@article{fdi:010055673,
  title = {{S}patio-temporal surface soil heat flux estimates from satellite data : results for the {AMMA} experiment at the {F}akara ({N}iger) supersite},
  author = {{V}erhoef, {A}. and {O}ttle, {C}. and {C}appelaere, {B}ernard and {M}urray, {T}. and {S}aux-{P}icart, {S}. and {Z}ribi, {M}ehrez and {M}aignan, {F}. and {B}oulain, {N}icolas and {D}emarty, {J}{\'e}rome and {R}amier, {D}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}his paper describes a method that employs {E}arth {O}bservation ({EO}) data to calculate spatiotemporal estimates of soil heat flux, {G}, using a physically-based method (the {A}nalytical {M}ethod). {T}he method involves a harmonic analysis of land surface temperature ({LST}) data. {I}t also requires an estimate of near-surface soil thermal inertia; this property depends on soil textural composition and varies as a function of soil moisture content. {T}he {EO} data needed to drive the model equations, and the ground-based data required to provide verification of the method, were obtained over the {F}akara domain within the {A}frican {M}onsoon {M}ultidisciplinary {A}nalysis ({AMMA}) program. {LST} estimates (3 km x 3 km, one image 15 min(-1)) were derived from {MSG}-{SEVIRI} data. {S}oil moisture estimates were obtained from {ENVISAT}-{ASAR} data, while estimates of leaf area index, {LAI}, (to calculate the effect of the canopy on {G}, largely due to radiation extinction) were obtained from {SPOT}-{HRV} images. {T}he variation of these variables over the {F}akara domain, and implications for values of {G} derived from them, were discussed. {R}esults showed that this method provides reliable large-scale spatiotemporal estimates of {G}. {V}ariations in {G} could largely be explained by the variability in the model input variables. {F}urthermore, it was shown that this method is relatively insensitive to model parameters related to the vegetation or soil texture. {H}owever, the strong sensitivity of thermal inertia to soil moisture content at low values of relative saturation (<0.2) means that in arid or semi-arid climates accurate estimates of surface soil moisture content are of utmost importance, if reliable estimates of {G} are to be obtained. {T}his method has the potential to improve large-scale evaporation estimates, to aid land surface model prediction and to advance research that aims to explain failure in energy balance closure of meteorological field studies. {C}rown {C}opyright ({C}) 2011 {P}ublished by {E}lsevier {B}.{V}. {A}ll rights reserved.},
  keywords = {{L}and surface temperatures ; {MSG} ; {S}oil heat flux ; {AMMA} ; {S}ahel},
  booktitle = {},
  journal = {{A}gricultural and {F}orest {M}eteorology},
  volume = {154},
  numero = {},
  pages = {55--66},
  ISSN = {0168-1923},
  year = {2012},
  DOI = {10.1016/j.agrformet.2011.08.003},
  URL = {https://www.documentation.ird.fr/hor/fdi:010055673},
}