Estimation of winter wheat yield by using remote sensing data and crop model

Remote sensing data combined with crop model is an important application and development trend of current agricultural information technology, it can solve the problem that remote sensing or crop model cannot solve alone. In order to simulate crop growth and yield prediction in large scale, this paper using field test data to calibrate and validation the model parameters before apply to the winter wheat WOFOST model, than according to the actual environment of Xinxiang, simulate the growth in 3 different condition in the 2002-2003 growing season. Contrast the simulation value WOFOST model, using the Landsat-7 ETM retrieving leaf area index, define winter wheat's growth condition in each pixel, the remote sensing information combined with crop model is accomplished at pixel scale. Based on the actual production of Xinxiang winter wheat in 2003, compare the simulate results with the corresponding parameter, results shows that the method of this study method is feasible.