Regional Yield Estimation of Summer Maize Based on Assimilation of Remotely Sensed LAI into EPIC Model
会议名称：《2010 Second IITA International Conference on Geoscience and Remote Sensing (IITA-GRS 2010)》
会议日期：2010年
学科分类：083002[工学-环境工程] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 081802[工学-地球探测与信息技术] 08[工学] 09[农学] 0818[工学-地质资源与地质工程] 081602[工学-摄影测量与遥感] 0816[工学-测绘科学与技术] 0901[农学-作物学]
基 金：supported by International S&T Cooperation Program of China (No.2010DFB10030) International Advanced Agricultural Technology Introduction Program (948 Program,No.2009-Z31) National High Technology Research and Development Program of China (863 Program,No.2009AA12Z143) Ministry of Finance of China through National Non-Profit Foundation for Research Institutes (IARRP-2009-27,IARRP-2010-02) China Agriculture Remote Sensing Monitoring System (CHARMS) of Ministry of Agriculture
关 键 词：data assimilation global optimization algorithm Crop growth model EPIC yield estimation remote sensing LAI
摘 要：In order to acquire more accurate crop yield information,the global optimization algorithm SCE-UA was used to integrate leaf area index derived from remote sensing with crop growth model EPIC to simulate regional summer maize yield and field management information in Huanghuaihai Plain in China. The results showed that the mean relative error of estimated summer maize yield was 4.37% and RMSE was 0.44t/ha. Compared with the actual field observation data,the mean relative error of simulated sowing date,plant density and net nitrogen fertilization application rate was 1.85%,-7.78% and -10.60% respectively. These above simulated results could meet need of accuracy of crop growth simulation and yield estimation at regional scale. It was proved that integrating remotely sensed LAI with EPIC model based on SCE-UA for simulating regional summer maize yield and field management information was feasible and reliable.