小麦单产的遥感—气象综合模式研究

本文以北京顺义县为例,以气象因子与垂直植被指数(PVI)作为参数,用灰色模型G(0,2)和逐段订正模型即阶乘模型,建立冬小表遥感信息-气象因子综合模型。计算结果表明,改进后的综合模型其平均精度比单纯的遥感信息模型提高近7％,个别年份达到10％以上。

AfResearch on Remote Sensing-Meteorological Model for Wheat Yield Estimation

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.