Angular Spectral Index Can Reduce the Effect of Specular Reflection on Leaf Chlorophyll Content Estimation

Chlorophyll has been considered as an indicator related to photosynthesis and the vegetative growth process. The advent of high spatial resolution remote sensing provides an efficient way to accurately estimate chlorophyll content on different scales. Due to the combination of the field of view of sensors and varied leaf angles, the measured signals under the high spatial resolution, in fact, are composed of the multiangular reflection of leaves. Specular reflection, which generally has an additive effect on the spectrum and keeps the shape of the spectrum invariant with the varying viewing angles, dominates the multiangular reflection of leaves and drastically reduces the accuracy of leaf chlorophyll content (LCC) assessment for most spectral indices. In this study, we proposed a novel angular spectral index (ASI) based on multiangular data, defined by a triangle formed by three wavelengths (550, 720, and 755 nm), to estimate LCC. ASI provided a good and stable LCC estimation at different angles [the root mean square error (RMSE) at 0° is $6.98~\mu $ g/cm2, and −40° is $7.05~\mu $ g/cm2]. Furthermore, ASI was tested by the close-range hyperspectral imaging data of leaves and it demonstrated optimal estimation capability (RRMSE =20.29%). ASI provides an effective method for accurately estimating LCC by reducing the effect of specular reflection.