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Accurate cropland information is of paramount importance for crop monitoring. This study compares five existing cropland mapping methodologies over five contrasting Joint Experiment for Crop Assessment and Monitoring (JECAM) sites of medium to large average field size using the time series of 7-day 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) mean composites (red and near-infrared channels). Different strategies were devised to assess the [ver mas...]
dc.contributor.authorWaldner, François
dc.contributor.authorDe Abelleyra, Diego
dc.contributor.authorVeron, Santiago Ramón
dc.contributor.authorZhang, Miao
dc.contributor.authorWu, Bingfang
dc.contributor.authorPlotnikov, Dmitry
dc.contributor.authorBartalev, Sergey
dc.contributor.authorLavreniuk, Mykola
dc.contributor.authorSkakun, Sergii
dc.contributor.authorKussul, Nataliia
dc.contributor.authorLe Maire, Guerric
dc.contributor.authorDupuy, Stéphane
dc.contributor.authorJarvis, Ian
dc.contributor.authorDefourny, Pierre
dc.date.accessioned2018-12-11T15:42:01Z
dc.date.available2018-12-11T15:42:01Z
dc.date.issued2016
dc.identifier.issn0143-1161
dc.identifier.issn1366-5901 (Online)
dc.identifier.otherhttps://doi.org/10.1080/01431161.2016.1194545
dc.identifier.urihttp://hdl.handle.net/20.500.12123/4057
dc.identifier.urihttps://www.tandfonline.com/doi/full/10.1080/01431161.2016.1194545
dc.description.abstractAccurate cropland information is of paramount importance for crop monitoring. This study compares five existing cropland mapping methodologies over five contrasting Joint Experiment for Crop Assessment and Monitoring (JECAM) sites of medium to large average field size using the time series of 7-day 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) mean composites (red and near-infrared channels). Different strategies were devised to assess the accuracy of the classification methods: confusion matrices and derived accuracy indicators with and without equalizing class proportions, assessing the pairwise difference error rates and accounting for the spatial resolution bias. The robustness of the accuracy with respect to a reduction of the quantity of calibration data available was also assessed by a bootstrap approach in which the amount of training data was systematically reduced. Methods reached overall accuracies ranging from 85% to 95%, which demonstrates the ability of 250 m imagery to resolve fields down to 20 ha. Despite significantly different error rates, the site effect was found to persistently dominate the method effect. This was confirmed even after removing the share of the classification due to the spatial resolution of the satellite data (from 10% to 30%). This underlines the effect of other agrosystems characteristics such as cloudiness, crop diversity, and calendar on the ability to perform accurately. All methods have potential for large area cropland mapping as they provided accurate results with 20% of the calibration data, e.g. 2% of the study area in Ukraine. To better address the global cropland diversity, results advocate movement towards a set of cropland classification methods that could be applied regionally according to their respective performance in specific landscapes.eng
dc.formatapplication/pdfeng
dc.language.isoeng
dc.publisherInforma UK Limitedeng
dc.rightsinfo:eu-repo/semantics/openAccesseng
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.sourceInternational journal of remote sensing 37 (14) : 3196–3231. (2016)eng
dc.subjectAgroecosistemases_AR
dc.subjectAgroecosystemseng
dc.subjectTierras Agrícolases_AR
dc.subjectFarmlandeng
dc.subjectLand Use Mappingeng
dc.subjectCartografía del Uso de la Tierraes_AR
dc.subjectSistema de Posicionamiento Global
dc.subjectGlobal Positioning Systemseng
dc.subject.otherModerate Resolution Imaging Spectroradiometereng
dc.subject.otherMODISeng
dc.titleTowards a set of agrosystem-specific cropland mapping methods to address the global cropland diversityeng
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articleeng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.rights.licenseCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.description.origenInstituto de Clima y Aguaes_AR
dc.description.filFil: Waldner, François. Université catholique de Louvain. Earth and Life Institute - Environment, Croix du Sud; Belgicaes_AR
dc.description.filFil: De Abelleyra, Diego. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentinaes_AR
dc.description.filFil: Veron, Santiago Ramón. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentinaes_AR
dc.description.filFil: Zhang, Miao. Chinese Academy of Science. Institute of Remote Sensing and Digital Earth; Chinaes_AR
dc.description.filFil: Wu, Bingfang. Chinese Academy of Science. Institute of Remote Sensing and Digital Earth; Chinaes_AR
dc.description.filFil: Plotnikov, Dmitry. Russian Academy of Sciences. Space Research Institute. Terrestrial Ecosystems Monitoring Laboratory; Rusiaes_AR
dc.description.filFil: Bartalev, Sergey. Russian Academy of Sciences. Space Research Institute. Terrestrial Ecosystems Monitoring Laboratory; Rusiaes_AR
dc.description.filFil: Lavreniuk, Mykola. Space Research Institute NAS and SSA. Department of Space Information Technologies; Ucraniaes_AR
dc.description.filFil: Skakun, Sergii. Space Research Institute NAS and SSA. Department of Space Information Technologies; Ucrania. University of Maryland. Department of Geographical Sciences; Estados Unidoses_AR
dc.description.filFil: Kussul, Nataliia. Space Research Institute NAS and SSA. Department of Space Information Technologies; Ucraniaes_AR
dc.description.filFil: Le Maire, Guerric. UMR Eco&Sols, CIRAD; Francia. Empresa Brasileira de Pesquisa Agropecuária. Meio Ambiante; Brasiles_AR
dc.description.filFil: Dupuy, Stéphane. Centre de Coopération Internationale en Recherche Agronomique pour le Développement. Territoires, Environnement, Télédétection et Information Spatiale; Franciaes_AR
dc.description.filFil: Jarvis, Ian. Agriculture and Agri-Food Canada. Science and Technology Branch. Agri-Climate, Geomatics and Earth Observation; Canadáes_AR
dc.description.filFil: Defourny, Pierre. Université Catholique de Louvain. Earth and Life Institute - Environment, Croix du Sud; Belgicaes_AR
dc.subtypecientifico


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