AfResearch on Remote Sensing-Meteorological Model for Wheat Yield Estimation
小麦单产的遥感—气象综合模式研究

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.