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dc.contributor.authorSanchez Ruiz, Sergio
dc.contributor.authorPiles Guillem, Maria
dc.contributor.authorSanchez, Nilda
dc.contributor.authorMartinez Fernandez, Jose
dc.contributor.authorVall-Llossera Ferran, Mercedes Magdalena
dc.contributor.authorCamps Carmona, Adriano José
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2015-01-20T15:03:41Z
dc.date.created2014-08-04
dc.date.issued2014-08-04
dc.identifier.citationSanchez, S. [et al.]. Combining SMOS with visible and near/shortwave/thermal infrared satellite data for high resolution soil moisture estimates. "Journal of hydrology", 04 Agost 2014, vol. 516, p. 273-283.
dc.identifier.issn0022-1694
dc.identifier.urihttp://hdl.handle.net/2117/25965
dc.description.abstractSensors in the range of visible and near-shortwave-thermal infrared regions can be used in combination with passive microwave observations to provide soil moisture maps at much higher spatial resolution than the original resolution of current radiometers. To do so, a new downscaling algorithm ultimately based on the land surface temperature (LST) - Normalized Difference Vegetation Index (NDVI) - Brightness Temperature (T-B) relationship is used, in which shortwave infrared indices are used as vegetation descriptors, instead of the more common near infrared ones. The theoretical basis of those indices, calculated as the normalized ratio of the 1240, 1640 and 2130 nm shortwave infrared (SWIR) bands and the 858 nm near infrared (NIR) band indicate that they are able to provide estimates of the vegetation water content. These so-called water indices extracted from MODIS products, have been used together with MODIS LST, and SMOS T-B to improve the spatial resolution of similar to 40 km SMOS soil moisture estimates. The aim was to retrieve soil moisture maps with the same accuracy as SMOS, but at the same resolution of the MODIS dataset, i.e., 500 m, which were then compared against in situ measurements from the REMEDHUS network in Spain. Results using two years of SMOS and MODIS data showed a similar performance for the four indices, with slightly better results when using the index derived from the first SWIR band. For the areal-average, a coefficient of correlation (R) of similar to 0.61 and similar to 0.72 for the morning and afternoon orbits, respectively, and a centered root mean square difference (cRMSD) of similar to 0.04 m(3) m(-3) for both orbits was obtained. A twofold improvement of the current versions of this downscaling approach has been achieved by using more frequent and higher spatial resolution water indexes as vegetation descriptors: (1) the spatial resolution of the resulting soil moisture maps can be enhanced from similar to 40 km up to 500 m, and (2) more accurate soil moisture maps (in terms of R and cRMSD) can be obtained, especially in periods of high vegetation activity. The results of this study support the use of high resolution LST and SWIR-based vegetation indices to disaggregate SMOS observations down to 500 m soil moisture maps, meeting the needs of fine-scale hydrological applications.
dc.format.extent11 p.
dc.language.isoeng
dc.publisherElsevier
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Circuits de microones, radiofreqüència i ones mil·limètriques
dc.subjectÀrees temàtiques de la UPC::Desenvolupament humà i sostenible::Enginyeria ambiental::Tractament dels sòls
dc.subject.lcshSoil moisture
dc.subject.lcshSalinity
dc.subject.lcshMicrowave circuits
dc.subject.otherDownscaling
dc.subject.otherDisaggregation
dc.subject.otherSMOS
dc.subject.otherMODIS
dc.subject.otherSoil moisture
dc.subject.otherNDWI
dc.subject.otherVegetation water-content
dc.subject.otherRemedhus network Spain
dc.subject.otherRemote-sensing data
dc.subject.otherAMSR-E
dc.subject.otherMODIS Products
dc.subject.otherModel
dc.subject.otherIndex
dc.subject.otherCorn
dc.subject.otherDisaggregation
dc.subject.otherValidation
dc.titleCombining SMOS with visible and near/shortwave/thermal infrared satellite data for high resolution soil moisture estimates
dc.typeArticle
dc.subject.lemacSòls -- Humitat
dc.subject.lemacSalinitat
dc.subject.lemacCircuits de microones
dc.contributor.groupUniversitat Politècnica de Catalunya. RSLAB - Grup de Recerca en Teledetecció
dc.identifier.doi10.1016/j.jhydrol.2013.12.047
dc.description.peerreviewedPeer Reviewed
dc.rights.accessRestricted access - publisher's policy
drac.iddocument15075870
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
upcommons.citation.authorSanchez, S.; Piles, M.; Sanchez, N.; Martinez, J.; Vall-llossera, M.; Camps, A.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameJournal of hydrology
upcommons.citation.volume516
upcommons.citation.startingPage273
upcommons.citation.endingPage283


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