Leaf polarized BRDF simulation based on Monte Carlo 3-D vector RT modeling

Abstract The category of 3-D Vector radiative transfer (VRT) modeling was proved accurate enough to mimic realistically the polarized component of a vegetation canopy reflectance. Nonetheless, the reliability of such variety of model is still somewhat hampered by a lack of parameterization of the light polarization at the leaf level. This is traditionally based on Fresnel like specular reflection occurring at the leaf surface-air interface. Herein, we propose to perform an adaptation of the VRT formalism for leaves medium case based on the Monte Carlo (MC) forward ray tracing simulation. Two phenomena are taken into account; (i) a decrease by an absorption law within the different leaf tissues that is governed by the absorption coefficients; (ii) a reflection or refraction in the interface between two tissues that is sketched by the tissue refractive index ratio. This latter effect plays at modifying the light polarization since the parallel and perpendicular components of the wave are not scattered with the same probabilities. Rays will travel generally along long distances before exiting the medium, thereby leading to a large running computational time. In order to make the computation more efficient, we developed a dedicated model aimed at predicting the average so-called ray effect after a long travel. Hence, the ray tracing is stopped earlier in practice. The improvement is extended to hyper-spectral simulations as the demand is increasing. A new MC weighted sampling technique is proposed in this study with the objective to be applicable once for close wavelengths using the same tracing. Alike, as to simulate canopy reflectance, all the leaf directional scattering distributions are required, multi-angular simulation are gathered using the same ray tracing technique. Experimental results show large differences between classical 1-D model and the new proposed here, as leaves are no longer treated as Lambertian surfaces, with thin peak of specular reflection, but the reflectance increases in the forward direction. Moreover, with the new formulation leaves highly polarize light in both horizontal and horizontal-diagonal directions in the forward and inclined-forward directions, respectively. Taking into account the polarization mainly affects the scattering distribution for polarized incident light. This effect is more pronounced for smooth leaves. By comparison to the existing measurements of reflectance and polarization, the model shows generally the same trends.

[1]  Y. Lv,et al.  Photopolarimetric properties of leaf and vegetation covers over a wide range of measurement directions , 2018 .

[2]  Xin-Guang Zhu,et al.  The influence of leaf anatomy on the internal light environment and photosynthetic electron transport rate: exploration with a new leaf ray tracing model , 2016, Journal of experimental botany.

[3]  M. Mishchenko Electromagnetic Scattering by Particles and Particle Groups: An Introduction , 2014 .

[4]  Yu. I. Atrashevskii,et al.  The reflection and scattering of light by a plant leaf , 1999 .

[5]  A. Kuusk,et al.  A reflectance model for the homogeneous plant canopy and its inversion , 1989 .

[6]  J. Woolley Reflectance and transmittance of light by leaves. , 1971, Plant physiology.

[7]  Keith I. Hopcraft,et al.  Ray tracing in absorbing media , 2005 .

[8]  L. Johnson,et al.  LEAFMOD : A new within-leaf radiative transfer model , 1998 .

[9]  F. Baret,et al.  PROSPECT: A model of leaf optical properties spectra , 1990 .

[10]  H. Gausman,et al.  Interaction of Isotropic Light with a Compact Plant Leaf , 1969 .

[11]  V. I. Shuplyak,et al.  Spectral polarization characteristics of optical radiation reflected from leaves subjected to unfavorable ecological factors , 1998 .

[12]  Narendra S. Goel,et al.  Two models for rapidly calculating bidirectional reflectance of complex vegetation scenes: Photon spread (PS) model and statistical photon spread (SPS) model , 1998 .

[13]  V. I. Shuplyak,et al.  Spectral and spectral-polarization characteristics of potato leaves , 2000 .

[14]  W. Verhoef,et al.  PROSPECT+SAIL models: A review of use for vegetation characterization , 2009 .

[15]  Ahmad Al Bitar,et al.  DART: Recent Advances in Remote Sensing Data Modeling With Atmosphere, Polarization, and Chlorophyll Fluorescence , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[16]  Stéphane Jacquemoud,et al.  Simulation of photon transport in a three‐dimensional leaf: implications for photosynthesis , 2001 .

[17]  Christian P. Robert,et al.  Monte Carlo Statistical Methods , 2005, Springer Texts in Statistics.

[18]  Norman Badler,et al.  Spherical Sampling by Archimedes' Theorem , 1996 .

[19]  C. Bohren,et al.  An introduction to atmospheric radiation , 1981 .

[20]  A. Lacis,et al.  Multiple Scattering of Light by Particles: Radiative Transfer and Coherent Backscattering , 2006 .

[21]  V. A. Zaitseva,et al.  Polarization Characteristics of the He–Ne Laser Radiation Reflected from Rhododendron Leaves Subjected to Acid Treatment , 2001 .

[22]  V. A. Zaitseva,et al.  Changes in the Polarization Characteristics of He–Ne Laser Radiation Reflected From Plant Leaves , 2001 .

[23]  V. Vanderbilt,et al.  Plant Canopy Specular Reflectance Model , 1985, IEEE Transactions on Geoscience and Remote Sensing.

[24]  Abdelaziz Kallel,et al.  Canopy polarized BRDF simulation based on non-stationary Monte Carlo 3-D vector RT modeling , 2017 .

[25]  S. Jacquemoud,et al.  Leaf BRDF measurements and model for specular and diffuse components differentiation , 2005 .

[26]  Yoshihide Takano,et al.  Radiative Transfer in Cirrus Clouds. Part III: Light Scattering by Irregular Ice Crystals , 1995 .

[27]  T. Brakke,et al.  Specular and diffuse components of radiation scattered by leaves , 1994 .

[28]  V. Demarez,et al.  Modeling radiative transfer in heterogeneous 3D vegetation canopies , 1995, Remote Sensing.

[29]  Vyacheslav I. Shuplyak,et al.  Spectropolarization-characteristics angular dependence of radiation reflected by potato leaves , 1997, Remote Sensing.

[30]  Hankui K. Zhang,et al.  An extended PROSPECT: Advance in the leaf optical properties model separating total chlorophylls into chlorophyll a and b , 2017, Scientific Reports.

[31]  W. Egan,et al.  Optical stokes parameters for farm cropidentification , 1970 .

[32]  S. Ustin,et al.  Three-dimensional radiation transfer modeling in a dicotyledon leaf. , 1996, Applied optics.

[33]  F. Baret,et al.  Leaf optical properties with explicit description of its biochemical composition: Direct and inverse problems , 1996 .

[34]  H. Gausman,et al.  Mean Effective Optical Constants of Cotton Leaves , 1970 .

[35]  B. Acklin,et al.  Generalization of complex Snell–Descartes and Fresnel laws , 1994, Optical Society of America Annual Meeting.

[36]  D. Jordan,et al.  Polarized directional reflectance from laurel and mullein leaves , 2002 .

[37]  Andrew A. Lacis,et al.  Scattering, Absorption, and Emission of Light by Small Particles , 2002 .