 The study aims to use UAV multispectral imagery and ground hyperspectral measurements to predict canopy nitrogen weight of wheat and corn fields in Ontario using a simple linear regression model with the Ratio Vegetation Index, RVI, performing the best. The RVI based regression model accurately predicted canopy nitrogen weight for both crops with an RMS E of 0.95 Gm2 for wheat and 0.66 Gm2 for corn. This information is important for farmers as it will lead to a more efficient fertilizer application programme. This article was authored by Huang Li, Jean-Faye Wang, and Brigitte Leblon.