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A Unified Cropland Layer at 250 m for Global Agriculture Monitoring

Earth and Life Institute, Université catholique de Louvain, Croix du Sud, 1348 Louvain-la-Neuve, Belgium
International Institute for Applied Systems Analysis (IIASA), 2361 Laxenburg, Austria
Food and Agriculture Organisation (FAO), 00153 Rome, Italy
Space Research Institute (IKI), Russian Academy of Sciences, Profsoyuznaya str. 117997 Moscow, Russia
Space Research Institute NAS & SSA (SRI), Glushkov Prospekt 40, 03680 Kyiv, Ukraine
Tsinghua University, 30 Shuang Qing Lu, Tsinghua University, 30 Shuang Qing Lu Beijing, China
United States Geological Survey, Flagstaff, Arizona 86001, USA
Alterra, Droevendaalsesteeg, 6708 PB Wageningen, The Netherlands
Deutschen Zentrums für Luft- und Raumfahrt (DLR), Linder Höhe, 51147 Cologne, Germany
Bonn University, 53113 Bonn, Germany
Centre for Remote Imaging, Sensing and Processing (CRISP) at the National University of Singapore (NUS), Singapore, Singapore
National Remote Sensing Centre, ISRO, Balanagar, Hyderabad 500037, India
Author to whom correspondence should be addressed.
Academic Editors: Juan C. Jiménez-Muñoz and Jamal Jokar Arsanjani
Received: 22 January 2016 / Revised: 4 March 2016 / Accepted: 9 March 2016 / Published: 19 March 2016
(This article belongs to the Special Issue Geospatial Data)
Accurate 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. View Full-Text
Keywords: global; agriculture; cropland map; multi-criteria analysis; accuracy assessment global; agriculture; cropland map; multi-criteria analysis; accuracy assessment
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MDPI and ACS Style

Waldner, F.; Fritz, S.; Di Gregorio, A.; Plotnikov, D.; Bartalev, S.; Kussul, N.; Gong, P.; Thenkabail, P.; Hazeu, G.; Klein, I.; Löw, F.; Miettinen, J.; Dadhwal, V.K.; Lamarche, C.; Bontemps, S.; Defourny, P. A Unified Cropland Layer at 250 m for Global Agriculture Monitoring. Data 2016, 1, 3.

AMA Style

Waldner F, Fritz S, Di Gregorio A, Plotnikov D, Bartalev S, Kussul N, Gong P, Thenkabail P, Hazeu G, Klein I, Löw F, Miettinen J, Dadhwal VK, Lamarche C, Bontemps S, Defourny P. A Unified Cropland Layer at 250 m for Global Agriculture Monitoring. Data. 2016; 1(1):3.

Chicago/Turabian Style

Waldner, François, Steffen Fritz, Antonio Di Gregorio, Dmitry Plotnikov, Sergey Bartalev, Nataliia Kussul, Peng Gong, Prasad Thenkabail, Gerard Hazeu, Igor Klein, Fabian Löw, Jukka Miettinen, Vinay K. Dadhwal, Céline Lamarche, Sophie Bontemps, and Pierre Defourny. 2016. "A Unified Cropland Layer at 250 m for Global Agriculture Monitoring" Data 1, no. 1: 3.

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