DECOMPOSING THE CONTRIBUTION OF FOLIAR NITROGEN CONTENT AND CANOPY STRUCTURAL PROPERTIES IN THE REFLECTANCE SPECTRA OF CEREAL CROPS

Recent studies have debated over the effect of canopy structure on the remote sensing of foliar nitrogen content. Although previous work reported on the radiative transfer modeling of canopy structural influence, the modeling implementation is still of limited use in the hyperspectral community This study proposes to use a multi-scale tool, continuous wavelet analysis, to decompose the spectral responses to variations in canopy structure and foliar nitrogen content. Our results demonstrated that the leaf area index (LAI) and leaf nitrogen content (LNC) were best correlated to the wavelet features (732 nm, scale 6) and (735 nm, scale 4), respectively. These two wavelet features could be used to separate the spectral contributions of LAI and LNC at different scales. The findings provide a new perspective for understanding the effect of canopy structure on hyperspectral remote sensing of foliar nitrogen.