ACT: A leaf BRDF model taking into account the azimuthal anisotropy of monocotyledonous leaf surface

Abstract

International audienceKeywords: Sorghum Wheat Leaf Surface roughness BRDF BRF Reflectance Conoscope Azimuthal anisotropy Optical properties Goniometer Physical model Refractive index Leaf reflectance of monocotyledons generally displays a strong azimuthal anisotropy due to the longitudinal orientation of the veins. The Cook and Torrance (CT) bidirectional reflectance distribution function model was adapted to account for this distinctive feature. The resulting ACT (Anisotropic Cook and Torrance) model is based on the decomposition of the roughness parameter into two perpendicular components. It is evaluated on sorghum (Sorghum halepense) and wheat (Triticum durum) leaf BRF (Bidirectional Reflectance Factor) measurements acquired using a conoscope system. Results show that the ACT model fits the measurements better than azimuthally isotropic surface models: the root mean square error computed over all the BRF measurements for both leaves decreases from ≈0.06 for the Lambertian model to ≈0.04 for the CT model and down to ≈0.03 for the ACT model. The adjusted value of the refraction index is plausible (n ≈ 1.32) for both leaves while the retrieved roughness values perpendicular to the veins (sorghum = 0.56; wheat = 0.46) is about two times larger than that parallel to the veins (sorghum = 0.27; wheat = 0.18). Nonetheless, the observed residual discrepancies between the ACT model simulations and the measurements may be explained mainly by the Lambertian assumption of the volume scattering

Joint leaf chlorophyll content and leaf area index retrieval from Landsat data using a regularized model inversion system (REGFLEC)

“…6a-c). These results highlight the strong sensitivity of vegetation retrievals (particularly Chl l ) to the adopted refractive index spectrum and specific absorption coefficients for pigments in PROSPECT and there is a need for continued research to improve the modeling of leaf reflectivity for application to both monocots (maize) and dicots (soybean) (Comar et al, 2014). While the blue spectrum holds information valuable for LAI and Chl l detection (Huete et al, 2002;Hunt, Daughtry, Eitel & Long, 2011), the large differences in calibrated absorption coefficients in the blue spectrum (Fig.…”

PROSPECT-D: Towards modeling leaf optical properties through a complete lifecycle

“…Barry and Newnham (2012) already pointed out an incorrect assessment of carotenoid content in Eucapyptus globulus and Eucapyptus nitens leaves. The development of PROSPECT-D partly answers these limitations, but further efforts will be needed to include specular reflection (Bousquet et al, 2005;Comar et al, 2014;Jay et al, 2016). , vol.…”

Estimation of the leaf chlorophyll content using multiangular spectral reflectance factor

“…Especially in the forward scattering directions, the R 2 values of existing spectral indices are strongly dependent on the viewing zenith angle. This scenario occurs because specular reflection dominates the reflection of leaves in the forward scattering directions (Bousquet et al, ; Comar et al, ; Combes et al, ; Grant, ; Woolley, ), and leaf surface properties control the magnitude and distribution pattern of leaf reflection. Thus, as the difference in reflection among the three types of leaves increases, the relationship of spectral indices with LCC of all calibration samples weakens.…”

“…Based on a semiempirical model of leaf reflection (Baret et al, 1988), the specular reflection from a leaf surface, which is assumed to be spectrally flat, can be reduced by the difference between two wavelengths (Datt, 1999;Penuelas et al, 1995;Sims & Gamon, 2002). In the multiangular measurements, specular reflection from a leaf surface dominates the total reflection in the forward scattering directions in the principal plane (Bacour & Bréon, 2005;Comar et al, 2012;Comar et al, 2014), which may reduce the ability of existing spectral indices to estimate LCC. Thus, spectral indices developed by the ratios of the difference between the reflections in two different wavelengths will reduce most of the influence of the leaf surface on the estimation of LCC (Datt, 1999;Lu et al, 2015;Penuelas et al, 1995;Sims & Gamon, 2002).…”