@article{fdi:010074015,
  title = {{P}otential applications of {GNSS}-{R} observations over agricultural areas : results from the {GLORI} airborne campaign},
  author = {{Z}ribi, {M}. and {M}otte, {E}. and {B}aghdadi, {N}. and {B}aup, {F}. and {D}ayau, {S}. and {F}anise, {P}ascal and {G}uyon, {D}. and {H}uc, {M}. and {W}igneron, {J}. {P}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he aim of this study is to analyze the sensitivity of airborne {G}lobal {N}avigation {S}atellite {S}ystem {R}eflectometry ({GNSS}-{R}) on soil surface and vegetation cover characteristics in agricultural areas. {A}irborne polarimetric {GNSS}-{R} data were acquired in the context of the {GLORI}'2015 campaign over two study sites in {S}outhwest {F}rance in {J}une and {J}uly of 2015. {G}round measurements of soil surface parameters (moisture content) and vegetation characteristics (leaf area index ({LAI}), and vegetation height) were recorded for different types of crops (corn, sunflower, wheat, soybean, vegetable) simultaneously with the airborne {GNSS}-{R} measurements. {T}hree {GNSS}-{R} observables (apparent reflectivity, the reflected signal-to-noise-ratio ({SNR}), and the polarimetric ratio ({PR})) were found to be well correlated with soil moisture and a major vegetation characteristic ({LAI}). {A} tau-omega model was used to explain the dependence of the {GNSS}-{R} reflectivity on both the soil moisture and vegetation parameters.},
  keywords = {{GNSS}-{R} ; {GLORI} ; airborne ; agriculture ; soil moisture ; crops ; {LAI} ; {FRANCE}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {10},
  numero = {8},
  pages = {art. 1245 [17 p.]},
  ISSN = {2072-4292},
  year = {2018},
  DOI = {10.3390/rs10081245},
  URL = {https://www.documentation.ird.fr/hor/fdi:010074015},
}