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Article: FROM-GC: 30 m global cropland extent derived through multisource data integration

TitleFROM-GC: 30 m global cropland extent derived through multisource data integration
Authors
KeywordsLandsat
FROM-GLC
global mapping
MODIS
FROM-GLC-agg
Issue Date2013
Citation
International Journal of Digital Earth, 2013, v. 6, n. 6, p. 521-533 How to Cite?
AbstractWe report on a global cropland extent product at 30-m spatial resolution developed with two 30-m global land cover maps (i.e. FROM-GLC, Finer Resolution Observation and Monitoring, Global Land Cover; FROM-GLC-agg) and a 250-m cropland probability map. A common land cover validation sample database was used to determine optimal thresholds of cropland probability in different parts of the world to generate a cropland/noncropland mask according to the classification accuracies for cropland samples. A decision tree was then applied to combine two 250-m cropland masks: one existing mask from the literature and the other produced in this study, with the 30-m global land cover map FROM-GLC-agg. For the smallest difference with country-level cropland area in Food and Agriculture Organization Corporate Statistical (FAOSTAT) database, a final global cropland extent map was composited from the FROM-GLC, FROM-GLC-agg, and two masked cropland layers. From this map FROM-GC (Global Cropland), we estimated the global cropland areas to be 1533.83 million hectares (Mha) in 2010, which is 6.95 Mha (0.45%) less than the area reported by the Food and Agriculture Organization (FAO) of the United Nations for the year 2010. A country-by-country comparison between the map and the FAOSTAT data showed a linear relationship (FROM-GC = 1.05*FAOSTAT -1.2 (Mha) with R2= 0.97). Africa, South America, Southeastern Asia, and Oceania are the regions with large discrepancies with the FAO survey. © 2013 Taylor & Francis.
Persistent Identifierhttp://hdl.handle.net/10722/296725
ISSN
2023 Impact Factor: 3.7
2023 SCImago Journal Rankings: 0.950
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYu, Le-
dc.contributor.authorWang, Jie-
dc.contributor.authorClinton, Nicholas-
dc.contributor.authorXin, Qinchuan-
dc.contributor.authorZhong, Liheng-
dc.contributor.authorChen, Yanlei-
dc.contributor.authorGong, Peng-
dc.date.accessioned2021-02-25T15:16:32Z-
dc.date.available2021-02-25T15:16:32Z-
dc.date.issued2013-
dc.identifier.citationInternational Journal of Digital Earth, 2013, v. 6, n. 6, p. 521-533-
dc.identifier.issn1753-8947-
dc.identifier.urihttp://hdl.handle.net/10722/296725-
dc.description.abstractWe report on a global cropland extent product at 30-m spatial resolution developed with two 30-m global land cover maps (i.e. FROM-GLC, Finer Resolution Observation and Monitoring, Global Land Cover; FROM-GLC-agg) and a 250-m cropland probability map. A common land cover validation sample database was used to determine optimal thresholds of cropland probability in different parts of the world to generate a cropland/noncropland mask according to the classification accuracies for cropland samples. A decision tree was then applied to combine two 250-m cropland masks: one existing mask from the literature and the other produced in this study, with the 30-m global land cover map FROM-GLC-agg. For the smallest difference with country-level cropland area in Food and Agriculture Organization Corporate Statistical (FAOSTAT) database, a final global cropland extent map was composited from the FROM-GLC, FROM-GLC-agg, and two masked cropland layers. From this map FROM-GC (Global Cropland), we estimated the global cropland areas to be 1533.83 million hectares (Mha) in 2010, which is 6.95 Mha (0.45%) less than the area reported by the Food and Agriculture Organization (FAO) of the United Nations for the year 2010. A country-by-country comparison between the map and the FAOSTAT data showed a linear relationship (FROM-GC = 1.05*FAOSTAT -1.2 (Mha) with R2= 0.97). Africa, South America, Southeastern Asia, and Oceania are the regions with large discrepancies with the FAO survey. © 2013 Taylor & Francis.-
dc.languageeng-
dc.relation.ispartofInternational Journal of Digital Earth-
dc.subjectLandsat-
dc.subjectFROM-GLC-
dc.subjectglobal mapping-
dc.subjectMODIS-
dc.subjectFROM-GLC-agg-
dc.titleFROM-GC: 30 m global cropland extent derived through multisource data integration-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/17538947.2013.822574-
dc.identifier.scopuseid_2-s2.0-84888134923-
dc.identifier.volume6-
dc.identifier.issue6-
dc.identifier.spage521-
dc.identifier.epage533-
dc.identifier.eissn1753-8955-
dc.identifier.isiWOS:000330015800001-
dc.identifier.issnl1753-8947-

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