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

Comparisons of detection of wheat stripe rust using hyper-spectrometer and UAV aerial photography

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。

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 dig- ital 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 inlarge 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.