@article{PAR00010521,
  title = {{S}patial distribution and possible sources of {SMOS} errors at the global scale},
  author = {{L}eroux, {D}.{J}. and {K}err, {Y}ann and {R}ichaume, {P}. and {F}ieuzal, {R}.},
  editor = {},
  language = {{ENG}},
  abstract = {{SMOS} ({S}oil {M}oisture and {O}cean {S}alinity) data have now been available for over two years and, as part of the validation process, comparing this new dataset to already existing global datasets of soil moisture is possible. {I}n this study, {SMOS} soil moisture product was evaluated globally by using the triple collocation method. {T}his statistical method is based on the comparison of three datasets and produces global error maps by statistically inter-comparing their variations. {O}nly the variable part of the errors are considered here, the bias errors are not treated by triple collocation. {T}his method was applied to the following datasets: {SMOS} {L}evel 2 product, two soil moisture products derived from {AMSR}-{E} ({A}dvanced {M}icrowave {S}canning {R}adiometer)-{LPRM} ({L}and {P}arameter {R}etrieval {M}odel) and {NSIDC} ({N}ational {S}now and {I}ce {D}ata {C}enter), {ASCAT} ({A}dvanced {S}catterometer) and {ECMWF} ({E}uropean {C}enter for {M}edium range {W}eather {F}orecasting). {T}he resulting errors are not absolute since they depend on the choice of the datasets. {H}owever this study showed that the spatial structure of the {SMOS} was independent of the combination and pointed out the same areas where {SMOS} performed well and where it did not. {T}his global {SMOS} error map was then linked to other global parameters such as soil texture, {RFI} ({R}adio {F}requency {I}nterference) occurrence probabilities and land cover in order to identify their influences in the {SMOS} error. {G}lobally the presence of forest in the field of view of the radiometer seemed to have the greatest influence on {SMOS} error (56.8%) whereas {RFI} represented 1.7% according to the analysis of variance from a multiple linear regression model. {T}hese percentages were not identical for all the continents and some discrepancies in the proportion of the influence were highlighted: soil texture was the main influence over {E}urope whereas {RFI} had the largest influence over {A}sia.},
  keywords = {{T}riple collocation ; {SMOS} ; {E}rror structure ; {S}oil moisture ; {M}ultiple linear regression ; {A}nalysis of variance},
  booktitle = {},
  journal = {{R}emote {S}ensing of {E}nvironment},
  volume = {133},
  numero = {},
  pages = {240--250},
  ISSN = {0034-4257},
  year = {2013},
  DOI = {10.1016/j.rse.2013.02.017},
  URL = {https://www.documentation.ird.fr/hor/{PAR}00010521},
}