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dc.contributor.authorSanchez, Nilda
dc.contributor.authorPiles Guillem, Maria
dc.contributor.authorScaini, Anna
dc.contributor.authorMartinez Fernandez, Jose
dc.contributor.authorCamps Carmona, Adriano José
dc.contributor.authorVall-Llossera Ferran, Mercedes Magdalena
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2013-06-21T15:19:57Z
dc.date.created2012
dc.date.issued2012
dc.identifier.citationSanchez, N. [et al.]. Spatial patterns of SMOS downscaled soil moisture maps over the remedhus network (Spain). A: IEEE International Geoscience and Remote Sensing Symposium. "IGARSS 2012: International Geoscience and Remote Sensing Symposium: remote science for a dynamic earth: proceedings, 22-27 July 2012 Munich". Munich: Institute of Electrical and Electronics Engineers (IEEE), 2012, p. 714-717.
dc.identifier.isbn978-1-4673-1159-5
dc.identifier.urihttp://hdl.handle.net/2117/19615
dc.description.abstractThis paper describes the relationships found between remotely sensed soil moisture, in situ observed soil moisture, and spatial distribution of soil and climatic factors. For the comparison between remote and in situ soil moisture, soil moisture map series at high resolution, obtained by applying a downscaling approach that combines Soil Moisture and Ocean Salinity (SMOS) and MODIS imagery is extracted. The in situ soil moisture series are obtained from the Soil Moisture Measurement Stations Network (REMEDHUS) in Spain. For the spatial analysis, factors such as topography, precipitation, and land uses were mapped from the climatic and cartographic database of REMEDHUS. The comparison between downscaled and in situ soil moisture data resulted in correlation coefficient (R) values between 0.40 and 0.70, bias between -0.04 and 0.16 m3m-3, and root mean squared difference (RMSD) between 0.07 and 0.19 m3m-3. Regarding the spatial correlations between downscaled and spatial factors, no clear patterns were found when considering the topography (Topographic Wetness Index, TWI), and the land uses (Landsat classification). Nevertheless, the downscaled soil moisture was more related with the spatial distribution of precipitation (Antecedent Precipitation Index, API), with significant correlations varying between 0.24 and 0.55.
dc.format.extent4 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Enginyeria civil::Geologia::Oceanografia
dc.subjectÀrees temàtiques de la UPC::Enginyeria electrònica::Instrumentació i mesura::Sensors i actuadors
dc.subject.lcshSoil moisture
dc.subject.lcshRemote sensing
dc.subject.otherAPI
dc.subject.otherDEM
dc.subject.otherdownscaling
dc.subject.otherSMOS
dc.subject.othersoil moisture
dc.titleSpatial patterns of SMOS downscaled soil moisture maps over the remedhus network (Spain)
dc.typeConference report
dc.subject.lemacTeledetecció
dc.subject.lemacSòls -- Humitat
dc.contributor.groupUniversitat Politècnica de Catalunya. RSLAB - Grup de Recerca en Teledetecció
dc.identifier.doi10.1109/IGARSS.2012.6351465
dc.description.peerreviewedPeer Reviewed
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac12324469
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
local.citation.authorSanchez, N.; Piles, M.; Scaini, A.; Martinez, J.; Camps, A.; Vall-llossera, M.
local.citation.contributorIEEE International Geoscience and Remote Sensing Symposium
local.citation.pubplaceMunich
local.citation.publicationNameIGARSS 2012: International Geoscience and Remote Sensing Symposium: remote science for a dynamic earth: proceedings, 22-27 July 2012 Munich
local.citation.startingPage714
local.citation.endingPage717


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