@article{fdi:010090305,
  title = {{S}ensitivity of surface soil moisture retrieval to satellite-derived vegetation descriptors over wheat fields in the {K}airouan plain},
  author = {{A}yari, {E}. and {Z}ribi, {M}. and {L}ili-{C}habaane, {Z}. and {K}assouk, {Z}. and {J}arlan, {L}ionel and {R}odriguez-{F}ernandez, {N}. and {B}aghdadi, {N}.},
  editor = {},
  language = {{ENG}},
  abstract = {{S}oil moisture estimation is a key component in hydrological processes and irrigation amounts' estimation. {T}he synergetic use of optical and radar data has been proven to retrieve the surface soil moisture at a field scale using the {W}ater {C}loud {M}odel ({WCM}). {I}n this work, we evaluate the impact of staellite-derived vegetation descriptors to estimate the surface soil moisture. {T}herefore, we used the {S}entinel-1 data to test the polarization ratio ( sigma {V} {H} 0 / sigma {V} {V} 0 ) and the normalized polarization ratio ({IN}) and the frequently used optical {N}ormalized {D}ifference vegetation {I}ndex ({NDVI}) as vegetation descriptors. {S}ynchronous with {S}entinel-1 acquisitions, in situ soil moisture were collected over wheat fields in the {K}airouan plain in the center of {T}unisia. {T}o avoid the bare soil roughness effect and the radar signal saturation in dense vegetation context, we considered the data where the {NDVI} values vary between 0.25 and 0.7. {T}he soil moisture inversion using the {WCM} and {NDVI} as a vegetation descriptor was characterized by an {RMSE} value of 5.6 vol.%. {A} relatively close performance was obtained using {IN} and ( sigma {V} {H} 0 / sigma {V} {V} 0 ) with {RMSE} under 7. 5 vol.%. {T}he results revealed the consistency of the radar-derived data in describing the vegetation for the retrieval of soil moisture.},
  keywords = {{S}urface soil moisture ; wheat ; radar ; {S}entinel-1 ; normalized difference ; vegetation index ; semi-arid ; {TUNISIE}},
  booktitle = {},
  journal = {{E}uropean {J}ournal of {R}emote {S}ensing},
  volume = {56},
  numero = {1},
  pages = {2260555 [13 p.]},
  year = {2023},
  DOI = {10.1080/22797254.2023.2260555},
  URL = {https://www.documentation.ird.fr/hor/fdi:010090305},
}