Simulation of regional winter wheat growth by using remote sensing data and crop model

Crop model is a powerful tool in crop growth monitoring and yield forecasting, however crop model is developed based on single point scale, due to regional differentiation. field variation and other reasons lead to input parameters and initial conditions which required by crop model simulation are hard to obtain, the application of crop model has been greatly limited in the regional scale, the introduction of remote sensing will solve this problem, remote sensing is combined with the crop model WOFOST, using the state variable retrieved by remote sensing to optimize crop model simulation, revaluing the sensitive parameters and initial conditions which needed in crop model on the region scale, in order to take the advantage of crop model in the area. This study is on the basis of adaptive adjustment and amendment of crop model WOFOST, build a winter wheat growth simulation model which is suitable for Yucheng, Shandong; Using the field experiment data calibration and validation the WOFOST model, discussed the method which combined crop simulation model and remote sensing under water stress level, using remote sensing calibrated some key processes of crop simulation or reinitialize. parameterize the crop simulation model in order to achieve the optimization model; Explored some reasonable and practical method of remote sensing information application in crop simulation at regional scale, with more research, make it possible to monitor regional crop growth and forecast the output.