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近地高光谱和低空航拍数字图像遥感 监测小麦条锈病的比较研究
引用本文:刘伟,杨共强,徐飞,乔红波,范洁茹,宋玉立,周益林.近地高光谱和低空航拍数字图像遥感 监测小麦条锈病的比较研究[J].植物病理学报,2018,48(2):223-227.
作者姓名:刘伟  杨共强  徐飞  乔红波  范洁茹  宋玉立  周益林
作者单位:中国农业科学院植物保护研究所/植物病虫害生物学国家重点实验室,北京 100193;
河南省农业科学院植物保护研究所/农业部华北南部作物有害生物综合治理重点实验室,郑州 450002;
河南农业大学信息与管理科学学院,郑州 450046
基金项目:国家重点研发计划(2016YFD0300702);国家重点基础研究发展计划(2013CB127704)
摘    要: 分别利用近地高光谱和低空航拍数字图像同时对田间小麦条锈病的发生情况进行监测,结果表明近地高光谱遥感参数DVI、NDVI、GNDVI和低空航拍数字图像颜色特征值R、G、B与病情指数存在极显著相关性,整体上,所选近地高光谱参数与病情指数的相关性要优于低空航拍数字图像参数与病情指数的相关性,而且近地高光谱参数DVI、NDVI、GNDVI与低空航拍数字图像参数R、G、B之间均存在极显著负相关关系。分别建立了基于近地高光谱参数GNDVI和低空航拍数字图像参数R的田间小麦条锈病病情估计模型,模型均达到较好的拟合效果,其中近地高光谱参数GNDVI对小麦条锈病的监测效果好于低空航拍数字图像参数R,而低空航拍数字图像具有可以进行大面积快速监测的优势,因此在实际应用中可以根据需要选择其中一种方法或参数来估计田间小麦条锈病的发生和流行程度。

收稿时间:2017-06-30

Comparisons of detection of wheat stripe rust using hyper-spectrometer and UAV aerial photography
LIU Wei,Yang Gong-qiang,XU Fei,QIAO Hong-bo,FAN Jie-ru,SONG Yu-li,ZHOU Yi-lin.Comparisons of detection of wheat stripe rust using hyper-spectrometer and UAV aerial photography[J].Acta Phytopathologica Sinica,2018,48(2):223-227.
Authors:LIU Wei  Yang Gong-qiang  XU Fei  QIAO Hong-bo  FAN Jie-ru  SONG Yu-li  ZHOU Yi-lin
Abstract:Wheat stripe rust were monitored using hyper-spectrometer and UAV aerial photography in the field, respectively. The relationships among disease index and hyperspectral canopy reflectance parameters or UAV digital image parameters were analyzed. The results showed that there were significantly correlations between disease index and the hyperspectral parameters (DVI, NDVI, GNDVI) or UAV digital image color feature parameters (R, G, B). In general, the correlations between hyperspectral parameters and disease index were higher than those between UAV digital image parameters and the disease index. Furthermore, hyperspectral parameters DVI, NDVI, GNDVI were negatively and significantly correlated with UAV digital image parameters R, G, B. We constructed the estimation models of wheat stripe rust based on hyperspectral parameter GNDVI and UAV digital image parameter R, respectively, both the models fitted well, and the model based on GNDVI performed better than the model based on R, however, UAV digital images have the advantages of undertaking fast detection in large area, so in practice, we can choose one methods or one of the parameters to estimate the occurrence and epidemic of wheat stripe rust in the field as needed.
Keywords:wheat stripe rust  hyperspectral parameter  UAV digital image  disease monitoring  
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