Spectral pBRDF microfacet modeling for dicotyledonous leaves and a coefficient correction

Area of Science:

• Plant biophysics
• Optical remote sensing
• Spectroscopy

Background:

• Traditional polarized bidirectional reflectance distribution function (pBRDF) microfacet models do not adequately account for volumetric scattering or are not leaf-specific.
• Spectral polarization detection offers a way to expand physicochemical information obtainable from leaves.

Purpose of the Study:

• To develop a spectral pBRDF microfacet model explicitly designed for leaves.
• To incorporate volumetric scattering and polarization effects into a leaf-specific pBRDF model.
• To analyze the correlation between leaf properties and spectral polarization signatures.

Main Methods:

• Developed a spectral pBRDF microfacet model incorporating volumetric scattering and polarization.
• Conducted spectral pBRDF measurements on various dicotyledonous leaves with differing chlorophyll content.
• Compared the performance of the new model against traditional pBRDF models using measured data.

Main Results:

• Leaf volumetric scattering intensity, chlorophyll content, and surface roughness (σg) are correlated with spectral polarization information.
• The proposed model demonstrates superior fitting for the f00 element of the pBRDF matrix compared to non-volumetric models.
• The model successfully integrates Mueller matrix forms with BRDF microfacet principles.

Conclusions:

• The developed spectral pBRDF microfacet model accurately represents leaf optical properties, including volumetric scattering.
• This model enhances the analysis of leaf physicochemical properties through spectral polarization detection.
• The findings provide a foundation for more sophisticated remote sensing applications in plant science.