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基于无人机遥感的不同施氮水稻光谱与植被指数分析
引用本文:裴信彪,吴和龙,马萍,严永峰,彭程,郝亮,白越. 基于无人机遥感的不同施氮水稻光谱与植被指数分析[J]. 中国光学, 2018, 11(5): 832-840. DOI: 10.3788/CO.20181105.0832
作者姓名:裴信彪  吴和龙  马萍  严永峰  彭程  郝亮  白越
作者单位:1. 中国科学院 长春光学精密机械与物理研究所, 吉林 长春 130033;2. 中国科学院大学, 北京 100039;3. 吉林省农业科学院 水稻研究所, 吉林 公主岭 136100
基金项目:国家自然科学基金项目(No.11372309,No.61304017);吉林省科技发展计划重点项目(No.20150204074GX,No.20160204010NY);省院合作科技专项资金项目(No.2017SYHZ0024);中科院青促会项目(No.2014192).
摘    要:卫星遥感空间分辨率低且易受大气、云层、雨雪等因素的影响。本文使用共轴十二旋翼无人机搭载光谱仪构成农情遥感系统。首先,给出自主设计的无人机结构和飞行控制系统,围绕飞行平台、控制系统、遥感载荷构建了多环节数据备份的无人机遥感数据采集系统;然后,试验测试4种施氮水平水稻的光谱指数变化规律;最后,通过试验数据分析可得:在可见光区水稻冠层光谱反射率随氮素水平增加而减小,在近红外区,光谱反射率一开始随氮素水平增加而增大,但氮素水平增大到一定程度后再增加氮素导致反射率降低。在4种氮素水平下,水稻植被指数RVI和NDVI由分蘖期到拔节期先增大,然后至抽穗期又逐渐减小,且抽穗期RVI和NDVI值小于其分蘖期RVI和NDVI值。试验表明以多旋翼无人机为平台搭载光谱仪器构成农情遥感监测系统用于反演作物植被指数方面是可行的。本文设计的无人机遥感数据采集系统能够有效、实时获取遥感信息,其获取的高空间分辨率和光谱分辨率的农田实时信息能够为作物长势的分析、健康状况的监测提供必要的数据支持。

关 键 词:无人机  数据采集  水稻植被指数  氮素
收稿时间:2017-12-14

Analysis of the spectrum and vegetation index of rice under different nitrogen levels based on unmanned aerial vehicle remote sensing
PEI Xin-biao,WU He-long,MA Ping,YAN Yong-feng,PENG Cheng,HAO Liang,BAI Yue. Analysis of the spectrum and vegetation index of rice under different nitrogen levels based on unmanned aerial vehicle remote sensing[J]. Chinese Optics, 2018, 11(5): 832-840. DOI: 10.3788/CO.20181105.0832
Authors:PEI Xin-biao  WU He-long  MA Ping  YAN Yong-feng  PENG Cheng  HAO Liang  BAI Yue
Affiliation:1. Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China;2. University of Chinese Academy of Sciences, Beijing 100039, China;3. Institute of Rice, Jilin Academy of Agriculture, Gongzhuling 136100, China
Abstract:Satellite remote sensing has low spatial resolution and is susceptible to the atmosphere, cloud layer, rain, and snow and so on. In this paper, the coaxial remote sensing system is constructed by using a coaxial 12-rotor unmanned aerial vehicle with spectrometer. Firstly, the self-designed UAV structure and flight control system are introduced, and a multi-link data backup UAV remote sensing data acquisition system is built around the flight platform, control system and remote sensing load. Then, the change of spectral index of four rices with different nitrogen levels is tested. Finally, by analyzing the experimental data, it can be obtained that the spectral reflectance of rice canopy decreases with the increase of nitrogen level in the visible region, and the spectral reflectance increases with the increase of nitrogen level in the near-infrared region. However, when the nitrogen level is increased to a certain extent, the increase of nitrogen will cause the reflectivity to decrease. Under the four nitrogen levels, the RVI and NDVI increased from tillering stage to jointing stage, then decreased gradually in heading stage, and the values of RVI and NDVI at heading stage are lower than those of RVI and NDVI in tillering stage. The test shows that the multi-rotor UAV platform equipped with a spectrometer composed of agricultural remote sensing monitoring system is feasible in the inversion of crop vegetation index. The UAV remote sensing data acquisition system designed in this paper can obtain remote sensing information effectively and in real time. The real time information of farmland with high spatial resolution and spectral resolution can provide necessary data support for crop growth analysis and health monitoring.
Keywords:unmanned aerial vehicle  multi link data backup  data acquisition  rice vegetation index  nitrogen
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