Crop Phenology Estimation Using a Multitemporal Model and a Kalman Filtering Strategy

Please use this identifier to cite or link to this item: http://hdl.handle.net/10045/37746
Full metadata record
Full metadata record
DC FieldValueLanguage
dc.contributorSeñales, Sistemas y Telecomunicaciónes
dc.contributor.authorVicente-Guijalba, Fernando-
dc.contributor.authorMartínez Marín, Tomás-
dc.contributor.authorLopez-Sanchez, Juan M.-
dc.contributor.otherUniversidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señales
dc.contributor.otherUniversidad de Alicante. Instituto Universitario de Investigación Informáticaes
dc.date.accessioned2014-05-30T10:58:47Z-
dc.date.available2014-05-30T10:58:47Z-
dc.date.issued2014-06-
dc.identifier.citationIEEE Geoscience and Remote Sensing Letters. 2014, 11(6): 1081-1085. doi:10.1109/LGRS.2013.2286214es
dc.identifier.issn1545-598X (Print)-
dc.identifier.issn1558-0571 (Online)-
dc.identifier.urihttp://hdl.handle.net/10045/37746-
dc.description.abstractIn this letter, a new approach for crop phenology estimation with remote sensing is presented. The proposed methodology is aimed to exploit tools from a dynamical system context. From a temporal sequence of images, a geometrical model is derived, which allows us to translate this temporal domain into the estimation problem. The evolution model in state space is obtained through dimensional reduction by a principal component analysis, defining the state variables, of the observations. Then, estimation is achieved by combining the generated model with actual samples in an optimal way using a Kalman filter. As a proof of concept, an example with results obtained with this approach over rice fields by exploiting stacks of TerraSAR-X dual polarization images is shown.es
dc.description.sponsorshipThis project was supported in part by the Spanish Ministry of Economy and Competitiveness (MINECO) and in part by EU FEDER under Project TEC2011-28201-C02-02.es
dc.languageenges
dc.publisherIEEEes
dc.rights© Copyright 2014 IEEEes
dc.subjectAgriculturees
dc.subjectKalman filteres
dc.subjectMultitemporales
dc.subjectPhenologyes
dc.subjectPolarimetryes
dc.subjectRicees
dc.subjectSynthetic aperture radar (SAR)es
dc.subject.otherTeoría de la Señal y Comunicacioneses
dc.titleCrop Phenology Estimation Using a Multitemporal Model and a Kalman Filtering Strategyes
dc.typeinfo:eu-repo/semantics/articlees
dc.peerreviewedsies
dc.identifier.doi10.1109/LGRS.2013.2286214-
dc.relation.publisherversionhttp://dx.doi.org/10.1109/LGRS.2013.2286214es
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
Appears in Collections:INV - SST - Artículos de Revistas

Files in This Item:
Files in This Item:
File Description SizeFormat 
Thumbnail2014_Vicente-Guijalba_etal_IEEE-GRSL_final.pdfVersión final (acceso restringido)583,27 kBAdobe PDFOpen    Request a copy
Thumbnail2014_Vicente-Guijalba_etal_IEEE-GRSL.pdfVersión revisada (acceso abierto)807,49 kBAdobe PDFOpen Preview


Items in RUA are protected by copyright, with all rights reserved, unless otherwise indicated.