INTEGRATING REMOTELY SENSED DATA WITH AN ECOSYSTEM MODEL TO ESTIMATE CROP YIELD IN NORTH CHINA

This paper describes a method of integrating remotely sensed data (the MODIS LAI product) with an ecosystem model (the spatial EPIC model) to estimate crop yield in North China. The traditional productivity simulations based on crop models are normally sitespecific. To simulate regional crop productivity, the spatial crop model is developed firstly in this study by integrating Geographical Information System (GIS) with Environmental Policy Integrated Climate (EPIC) model. The integration applies a loose coupling approach. Data are exchanged using the ASCII or binary data format between GIS and EPIC model without a common user interface. It is crucial for the simulation accuracy of the spatial EPIC model to get the detailed initial conditions (sowing date, initial soil water content, etc) and management information (irrigation schedule, fertilizer schedule, tillage schedule, etc). But when applied at a large scale, the initial conditions and management information are most unlikely obtained through direct measurement. Therefore, the spatial EPIC model is integrated secondly with the MODIS LAI product from the Earth Resources Observation System (EROS) Data Center Distributed Active Archive Center. The integration of the MODIS LAI product makes the real time information taken into account in the simulation of spatial EPIC model, such as the amount of solar radiation captured by plant canopies, soil-water or nutrient effects on crop growth, and the effects of natural or man-made disturbances caused to crop yield. Finally, the method is conducted to estimate the Winter Wheat yield in North China in the year of 2003. 1