In this paper

the authors develop an operational method to predict crop yield in China. Crop yield stratification is fundament

in which each stratum has own yield model for different crops. The level of crop yield （winter wheat

corn

rice

et al.） as well as physical factors of temperature

precipitation

soil type and sun radiation are considered. There are about 11 strata in China at the first level based on physical factors

39 strata at the second level based on crop yield and 133 strata at the third level based on agro-meteorology stratification. Literature study goes review has been made through the journals and books since 1980s for collecting agro-meteorological models and relevant application area. There are 114 models for wheat

25 models for maize

70 models for rice and 36 models for soybean. For every model

the suitable area has been defined by considering the original application area and crop yield stratification

and the parameters are generated by regression method of historical crop yield data and meteorological data. The crop yield prediction is stratum by stratum. To one stratum

there are many meteorological stations and counties. It is impossible to do the model calibration for each station or each county due to the lack of data. It may have the yield data for each county

but it is difficult to have the meteorological data at the same period for this county. Only those counties with both yield and meteorological data are selected to calibrate the yield model. The yield predictions are done for those counties. Spatial interpolation is used to extrapolate the yield at a station to whole county or whole stratum. Each pixel has its own yield data. The non-arable land is masked with landuse map and the average yield at a county or a stratum is calculated. At the end of this paper

a case study is presented to predict the yield of winter wheat in 2003.