Monitoring and evaluation of the diseases of and yield winter wheat from multi-temporal remotely-sensed data

Remote sensing techniques can provide crop growth information economically, rapidly, and objectively on a large scale., It has been widely used to monitor crop diseases. In this study, four Landsat TM images were acquired in the Beijing areas in winter wheat at four stages of growth—erecting stage (Apr. 10, 2007), booting stage (Apr. 26, 2007), anthesis stage (May 12, 2007) and grain filling stage (May 28, 2007) in Beijing. At the first three stages, the relative canopy spectra were also measured. All these multi-temporal remotely sensed data were analyzed to detect and evaluate winter wheat rust stripe and powdery mildew diseases. If diseases occurred, the spectral reflectances of diseased crops at visible and short infrared regions decreased, and the spectral reflectances at near-infrared region increased due to the decrease of plant chlorophyll concentration, water content and leaf area index (LAI); In addition, the red edge position decreased, namely, “blue shift” and NDVI values also decreased. Moreover, an early yield prediction model was developed using the Landsat TM images acquired at the erecting and booting stages, and the yield loss due to diseases was evaluated by using the measured yield and the predicted yield.