@article{fdi:010066940,
  title = {{SMOS} disaggregated soil moisture product at 1 km resolution : processor overview and first validation results},
  author = {{M}olero, {B}. and {M}erlin, {O}livier and {M}albeteau, {Y}. and {A}l {B}itar, {A}. and {C}abot, {F}. and {S}tefan, {V}. and {K}err, {Y}. and {B}acon, {S}. and {C}osh, {M}. {H}. and {B}indlish, {R}. and {J}ackson, {T}. {J}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he {SMOS} ({S}oil {M}oisture and {O}cean {S}alinity) mission provides surface soil moisture ({SM}) maps at a mean resolution of similar to 50 km. {H}owever, agricultural applications (irrigation, crop monitoring) and some hydrological applications (floods and modeling of small basins) require higher resolution {SM} information. {I}n order to overcome this spatial mismatch, a disaggregation algorithm called {D}isaggregation based on {P}hysical {A}nd {T}heoretical scale {C}hange ({DISPATCH}) combines higher-resolution data from optical/thermal sensors with the {SM} retrieved from microwave sensors like {SMOS}, producing higher-resolution {SM} as the output. {A} {DISPATCH}-based processor has been implemented for the whole globe (emerged lands) in the {C}entre {A}val de {T}raitement des {D}onnees {SMOS} ({CATDS}), the {F}rench data processing center for {SMOS} {L}evel 3 products. {T}his new {CATDS} {L}evel-4 {D}isaggregation processor ({C}4{DIS}) generates {SM} maps at 1 km resolution. {T}his paper provides an overview of the {C}4{DIS} architecture, algorithms and output products. {D}ifferences with the original {DISPATCH} prototype are explained and major processing parameters are presented. {T}he {C}4{DIS} {SM} product is compared against {L}3 and in situ {SM} data during a one year period over the {M}urrumbidgee catchment and the {Y}anco area ({A}ustralia), and during a four and a half year period over the {L}ittle {W}ashita and the {W}alnut {G}ulch watersheds ({USA}). {T}he four validation areas represent highly contrasting climate regions with different landscape properties. {A}ccording to this analysis, the {C}4{DIS} {SM} product improves the spatio-temporal correlation with in situ measurements in the semi-arid regions with substantial {SM} spatial variability mainly driven by precipitation and irrigation. {I}n sub-humid regions like the {L}ittle {W}ashita watershed, the performance of the algorithm is poor except for summer, as result of the weak moisture-evaporation coupling. {D}isaggregated products do not succeed to have and additional benefit in the {W}alnut {G}ulch watershed, which is also semi-arid but with well-drained soils that are likely to cancel the spatial contrast needed by {DISPATCH}. {A}lthough further validation studies are still needed to better assess the performance of {DISPATCH} in a range of surface and atmospheric conditions, the new {C}4{DIS} product is expected to provide satisfying results over regions having medium to high {SM} spatial variability.},
  keywords = {{D}isaggregation ; {S}oil moisture ; {P}rocessor ; {SMOS} ; {CATDS} ; {L}evel 4 ; {AUSTRALIE}},
  booktitle = {},
  journal = {{R}emote {S}ensing of {E}nvironment},
  volume = {180},
  numero = {{N}o {S}p{\'e}cial},
  pages = {361--376},
  ISSN = {0034-4257},
  year = {2016},
  DOI = {10.1016/j.rse.2016.02.045},
  URL = {https://www.documentation.ird.fr/hor/fdi:010066940},
}