Evaluating the Influence of Missing Data from the Crop Vegetation Index Time Series on Copernicus HR-VPP Phenological Products

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dc.contributor.authorValero Jorge, Alexey
dc.contributor.authorCasterad Seral, María Auxiliadora
dc.contributor.authorAlcalá, José-Tomás
dc.contributor.orcidValero Jorge, Alexey [0000-0002-5993-7346]
dc.contributor.orcidCasterad Seral, María Auxiliadora [0000-0003-4458-6966]
dc.date.accessioned2026-01-30T12:30:47Z
dc.date.available2026-01-30T12:30:47Z
dc.date.issued2025-06-23
dc.date.updated2026-01-05T06:56:09Z
dc.description.abstractPhenological parameters extracted from time series (TS) of spectral indices are essential to characterizing crops. However, the lack of data in the TS can affect their accuracy. The Copernicus Land Monitoring Service (CLMS) provides these parameters and their temporal quality. This paper evaluates the impact of missing vegetation index data on phenological parameters, namely, SOS, EOS, and MAX, for extensive arable crop between 2018 and 2023. The TSGenerator package was developed to download, process, and analyze the data. We used 252 images from the BIOPAR-VI module, 6 phenology parameters, and 2025 plots of barley and maize in Monegros and Zaidín, Spain. In barley, SOS and MAX showed 42.9% and 40.9% of missing data, while in maize, SOS and EOS showed 36.6% and 41.0%. The correlation between the Copernicus VPP quality parameter and the proposed one was r = 0.89 for barley and r = 0.74 for maize. This study advances the understanding of the effect of missing data on SOS, EOS, and MAX.
dc.description.peerreviewedSi
dc.description.sponsorshipEste trabajo forman parte del proyecto LAIKcA, PID2021-124029OR-I00, financiado por el MICIU/AEI/ 10.13039/501100011033 y el FEDER/UE.
dc.identifier.citationValero-Jorge, A., Casterad, M. A., & Alcalá, J.-T. (2025). Evaluating the Influence of Missing Data from the Crop Vegetation Index Time Series on Copernicus HR-VPP Phenological Products. Engineering Proceedings, 94(1). https://doi.org/10.3390/engproc2025094004
dc.identifier.doi10.3390/engproc2025094004
dc.identifier.issn2673-4591
dc.identifier.urihttps://doi.org/10.3390/engproc2025094004
dc.identifier.urihttps://hdl.handle.net/10532/8126
dc.language.isoen
dc.publisherMDPI
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-124029OR-I00/ES/Ajuste de ciclos y coeficientes de cultivo para la optimización de la gestión del agua en grandes zonas regables en un contexto de cambio climático/LAIKcA
dc.relation.citaSi
dc.relation.publisherversionhttps://doi.org/10.3390/engproc2025094004
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.agrovocFenología
dc.subject.agrovocImagen multiespectral
dc.subject.agrovocTeledetección
dc.subject.agrovocDatos
dc.subject.agrovocAnálisis de series cronológicas
dc.subject.sdgHambre cero
dc.titleEvaluating the Influence of Missing Data from the Crop Vegetation Index Time Series on Copernicus HR-VPP Phenological Products
dc.typetexto
dc.typecontribución de congreso
dc.typeactas de congreso
dc.typecomunicación de congreso
dc.type.hasVersionversión publicada

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