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Article: A unified cropland layer at 250 m for global agriculture monitoring

TitleA unified cropland layer at 250 m for global agriculture monitoring
Authors
KeywordsCropland map
Multi-criteria analysis
Agriculture
Global
Accuracy assessment
Issue Date2016
Citation
Data, 2016, v. 1, n. 1, article no. 3 How to Cite?
AbstractAccurate and timely information on the global cropland extent is critical for food security monitoring, water management and earth system modeling. Principally, it allows for analyzing satellite image time-series to assess the crop conditions and permits isolation of the agricultural component to focus on food security and impacts of various climatic scenarios. However, despite its critical importance, accurate information on the spatial extent, cropland mapping with remote sensing imagery remains a major challenge. Following an exhaustive identification and collection of existing land cover maps, a multi-criteria analysis was designed at the country level to evaluate the fitness of a cropland map with regards to four dimensions: its timeliness, its legend, its resolution adequacy and its confidence level. As a result, a Unified Cropland Layer that combines the fittest products into a 250 m global cropland map was assembled. With an evaluated accuracy ranging from 82% to 95%, the Unified Cropland Layer successfully improved the accuracy compared to single global products.
Persistent Identifierhttp://hdl.handle.net/10722/296788

 

DC FieldValueLanguage
dc.contributor.authorWaldner, François-
dc.contributor.authorFritz, Steffen-
dc.contributor.authorDi Gregorio, Antonio-
dc.contributor.authorPlotnikov, Dmitry-
dc.contributor.authorBartalev, Sergey-
dc.contributor.authorKussul, Nataliia-
dc.contributor.authorGong, Peng-
dc.contributor.authorThenkabail, Prasad-
dc.contributor.authorHazeu, Gerard-
dc.contributor.authorKlein, Igor-
dc.contributor.authorLöw, Fabian-
dc.contributor.authorMiettinen, Jukka-
dc.contributor.authorDadhwal, Vinay Kumar-
dc.contributor.authorLamarche, Céline-
dc.contributor.authorBontemps, Sophie-
dc.contributor.authorDefourny, Pierre-
dc.date.accessioned2021-02-25T15:16:41Z-
dc.date.available2021-02-25T15:16:41Z-
dc.date.issued2016-
dc.identifier.citationData, 2016, v. 1, n. 1, article no. 3-
dc.identifier.urihttp://hdl.handle.net/10722/296788-
dc.description.abstractAccurate and timely information on the global cropland extent is critical for food security monitoring, water management and earth system modeling. Principally, it allows for analyzing satellite image time-series to assess the crop conditions and permits isolation of the agricultural component to focus on food security and impacts of various climatic scenarios. However, despite its critical importance, accurate information on the spatial extent, cropland mapping with remote sensing imagery remains a major challenge. Following an exhaustive identification and collection of existing land cover maps, a multi-criteria analysis was designed at the country level to evaluate the fitness of a cropland map with regards to four dimensions: its timeliness, its legend, its resolution adequacy and its confidence level. As a result, a Unified Cropland Layer that combines the fittest products into a 250 m global cropland map was assembled. With an evaluated accuracy ranging from 82% to 95%, the Unified Cropland Layer successfully improved the accuracy compared to single global products.-
dc.languageeng-
dc.relation.ispartofData-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectCropland map-
dc.subjectMulti-criteria analysis-
dc.subjectAgriculture-
dc.subjectGlobal-
dc.subjectAccuracy assessment-
dc.titleA unified cropland layer at 250 m for global agriculture monitoring-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.3390/data1010003-
dc.identifier.scopuseid_2-s2.0-84982944935-
dc.identifier.volume1-
dc.identifier.issue1-
dc.identifier.spagearticle no. 3-
dc.identifier.epagearticle no. 3-
dc.identifier.eissn2306-5729-
dc.identifier.issnl2306-5729-

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