A synergy cropland of China by fusing multiple existing maps and statistics

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dc.creatorLu, Miao
dc.creatorWu, Wenbin
dc.creatorYou, Liangzhi
dc.creatorChen, Di
dc.creatorZhang, Li
dc.creatorYang, Peng
dc.creatorTang, Huajun
dc.date2017
dc.date2024-06-21T09:06:11Z
dc.date2024-06-21T09:06:11Z
dc.date.accessioned2026-06-27T15:16:29Z
dc.descriptionAccurate information on cropland extent is critical for scientific research and resource management. Several cropland products from remotely sensed datasets are available. Nevertheless, significant inconsistency exists among these products and the cropland areas estimated from these products differ considerably from statistics. In this study, we propose a hierarchical optimization synergy approach (HOSA) to develop a hybrid cropland map of China, circa 2010, by fusing five existing cropland products, i.e., GlobeLand30, Climate Change Initiative Land Cover (CCI-LC), GlobCover 2009, MODIS Collection 5 (MODIS C5), and MODIS Cropland, and sub-national statistics of cropland area. HOSA simplifies the widely used method of score assignment into two steps, including determination of optimal agreement level and identification of the best product combination. The accuracy assessment indicates that the synergy map has higher accuracy of spatial locations and better consistency with statistics than the five existing datasets individually. This suggests that the synergy approach can improve the accuracy of cropland mapping and enhance consistency with statistics.
dc.identifierhttps://hdl.handle.net/10568/146209
dc.identifier.urihttp://hdl.handle.net/123456789/99604
dc.languageen
dc.publisherMDPI
dc.rightsOpen Access
dc.sourceLu, Miao; Wu, Wenbin; You, Liangzhi; Chen, Di; Zhang, Li; Yang, Peng; and Tang, Huajun. 2017. A synergy cropland of China by fusing multiple existing maps and statistics. Sensors 17(7): 1613. https://doi.org/10.3390/s17071613
dc.subjectdata fusion
dc.subjectland-use mapping
dc.subjectremote sensing
dc.subjectcartography
dc.subjectfarmland
dc.subjectland cover mapping
dc.subjectsynergism
dc.subjectstatistics
dc.titleA synergy cropland of China by fusing multiple existing maps and statistics
dc.typeJournal Article

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Instituto Internacional de Investigación sobre Políticas Alimentarias (IFPRI)