The Measurement And Analysis Of Canopy Hyperspectral Character On Winter Wheat Damaged By Aphids And Wheat Powdery Mildew

Hyperspectral remote sensing inject new energy into the application of remote sensing on agriculture through it's more bands and abundant data. It is very important that monitoring the crop growth status and the diseases, insect pests' damage to them.. This article deal with the measurement and analysis the hyperspectral character of wheat aphid and wheat powdery mildew on winter wheat in year 2003, 2004. Canopy reflectance of winter wheat infected with different level wheat aphid and wheat powdery mildew were measured at different growth stage and damage level. The aphid amount in 100 trunks of wheat and disease incidence were also investigated at the same time. The spectrum feature and difference of winter wheat aphids and powdery mildew at green, yellow and near infrared band were studied qualitatively and quantitatively. The correlation and regression were taken between Normalized Difference Vegetable Index(NDVI) and aphids in 100 trunks of wheat, Disease Incidence(DI).The factors affect the quality and quantity of sunlight reflected from wheat canopies were discussed.The main results as follows: The canopy reflectance at green, yellow and near infrared bands was down, up, and down when the aphids and powdery mildew disease becomes more serious. The result of differential spectrum showed that the first derivative had got great changes at near infrared bands, but the red edge position shift not obvious. The correlations between NDVI and aphid amount in 100 trunks of wheat, Disease Incidence(DI) are very significant. The factors including weather condition, leaf wetness, the sensor height, the sun angle and the wheat variety affect the quality and quantity of sunlight reflected from wheat canopies hugely. In order to minimize the effects of all of the above external factors on the measurement of percentage of sunlight reflected from wheat canopies, the appropriate measurement method and time were discussed. This research provided theoretic foundation to further monitor winter wheat aphids and powdery mildew diseases at large scale using airborne and airspace remote sensing data.