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dc.contributor.authorRossato, Luciana
dc.contributor.authorVall-Llossera Ferran, Mercedes Magdalena
dc.contributor.authorCamps Carmona, Adriano José
dc.contributor.authorPortal González, Gerard
dc.contributor.authorSakuragi, Jojhy
dc.contributor.authorFrederico de Angelis, Carlos
dc.contributor.authorZeri, Marcelo
dc.contributor.authorBarbosa Alves, Humberto
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2019-01-25T16:26:23Z
dc.date.issued2018
dc.identifier.citationRossato, L. [et al.]. Validation of soil moisture in the Brazilian Semiarid, using smos satellite product and Simagri model. A: IEEE International Geoscience and Remote Sensing Symposium. "2018 IEEE International Geoscience & Remote Sensing Symposium: proceedings: July 22–27, 2018 Valencia, Spain". Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 84-87.
dc.identifier.isbn978-1-5386-7150
dc.identifier.urihttp://hdl.handle.net/2117/127618
dc.description.abstractSoil moisture constitutes one of the main factors for the study where there is a water deficit in the soil, mainly for semiarid regions. The semiarid region of Brazil, which extends from the northern of the Piaui State to the north of Minas Gerais, is a region vulnerable to drought. the accuracy of soil moisture estimation is important for different studies. Thus, the aim of this work is to present the soil moisture derived from different methods: 1) Soil Moisture and Ocean Salinity (SMOS) satellite products generated at the Barcelona Expert Center (BEC) [2] and 2) System of Monitoring and Alert of Anomaly for Agriculture (SIMAGRI) model, at the semiarid region of Brazil. This region is selected because is a semiarid region recently affected by droughts and in situ measurements are available. Then it is very suitable for validation. In this paper an inter-comparison work with data recorded by that network, HR SM data from BEC and SIMAGRI model is presented. This study has been carried out from November, 2015 to June, 2016. We are going to present the statistical study, using correlation coefficient (R), Bias, and Root Mean Square Error (RMSE) as metrics. The results of this study will help to analyze environmental and economic impacts when droughts are detected in this area, which economy is mainly based on agriculture and to act for mitigating the negative consequences. Finally, it seems that the combination of satellite product and SIMAGRI model can be used as a valuable tool for monitoring and alert in case of dry and/or flooding episodes in different agricultural regions.
dc.format.extent4 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Satèl·lits i ràdioenllaços
dc.subject.lcshArtificial satellites in telecommunication
dc.subject.lcshSoil moisture
dc.subject.otherSoil moisture
dc.subject.otherSMOS
dc.subject.otherSIMAGRI
dc.subject.otherBrazilian semiarid region
dc.titleValidation of soil moisture in the Brazilian Semiarid, using smos satellite product and Simagri model
dc.typeConference report
dc.subject.lemacSatèl·lits artificials en telecomunicació
dc.subject.lemacSòls -- Humitat
dc.contributor.groupUniversitat Politècnica de Catalunya. RSLAB - Grup de Recerca en Teledetecció
dc.identifier.doi10.1109/IGARSS.2018.8518430
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8518430
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac23635547
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
local.citation.authorRossato, L.; Vall-llossera, M.; Camps, A.; Portal, G.; Sakuragi, J.; Frederico, C.; Zeri, M.; Barbosa, H.
local.citation.contributorIEEE International Geoscience and Remote Sensing Symposium
local.citation.publicationName2018 IEEE International Geoscience & Remote Sensing Symposium: proceedings: July 22–27, 2018 Valencia, Spain
local.citation.startingPage84
local.citation.endingPage87


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