%0 Journal Article %1 noauthororeditor %A Waldner, François %A Fritz, Steffen %A Di Gregorio, Antonio %A Plotnikov, Dmitry %A Bartalev, Sergey %A Kussul, Nataliia %A Gong, Peng %A Thenkabail, Prasad %A Hazeu, Gerard %A Klein, Igor %A Löw, Fabian %A Miettinen, Jukka %A Dadhwal, Vinay Kumar %A Lamarche, Céline %A Bontemps, Sophie %A Defourny, Pierre %D 2016 %J Data %K article Klein LSFE %N 1 %P 1-13 %T A Unified Cropland Layer at 250 m for Global Agriculture Monitoring %U http://elib.dlr.de/111042/ %V 1 %X 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.

@article{noauthororeditor, abstract = {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.}, added-at = {2020-09-11T12:04:50.000+0200}, author = {Waldner, François and Fritz, Steffen and Di Gregorio, Antonio and Plotnikov, Dmitry and Bartalev, Sergey and Kussul, Nataliia and Gong, Peng and Thenkabail, Prasad and Hazeu, Gerard and Klein, Igor and Löw, Fabian and Miettinen, Jukka and Dadhwal, Vinay Kumar and Lamarche, Céline and Bontemps, Sophie and Defourny, Pierre}, biburl = {https://www.bibsonomy.org/bibtex/2974c9592633667ba04a07100d8f3f222/earthobs_uniwue}, interhash = {eb7e98763375960dd7e1e666edf5de00}, intrahash = {974c9592633667ba04a07100d8f3f222}, journal = {Data}, keywords = {article Klein LSFE}, month = mar, number = 1, pages = {1-13}, timestamp = {2020-11-18T22:08:33.000+0100}, title = {A Unified Cropland Layer at 250 m for Global Agriculture Monitoring}, url = {http://elib.dlr.de/111042/}, volume = 1, year = 2016 }