• DocumentCode
    24489
  • Title

    Evaluating the Semiempirical H - Q Model Used to Calculate the L-Band Emissivity of a Rough Bare Soil

  • Author

    Lawrence, H. ; Wigneron, Jean-Pierre ; Demontoux, F. ; Mialon, Arnaud ; Kerr, Yann H.

  • Author_Institution
    Integration du Materiau au Syst. Lab., Univ. of Bordeaux 1, Bordeaux, France
  • Volume
    51
  • Issue
    7
  • fYear
    2013
  • fDate
    Jul-13
  • Firstpage
    4075
  • Lastpage
    4084
  • Abstract
    In this paper, a numerical modeling approach was used to evaluate the semiempirical H-Q model used in the Soil Moisture and Ocean Salinity (SMOS) retrieval algorithm to account for roughness effects over bare soil. The H-Q model uses four parameters, HR, QR, NRH , and NRV, which are usually calibrated at the ground scale for different surface types. The aim of this paper is to investigate whether these empirical parameters could be linked to the physical roughness parameters of standard deviation of surface heights σ and autocorrelation length Lc. First, a numerical modeling approach was used to calculate rough soil emissivities for different roughness and soil moisture conditions. Second, H -Q model parameters were retrieved by minimizing a cost function between these emissivities and those calculated by the H -Q model. It was found that the retrieved HR could be related directly to Zs = σ2/Lc and that QR, NRV, and NRH were dependent on HR. HR was found to have a negligible dependence on soil moisture. Based on these results, a new model was proposed where the four H-Q model parameters were calibrated to Zs. This model was tested on the PORTOS 1993 data set and found to yield a root-mean-square difference between the retrieved and measured soil moisture values of ~ 0.03 m3/m3, which was within the desired 0.04-m3/m3 error margin for the SMOS mission.
  • Keywords
    geophysical techniques; soil; H-Q model parameters; HR parameter; L-band emissivity calculation; NRH parameter; NRV parameter; PORTOS 1993 data set; QR parameter; SMOS mission; SMOS retrieval algorithm; autocorrelation length; cost function minimization; empirical parameters; ground scale calibration; numerical modeling approach; physical roughness parameters; root-mean-square difference; rough bare soil roughness effects; rough soil emissivity calculation; semiempirical H-Q model evaluation; soil moisture and ocean salinity; soil moisture conditions; soil moisture value measurement; soil moisture value retrieval; surface height standard deviation; surface types; Correlation; Finite element methods; Numerical models; Rough surfaces; Soil moisture; Surface roughness; Modeling; passive microwave remote sensing; rough surfaces; soil moisture retrievals;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2012.2226995
  • Filename
    6418018