Nitrogen fertilizer plays a crucial role in keeping food production in pace with population growth. However, the exceeding application of nitrogen fertilizer causes environmental risks. Timely and accurate quantification of canopy nitrogen content in crops is important for the rational application of nitrogen fertilizer and reduction environmental risks. The current research aimed to remotely estimate canopy nitrogen content in winter wheat and summer maize. Experiments with different N rates for different cultivars of wheat and maize were conducted in southeast Germany and in the North China Plain from 2008 to 2011. The results showed that, compared with traditional red light based spectral parameters, optimized spectral parameters significantly improved the prediction capacity, overcoming saturation problem in deriving canopy nitrogen content of wheat and maize. Band combination of optimized parameters varied with the difference in species and canopy structure of crops. The optimized bands concentrated on 730~760 and 760~800 nm. The best performing spectral parameter was Rλ766/Rλ738-1 for maize, Rλ796/Rλ760-1 for wheat and Rλ876/Rλ730-1 for wheat and maize combination. The validation results further confirmed that the optimized spectral parameters had the lowest predictive error, indicating that optimized spectral indices could estimate canopy nitrogen content of crops. In conclusion, the band optimization of spectral parameters is a promising approach to derive canopy N content in wheat and maize. The findings from this study may be useful for designing improved nitrogen diagnosis systems and for enhancing the applications of satellite-based sensors.