@article{PAR00013941,
  title = {{R}oughness and vegetation parameterizations at {L}-band for soil moisture retrievals over a vineyard field},
  author = {{F}ernandez-{M}oran, {R}. and {W}igneron, {J}. {P}. and {L}opez-{B}aeza, {E}. and {A}l-{Y}aari, {A}. and {C}oll-{P}ajaron, {A}. and {M}ialon, {A}. and {M}iernecki, {M}. and {P}arrens, {M}. and {S}algado-{H}ernanz, {P}. {M}. and {S}chwank, {M}. and {W}ang, {S}. and {K}err, {Y}ann},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he capability of {L}-band radiometry to monitor surface soil moisture ({SM}) at global scale has been analyzed in numerous studies, mostly in the framework of the {ESA} {SMOS} and {NASA} {SMAP} missions. {T}o retrieve {SM} from {L}-band radiometric observations, two significant effects have to be accounted for, namely soil roughness and vegetation optical depth. {I}n this study, soil roughness effects on retrieved {SM} values were evaluated using brightness temperatures acquired by the {L}-band {ELBARA}-{II} radiometer, over a vineyard field at the {V}alencia {A}nchor {S}tation ({VAS}) site during the year 2013. {D}ifferent combinations of the values of the model parameters used to account for soil roughness effects ({H}-{R}, {Q}({R}), {N}-{RH} and {N}-{RV}) in the {L}-{MEB} model were evaluated. {T}he {L}-{MEB} model ({L}-band {M}icrowave {E}mission of the {B}iosphere) is the forward radiative transfer model used in the {SMOS} soil moisture retrieval algorithm. {I}n this model, {HR} parameterizes the intensity of roughness effects, {Q}({R}) accounts for polarization effects, and {N}-{RH} and {N}-{RV} parameterize the variations of the soil reflectivity as a function of the observation angle, theta, respectively for both {H} ({H}orizontal) and {V} ({V}ertical) polarizations. {T}hese evaluations were made by comparing in-situ measurements of {SM} (used here as a reference) against {SM} retrievals derived from tower-based {ELBARA}-{II} brightness temperatures mentioned above. {T}he general retrieval approach consists of the inversion of {L}-{MEB}. {T}wo specific configurations were tested: the classical 2-{P}arameter (2-{P}) retrieval configuration where {SM} and {T}-{NAD} (vegetation optical depth at nadir) are retrieved, and a 3-{P}arameter (3-{P}) configuration, accounting for the additional effects of the vineyard vegetation structure. {U}sing the 2-{P} configuration, it was found that setting {N}-{R}p (p = {H} or {V}) equals to 1 provided the best {SM} estimations in terms of correlation and unbiased {R}oot {M}ean {S}quare {E}rror (ub{RMSE}). {T}he assumption {N}-{RV} = {N}-{RH} = -1 simplifies the {L}-{MEB} retrieval, since the two parameters {T}wo and {H}-{R} can then be grouped and retrieved as a single parameter (method here defined as the {S}implified {R}etrieval {M}ethod ({SRP})). {T}he main advantage of the {SRP} method is that it is not necessary to calibrate {H}-{R} before performing the {SM} retrievals. {U}sing the 3-{P} configuration, the results improved, with respect to {SM} retrievals, in terms of correlation and ub{RMSE}, as the structural characteristics of the vineyards were better accounted for. {H}owever, this method still requires the calibration of {H}-{R}, a disadvantage for operational applications. {F}inally, it was found that the use of in-situ roughness measurements to calibrate the roughness model parameters did not provide significant improvements in the {SM} retrievals as compared to the {SRP} method.},
  keywords = {{M}icrowave radiometry ; {L}-band ; {S}oil moisture ; {S}oil roughness ; {V}egetation ; {L}-{MEB} ; {SMOS} ; {ESPAGNE}},
  booktitle = {},
  journal = {{R}emote {S}ensing of {E}nvironment},
  volume = {170},
  numero = {},
  pages = {269--279},
  ISSN = {0034-4257},
  year = {2015},
  DOI = {10.1016/j.rse.2015.09.006},
  URL = {https://www.documentation.ird.fr/hor/{PAR}00013941},
}