In growing season

from planting to havest of crop is a complicated process. There are many factors that influence the final yield which is a comprehensive response of various factors

such as environmental conditions

biological factors and agricultural management and techni-gue etc. Thus

remote sensing information or meteorological data doee not reflects the conditions of crop growth actually. In this paper

an example in Shunyi County

Beijing

is given

and a winter wheat yield comprehensive model is proposed. The model is combined Perpendicular Vegetation Index （PVI） with meteorological data. A grey-system model G （0

2） and successive corrected methods were used to establish a remote sensing- meteorological model for estimating winter wheat yield. By using multitemporal NOAA-AVHRR imageries and air temperature

the average accuracy of yield estimation is improved 7% in comprehensive model than in PVI model only.