Abstract: Temperature, precipitation, solar radiation and soil fertility are important ecological factors for wheat grain protein content (GPC), which are combined with remote sensing data to monitor GPC in this research. Experiments were carried out in suburban areas in Beijing. Multi -temporal HJ1A/B satellite data, meteorological data for the whole growing season from the corresponding meteorological stations, soil nutrient data and GPC obtained at maturity were acquired. Spectral GPC model, ecological factors GPC model and spectral ecological factors GPC model were constructed respectively. The results show that NDVIgreen corresponding to May 11 (around anthesis stage ) has best correlation with GPC in the research area. The correlation coefficient reaches significant level, thus May 11 was the best time for monitoring GPC by remote sensing. NDVIgreen values on May 11 were used for constructing spectral GPC model and spectral ecological factors GPC model. F-test shows that spectral GPC model, ecological factors GPC model, spectral ecological factors GPC model reach extremely significant levels with determination coefficients of 0.782, 0.635, 0.843, and relative error of 0.151, 0.123, 0.049 respectively. The results indicate that accuracy of spectral ecological factors GPC model combined with remote sensing data and ecological factor is higher than GPC model based on only spectral data or only ecological factors. Introduction of ecological factors into spectral protein GPC model helps to improve monitoring accuracy and agricultural mechanism of monitoring models.