中国农业气象

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 无人机多光谱遥感监测水稻高温胁迫的关键技术

 石涛,杨太明,黄勇,李翔,刘琪,杨元建   

  1.  1.芜湖市气象局,芜湖 241000;2.安徽省农业气象中心,合肥 230000;3.安徽省气象科学研究所,合肥 230000; 4.太原龙翔森业有限公司,太原 030001;5.南京信息工程大学大气物理学院,南京 210044
  • 出版日期:2020-09-20 发布日期:2020-09-13
  • 作者简介:石涛,E-mail:stahau1987@163.com
  • 基金资助:
     国家重点研发计划项目(2018YFC1506502);安徽省气象科技发展基金(2017022)

 Key Technologies of Monitoring High Temperature Stress to Rice by Portable UAV Multi Spectral Remote Sensing

 SHI Tao, YANG Tai-ming, HUANG Yong, Li Xiang, LIU Qi, YANG Yuan-jian   

  1.  1.Wuhu Meteorological Administration, Wuhu 241000, China; 2.Anhui Agrometeorological Center, Hefei 230000; 3.Anhui Institute of Meteorological and Sciences, Hefei 230000; 4.Taiyuan Longxiang Forest Business Co., Ltd,Taiyuan 030001; 5.School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044
  • Online:2020-09-20 Published:2020-09-13
  • Supported by:
     

摘要:  选取长江中下游的芜湖地区超级水稻生产基地为试验区域,以2019年7月20日?8月9日连续高温日为试验时段,设计基于消费级无人机与便携式多光谱传感器的水稻长势遥感监测系统,并创建数据后处理分析与应用方法,对处于生育敏感期稻株的光谱特征进行研究,建立水稻高温胁迫的反演识别模型。结果表明:稻株植被指数与叶面积指数呈显著的指数关系,相关系数达到0.918,由此建立稻株叶面积指数反演模型,并进一步确定稻株出现高温胁迫的叶面积指数判别条件。利用叶面积指数反演模型和判别条件对实验区域内的水稻进行高温胁迫下的光谱特征提取与分析,结果显示,实验区域内15.3%的水稻受到了持续高温胁迫的影响,与农业部门田间调查事实相符,即实验区域内水稻灌浆率为82.2%。相对于传统人工田间调查和卫星遥感调查的作物长势监测方法,便携式无人机多光谱遥感监测技术具有空间分辨率高、可实时大范围监测、简单易行以及应用成本低等特点,利于普及与推广,在农作物自然灾害监测方面具有应用前景。

关键词:  , 无人机, 便携式多光谱传感器, 水稻, 高温胁迫, 遥感监测, 叶面积指数

Abstract:  Rice is an important cereal crop in the world and the most important food resource in China. Under the background of global warming, the degree and frequency of extreme high temperature heat waves are also increasing. From July to August every year, continuous high temperature weather with daily maximum temperature exceeding 35.0℃ often occurs in the middle and lower reaches of the Yangtze River affected by subtropical high. At this time, rice is in a sensitive period of growth and development, and continuous high temperature will seriously influences the physiological development of rice. Consequently, scientific and reasonable monitoring of the occurrence and development process of high temperature stress to rice is of great scientific significance and practical value for impact assessment of rice yield variation and agricultural production decisions in the context of global warming. At present, crop growth monitoring methods mainly rely on field investigation and satellite remote sensing. However, the traditional field investigation methods are time-consuming and labor-intensive, and the accuracy is also influenced by the subjective consciousness of investigators. In addition, satellite remote sensing also has some shortcomings, such as low spatial resolution, long transit period, cloud pollution and so on. So, the application technology research of real-time monitoring of crop growth using multi-spectral sensors carried by portable drones is an important supplement and improvement to the existing monitoring and investigation methods for high temperature stress to rice. In this paper, a remote sensing monitoring system for rice growth and data post-processing analysis and application methods were designed based on consumer-grade drones and portable multi-spectral sensors, and then Wuhu super rice production base in the middle and lower reaches of the Yangtze river was selected as the experimental area, and the continuous high temperature days from July 20 to August 9, 2019 was taken as the experimental period. Experimental results showed that there was a significant exponential relationship between the rice vegetation index and the leaf area index, with the correlation coefficient of 0.918, and then the inversion model of rice leaf area index was established. Finally, the discrimination conditions of leaf area index of rice under high temperature stress were further determined. The inversion model and discrimination conditions of leaf area index were used to extract and to analyze the spectral characteristics of rice under high temperature stress in the experimental area. During this continuous high temperature period, 15.3% of rice in the experimental area was damaged by the continuous high temperature stress, which is coincided with the reality from the field investigation conducted by agricultural department (i.e., the grain filling rate of rice was 82.2% in the experimental area). Compared with the traditional field survey and satellite remote sensing monitoring methods, the portable UAV multispectral remote sensing monitoring technology developed in this paper has advantages of high spatial resolution, real-time and large-scale monitoring and application of low cost, which is conducive to the popularization and promotion. It has a certain application prospect in the remote sensing monitoring of crop natural disasters.

Key words:  , UAV, Portable multispectral sensor, Rice, High temperature stress, Remote sensing monitoring, LAI

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