Using Hyperspectral Derivative Index to Monitor Winter Wheat Disease
JIANG Jin-bao1,2,CHEN Yun-hao1*,HUANG Wen-jiang3
1. College of Resources Science and Technology, Beijing Normal University, Beijing 100875, China 2. College of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China 3. National Engineering Research Center for Information Technology in Agriculture, Beijing 100089, China
Abstract：The canopy reflectance of winter wheat that infected different severity stripe rust was measured through artificial inoculation, the disease index (DI) of the wheat corresponding to the spectra was acquired in the field, and the parameters of biochemistry and biophysics were measured indoors. The 1st derivatives were analyzed. The results show that the 1st derivative values increase at the green edge (500-560 nm), while decrease at the red edge (680-760 nm) with DI increasing. The ratio of the sum of derivatives within the red edge (SDr′) to the sum of derivatives within the green edge (SDg′) has a higher negative linear correlation with DI, with a coefficient of determination r2=0.921 0(n=28), and that can be use to identify the healthy and disease crops 12 days before symptoms appearing. Therefore, the derivative vegetation index SDr/SDg can be used to monitor crops disease information. The conclusion is significant and may find application in acquiring crops disease information using hyperspectral remote sensing, and has a important meaning for increasing yields of crops and ensuring security of food supplies.
Key words：Hyperspectra;Stripe rust;Disease index (DI);Winter wheat;Monitor
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