Using multi-angle hyperspectral data to monitor canopy leaf nitrogen content of wheat

Nitrogen (N) content is an important factor that can affect wheat production. The non-destructive testing of wheat canopy leaf N content through multi-angle hyperspectral remote sensing is of great importance for wheat production and management. Based on a 2-year experiment for winter wheat in Lethbridge (Canada), Zhengzhou (China), and Kaifeng (China) growing under different cultivation practices, the authors studied the relationships between N content and wheat canopy spectral data in solar principal plane (SPP) and perpendicular plane (PP) at different observation angles. Modeling was conducted according to the spectrum index with the highest correlation coefficient and the corresponding observation angle. The results showed that correlation coefficient between the spectral index and canopy leaf N content at each observation angle of the SPP was significantly higher than that of the PP. Significant differences in the correlation coefficient were also observed at different observation angles of the same observation plane, and the correlation coefficients of angles of -30A degrees and -40A degrees were higher than others. A model fitted by a power function by using mND705 as independent variable at an angle of -40A degrees in the SPP showed the highest accuracy.