Predicting grain yield of irrigation-land and dry-land winter wheat based on remote sensing data and meteorological data

The relationship between NDVI and grain yield was studied using remote sensing data at the different stages of winter wheat in Yuncheng region, and spectral yield model, meteorological yield model and spectrometeorological yield model were built. The results showed that the correlation between NDVI value of winter wheat in irrigation and dry-land on approximately May 8th and yield in Yuncheng region was the highest and extremely significant, so this period was the optimum period to establish remote sensing model of estimating yields in Yuncheng region. The spectral, meteorology and spectrometeorological yield models passed F test, and there were extremely significant level. Compared with other models, RRMSE and RE of spectrometeorological yield model apparently declined and the declining range was large, revealing better anticipating effect of spectrometeorological yield model compared to the model of spectrum. Remote sensing estimating value of average yield per unit was slightly larger than statistical value, while yield-estimating precision in dry-land was 80.91% and yield-estimating precision in irrigation-land was 87.72%. Estimating values of total yield were slightly higher than statistical values, where yield-estimating precision in dry-land was 99.20% and 80.54% in irrigation-land.