn was constructed to evaluate the growth of corn. The results showed that the maize variety LD556 of test plot 1 in the five different growth stages of maize was better than the maize varieties of the other two test plots (XL, JD16), and the mean and maximum values of NDVI of test plot 1 were higher than those of the other two test plots. In this paper, compared with the traditional ground monitoring, the corn growth monitoring test by multi spectral UAV was more rapid and efficient, which could greatly reduce the financial and human costs, and also promote the development of precision agriculture to a certain extent.

Key words: corn, UAV remote sensing technology, multispectral, growth monitoring

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