@article{fdi:010071332,
  title = {{S}patial downscaling of {SMAP} soil moisture using {MODIS} land surface temperature and {NDVI} during {SMAPVEX}15},
  author = {{C}olliander, {A}. and {F}isher, {J}. {B}. and {H}alverson, {G}. and {M}erlin, {O}livier and {M}isra, {S}. and {B}indlish, {R}. and {J}ackson, {T}. {J}. and {Y}ueh, {S}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he {S}oil {M}oisture {A}ctive {P}assive ({SMAP}) mission provides a global surface soil moisture ({SM}) product at 36-km resolution from its {L}-band radiometer. {W}hile the coarse resolution is satisfactory to many applications, there are also a lot of applications which would benefit from a higher resolution {SM} product. {T}he {SMAP} radiometer-based {SM} product was downscaled to 1 km using {M}oderate {R}esolution {I}maging {S}pectroradiometer ({MODIS}) data and validated against airborne data from the {P}assive {A}ctive {L}-band {S}ystem instrument. {T}he downscaling approach uses {MODIS} land surface temperature and normalized difference vegetation index to construct soil evaporative efficiency, which is used to downscale the {SMAP} {SM}. {T}he algorithm was applied to one {SMAP} pixel during the {SMAP} {V}alidation {E}xperiment 2015 ({SMAPVEX}15) in a semiarid study area for validation of the approach. {SMAPVEX}15 offers a unique data set for testing {SM} downscaling algorithms. {T}he results indicated reasonable skill (root-mean-square difference of 0.053 m(3)/m(3) for 1-km resolution and 0.037 m(3)/m(3) for 3-km resolution) in resolving high-resolution {SM} features within the coarse-scale pixel. {T}he success benefits from the fact that the surface temperature in this region is controlled by soil evaporation, the topographical variation within the chosen pixel area is relatively moderate, and the vegetation density is relatively low over most parts of the pixel. {T}he analysis showed that the combination of the {SMAP} and {MODIS} data under these conditions can result in a high-resolution {SM} product with an accuracy suitable for many applications.},
  keywords = {{L}and surface temperature ({LST}) ; {M}oderate {R}esolution {I}maging ; {S}pectroradiometer ({MODIS}) ; normalized difference vegetation index ({NDVI}) ; {P}assive {A}ctive {L}-band {S}ystem ({PALS}) ; soil moisture ({SM}) ; {S}oil {M}oisture {A}ctive {P}assive ({SMAP}) ; {ETATS} {UNIS} ; {ARIZONA}},
  booktitle = {},
  journal = {{IEEE} {G}eoscience and {R}emote {S}ensing {L}etters},
  volume = {14},
  numero = {11},
  pages = {2107--2111},
  ISSN = {1545-598{X}},
  year = {2017},
  DOI = {10.1109/lgrs.2017.2753203},
  URL = {https://www.documentation.ird.fr/hor/fdi:010071332},
}