Abstract: Accurate crop growth monitoring and yield forecasting are significant to food security and sustainable development of agriculture. Crop yield estimation by remote sensing and crop growth simulation models have highly potential application in crop growth monitoring and yield forecasting. However, both of them has limitations in mechanism or regional application, respectively. Therefore, approach and methodology study on combination of remote sensing data and crop growth simulation models are concerned by many researchers. Wofost based on adjustment and regionalization in North China and adjusted Sail-Prospect were coupled by I LA to simulate soil adjusted vegetation index (ISAV) of crop canopy, by which crop model was reinitialed by minimizing differences between simulated and synthesized I SAV from remote sensing data using an optimization software (FSEOPT). Thus, a regional remote sensing crop simulation framework model (WSPFRS) was established in potential production level (optimal soil water condition). The results were as follows: after re-initializing regional emergence date by using remote sensing data, anthesis and maturity date simulated by WSPFRS model were more close to measured values than simulated results of Wofost; by reinitializing regional biomass weight at turn-green stage, spatial distribution of simulated storage organ weight were more consistent to measured yields and the area with high values nearly consisted to actual high yield area. This research would be a foundation of developing regional crop model in water stress production level based on remote sensing data. 