Contribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperature

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dc.contributorSeñales, Sistemas y Telecomunicaciónes_ES
dc.contributor.authorDe Bernardis, Caleb G.-
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_ES
dc.contributor.otherUniversidad de Alicante. Instituto Universitario de Investigación Informáticaes_ES
dc.identifier.citationIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2016, 9(8): 3512-3523. doi:10.1109/JSTARS.2016.2539498es_ES
dc.identifier.issn1939-1404 (Print)-
dc.identifier.issn2151-1535 (Online)-
dc.description.abstractIn this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.es_ES
dc.description.sponsorshipThis work was supported in part by Spanish Ministry of Economy and Competitiveness (MINECO) and in part by EU FEDER under Project TEC2011-28201-C02-02 and TIN2014-55413-C2-2-P.es_ES
dc.rights© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.es_ES
dc.subjectData fusiones_ES
dc.subjectNormalized difference vegetation index (NDVI)es_ES
dc.subjectParticle filter (PF)es_ES
dc.subjectState spacees_ES
dc.subjectSynthetic aperture radar (SAR)es_ES
dc.subjectTime serieses_ES
dc.subject.otherTeoría de la Señal y Comunicacioneses_ES
dc.titleContribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperaturees_ES
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