Estimation of the vertical attenuation coefficient of nitrogen in cotton canopy using polarized multiple-angle vegetation index

The remote sensing-based estimation of the vertical attenuation coefficient K is of great significance to increase the accuracy of the estimation of crop canopy nitrogen vertical distribution by remote sensing technology. However, the multiple-angle information is susceptible to interference from specular reflection, which greatly limits the accuracy and stability of K estimation. In this research, the cotton canopy multiple-angle spectrum and polarization were acquired. Then, the spectral reflectance in the red- and blue-edge regions were combined to construct multiple-angle vegetation indices (MAVIs) using diffuse reflection component and total reflectance separately, and the MAVIs were used to estimate K. The estimated K was used to invert the nitrogen content of different vertical layers (upper, middle, and lower layers) of cotton canopy. Finally, the inversion results were compared with the inverted nitrogen content by the constructed multi-angle vegetative indices. The results showed that removing the specular reflection component from the total reflectance significantly increased the K estimation accuracy. The K estimation accuracy of MAVIs was higher than that of single-angle vegetation indices. Among the MAVIs, MNDVI_R-B (-30,45,45,45,0) had the highest K estimation accuracy, and the R² for the different growth season was in the range of 0.816–0.871. The estimated K by the MNDVI_R-B (-30,45,45,45,0) accurately inverted the nitrogen content of different vertical layers of cotton canopy, which was significantly higher than the R² of the estimation of different-layer nitrogen directly using the MAVIs. This study will provide a new method for accurately monitoring the vertical nitrogen status of crop canopy.