Multiple factors influence the consistency of cropland datasets in Africa

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cg.authorship.typesCGIAR single centre
cg.authorship.typesCGIAR and developing country institute
cg.contributor.donorNational Key Research and Development Program, China
cg.contributor.donorBeijing Outstanding Young Scientist Program
cg.contributor.donorFundamental Research Funds for the Central Universities, China
cg.coverage.regionNorthern Africa
cg.coverage.regionEastern Africa
cg.coverage.regionMiddle Africa
cg.coverage.regionWestern Africa
cg.coverage.regionAfrica
cg.coverage.regionSub-saharan Africa
cg.coverage.regionSouthern Africa
cg.creator.identifierYating Ru: 0000-0001-9071-0687
cg.identifier.doihttps://doi.org/10.1016/j.jag.2020.102087
cg.identifier.projectIFPRI - Environment and Production Technology Division
cg.identifier.publicationRankB
cg.isijournalISI Journal
cg.issn1569-8432
cg.issue20-Jul
cg.journalInternational Journal of Applied Earth Observation and Geoinformation
cg.number102087
cg.reviewStatusPeer Review
cg.volume89
dc.contributor.authorWei, Yanbing
dc.contributor.authorLu, Miao
dc.contributor.authorWu, Wenbin
dc.contributor.authorRu, Yating
dc.date.accessioned2024-05-22T12:10:48Zen
dc.date.available2024-05-22T12:10:48Zen
dc.identifier.urihttps://hdl.handle.net/10568/142645
dc.titleMultiple factors influence the consistency of cropland datasets in Africaen
dcterms.abstractAccurate geo-information of cropland is critical for food security strategy development and grain production management, especially in Africa continent where most countries are food-insecure. Over the past decades, a series of African cropland maps have been derived from remotely-sensed data, existing comparison studies have shown that inconsistencies with statistics and discrepancies among these products are considerable. Yet, there is a knowledge gap about the factors that influence their consistency. The aim of this study is thus to estimate the consistency of five widely-used cropland datasets (MODIS Collection 5, GlobCover 2009, GlobeLand30, CCI-LC 2010, and Unified Cropland Layer) in Africa, and to explore the effects of several limiting factors (landscape fragmentation, climate and agricultural management) on spatial consistency. The results show that total cropland area for Africa derived from GlobeLand30 has the best fitness with FAO statistics, followed by MODIS Collection 5. GlobCover 2009, CCI-LC 2010, and Unified Cropland Layer have poor performances as indicated by larger deviations from statistics. In terms of spatial consistency, disagreement is about 37.9 % at continental scale, and the disparate proportion even exceeds 50 % in approximately 1/3 of the countries at national scale. We further found that there is a strong and significant correlation between spatial agreement and cropland fragmentation, suggesting that regions with higher landscape fragmentation generally have larger disparities. It is also noticed that places with better consistency are mainly distributed in regions with favorable natural environments and sufficient agricultural management such as well-developed irrigated technology. Proportions of complete agreement are thus located in favorable climate zones including Hot-summer Mediterranean climate (Csa), Subtropical highland climate (Cwb), and Temperate Mediterranean climate (Csb). The level of complete agreement keeps rising as the proportion of irrigated cropland increases. Spatial agreement among these datasets has the most significant relationship with cropland fragmentation, and a relatively small association with irrigation area, followed by climate conditions. These results can provide some insights into understanding how different factors influence the consistency of cropland datasets, and making an appropriate selection when using these datasets in different regions. We suggest that future cropland mapping activities should put more effort in those regions with significant disagreement in Sub-Saharan Africa.en
dcterms.accessRightsOpen Access
dcterms.bibliographicCitationWei, Yanbing; Lu, Miao; Wu, Wenbin; and Ru, Yating. 2020. Multiple factors influence the consistency of cropland datasets in Africa. International Journal of Applied Earth Observation and Geoinformation Volume 89(July 2020): 102087. https://doi.org/10.1016/j.jag.2020.102087en
dcterms.issued2020-07-01
dcterms.languageen
dcterms.licenseCC-BY-NC-ND-4.0
dcterms.publisherElsevier
dcterms.replaceshttps://ebrary.ifpri.org/digital/collection/p15738coll5/id/7137
dcterms.subjectspatial dataen
dcterms.subjectdatabasesen
dcterms.subjectdataen
dcterms.subjectaccuracyen
dcterms.subjectcartographyen
dcterms.subjectcapacity developmenten
dcterms.subjectfarmlanden
dcterms.subjectland coveren
dcterms.typeJournal Article

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