Yield estimation of winter wheat in the North China Plain using the remote-sensing-photosynthesis-yield estimation for crops (RS-P-YEC) model

The accurate prediction of crop yield is of great help for grain policy making. By assuming a horizontally homogeneous, vertically laminar structure and introducing a multilayer-two-big-leaf model, we develop a radiative-transfer equation for winter-wheat canopy and a model, named the remote-sensing-photosynthesis-yield estimation for crops (RS-P-YEC) model, for winter-wheat yield estimation. The yield is calculated by multiplying the net primary productivity (NPP) by the harvest index (HI). In this study, the yield of winter wheat in the North China Plain in 2006 is estimated using the RS-P-YEC model. The simulated yield is consistent with observations from 17 agro-meteorological stations, and the mean relative error is 4.6%. The results demonstrate that the RS-P-YEC model is a useful tool for winter-wheat yield estimation in the North China Plain with widely available remotely sensed imageries.