Monitoring Wheat Stripe Rust With Remote Sensing And Hazard Assessment

Wheat stripe rust disease is one of the most large-range and the most serious diseases in China and all over the world. Crop varieties and meteorological conditions may cause frequent occurrence of wheat stripe rust, but the main causes could be to lack effective means of monitoring and predicting for wheat stripe rust disease. Remote sensing is able to monitor diseases and pests in crops with real - time, dynamic and lossless characteristics, and is playing a very important role in monitoring wheat stripe rust disease. The experiments were carried by remote sensing at Bejing Xiaotangshan Precision Agriculture Experimental Base in Changping district and Tongzhou and Shunyi of Beijing suburb during growing seasons of wheat. The results showed:(1) Base on previous studies, the model of NDVI= -0.247 PRI2 + 0.1195 PRI + 0.9001, which could identify quantitatively wheat stripe rust disease from other stresses, was established by application NDVI and RVI obtained from field hyper-spectral data of others stresses and disease data, and the stress points for wheat stripe rust disease were selected, when the NDVI of observation point was more than -0.247 PRI2 + 0.1195 PRI + 0.9001 with the accuracy being more than 75%.(2) Sensitive bands of wheat stripe rust disease in the range of 300-1500 nm were chosen, based on the relationship between 46 groups diseases and corresponding field spectral data at the experimental plots of Xiaotangshan in 2003. Red bands (620-718 nm) and near infrared bands (770-805 nm) were used as the sensitive bands of wheat stripe rust disease, considering the character of PHI image. The reverse model was constructed by both the mean reflectance of red bands (620-718 nm) and near infrared bands (770-805nm) and the observed diseases indexes: DI= 19.241 R1-2.20667 R2+12.2744. The tests indicated that the occurrence range and degree of wheat stripe rust disease could be monitoring successfully in PHI image.(3) Wheat stressed by water, powdery mildew and stripe rust disease, respectively, in setting stage, booting stage, heading and flowering stage was monitored simultaneously by field remote sensing and satellite remote sensing. With comparison of the spectral reflectance between the field hyper-spectral remote sensing and satellite remote sensing, both the spectral responses of stressed wheat and normal wheat were consistent among the three different grow stages. This result will lay a theoretical basis on monitoring and identifying the stressed wheat in the large area. (4) The planting areas of wheat in Tongzhou and Shunyi were picked from Landsat TM of November 10th, 2007 by decisional tree classification of supervised classification. And NDVI of TM images in setting stage of wheat (April 10th) and RVI of TM image in milky stage of wheat (May 28th) in the plating area of wheat were obtained with ENVI software. By the characters and law of NDVI and RVI of the field survey points, the diseases of wheat were identified and monitored successfully. In addition, a preliminary evaluation on losses of wheat yield caused by diseases was developed in this study, according to the actual yield and the result of monitoring diseases.