• Title of article

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

  • Author/Authors

    Comar، نويسنده , , Alexis and Baret، نويسنده , , Frédéric and Obein، نويسنده , , Gaël and Simonot، نويسنده , , Lionel and Meneveaux، نويسنده , , Daniel and Viénot، نويسنده , , Françoise and de Solan، نويسنده , , Benoit، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2014
  • Pages
    10
  • From page
    112
  • To page
    121
  • Abstract
    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.
  • Keywords
    Leaf , BRDF , BRF , Reflectance , Conoscope , Optical properties , Goniometer , Physical model , Surface roughness , Refractive index , sorghum , wheat , azimuthal anisotropy
  • Journal title
    Remote Sensing of Environment
  • Serial Year
    2014
  • Journal title
    Remote Sensing of Environment
  • Record number

    1634207