Optimizing Two-Band Spectral Indices to Estimate Leaf Chlorophyll Content Using the Non-Polarized Reflectance Factors

Leaf chlorophyll content (LCC) is a key indicator of plant photosynthesis and can be estimated by the optical properties of leaves. Due to the random distribution of leaf angles and the change of incident light angle, it is necessary to reduce the effects of specular reflection when estimating LCC under different measurement geometries. Because the polarized reflectance factor can account for specular reflection, which does not relate to LCC, it is possible to improve LCC estimation using spectral indices when the polarized reflectance is removed from the total reflectance. In this study, polarimetric measurements of leaves from three different plant species were performed with different measurement geometries in both laboratory and field conditions. We tested all possible waveband combinations in the 400–1000 nm range with two types of spectral indices: simple ratio (SR) (
$R_{\lambda 1}/R_{\lambda 2})$
and normalized difference vegetation index (NDVI) (
$R_{\lambda \mathrm {i}} - R_{\lambda \mathrm {j}}$
)/(
$R_{\lambda \mathrm {i}} + R_{\lambda \mathrm {j}}$
), using both total intensity [defined as
$I$
parameter reflectance factor (IpRF)] and non-polarized [defined as non-polarized reflectance factor (NpRF)] information. By comparing the LCC estimation accuracy based on IpRF with that based on NpRF, we found that NpRF increased the number of bands that can estimate LCC with relatively high accuracy. These results indicate that the simple two-band indices based on the NpRF are robust and accurate for estimating LCC at leaf scale, and the broad effective wavelength range of NpRF may have the ability to overcome bandwidth limitations. The results of this study support future vegetation indices design and model development.