dc.creatorBontemps, Sophie
dc.creatorArias, Marcela
dc.creatorCara, Cosmin
dc.creatorDedieu, Gérard
dc.creatorGuzzonato, Eric
dc.creatorHagolle, Olivier
dc.creatorInglada, Jordi
dc.creatorMatton, Nicolas
dc.creatorMorin, David
dc.creatorPopescu, Ramona
dc.creatorRabaute, Thierry
dc.creatorSavinaud, Mickael
dc.creatorSepulcre, Guadalupe
dc.creatorValero, Silvia
dc.creatorAhmad, Ijaz
dc.creatorBégué, Agnès
dc.creatorWu, Bingfang
dc.creatorDe Abelleyra, Diego
dc.creatorDiarra, Alhousseine
dc.creatorDupuy, Stéphane
dc.creatorFrench, Andrew
dc.creatorAkhtar, Ibrar ul Hassan
dc.creatorKussul, Nataliia
dc.creatorLebourgeois, Valentine
dc.creatorLe Page, Michel
dc.creatorNewby, Terrence
dc.creatorSavin, Igor
dc.creatorVeron, Santiago Ramón
dc.creatorKoetz, Benjamin
dc.creatorDefourny, Pierre
dc.date.accessioned2019-07-18T13:22:08Z
dc.date.accessioned2023-03-15T14:00:35Z
dc.date.available2019-07-18T13:22:08Z
dc.date.available2023-03-15T14:00:35Z
dc.date.created2019-07-18T13:22:08Z
dc.date.issued2015-12
dc.identifier2072-4292
dc.identifierhttps://doi.org/10.3390/rs71215815
dc.identifierhttps://www.mdpi.com/2072-4292/7/12/15815
dc.identifierhttp://hdl.handle.net/20.500.12123/5524
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/6208666
dc.description.abstractDeveloping better agricultural monitoring capabilities based on Earth Observation data is critical for strengthening food production information and market transparency. The Sentinel-2 mission has the optimal capacity for regional to global agriculture monitoring in terms of resolution (10–20 meter), revisit frequency (five days) and coverage (global). In this context, the European Space Agency launched in 2014 the “Sentinel­2 for Agriculture” project, which aims to prepare the exploitation of Sentinel-2 data for agriculture monitoring through the development of open source processing chains for relevant products. The project generated an unprecedented data set, made of “Sentinel-2 like” time series and in situ data acquired in 2013 over 12 globally distributed sites. Earth Observation time series were mostly built on the SPOT4 (Take 5) data set, which was specifically designed to simulate Sentinel-2. They also included Landsat 8 and RapidEye imagery as complementary data sources. Images were pre-processed to Level 2A and the quality of the resulting time series was assessed. In situ data about cropland, crop type and biophysical variables were shared by site managers, most of them belonging to the “Joint Experiment for Crop Assessment and Monitoring” network. This data set allowed testing and comparing across sites the methodologies that will be at the core of the future “Sentinel­2 for Agriculture” system.
dc.languageeng
dc.publisherMDPI
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourceRemote Sensing 7 (12) : 16062-16090 (December 2015)
dc.subjectImágenes por Satélites
dc.subjectAgricultura
dc.subjectSensores
dc.subjectVigilancia
dc.subjectSatellite Imagery
dc.subjectAgriculture
dc.subjectSensors
dc.subjectMonitoring
dc.titleBuilding a Data Set over 12 Globally Distributed Sites to Support the Development of Agriculture Monitoring Applications with Sentinel-2
dc.typeinfo:ar-repo/semantics/artículo
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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