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- Publisher Website: 10.1080/17538947.2013.822574
- Scopus: eid_2-s2.0-84888134923
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Article: FROM-GC: 30 m global cropland extent derived through multisource data integration
Title | FROM-GC: 30 m global cropland extent derived through multisource data integration |
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Authors | |
Keywords | Landsat FROM-GLC global mapping MODIS FROM-GLC-agg |
Issue Date | 2013 |
Citation | International Journal of Digital Earth, 2013, v. 6, n. 6, p. 521-533 How to Cite? |
Abstract | We 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 Identifier | http://hdl.handle.net/10722/296725 |
ISSN | 2023 Impact Factor: 3.7 2023 SCImago Journal Rankings: 0.950 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Yu, Le | - |
dc.contributor.author | Wang, Jie | - |
dc.contributor.author | Clinton, Nicholas | - |
dc.contributor.author | Xin, Qinchuan | - |
dc.contributor.author | Zhong, Liheng | - |
dc.contributor.author | Chen, Yanlei | - |
dc.contributor.author | Gong, Peng | - |
dc.date.accessioned | 2021-02-25T15:16:32Z | - |
dc.date.available | 2021-02-25T15:16:32Z | - |
dc.date.issued | 2013 | - |
dc.identifier.citation | International Journal of Digital Earth, 2013, v. 6, n. 6, p. 521-533 | - |
dc.identifier.issn | 1753-8947 | - |
dc.identifier.uri | http://hdl.handle.net/10722/296725 | - |
dc.description.abstract | We 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.language | eng | - |
dc.relation.ispartof | International Journal of Digital Earth | - |
dc.subject | Landsat | - |
dc.subject | FROM-GLC | - |
dc.subject | global mapping | - |
dc.subject | MODIS | - |
dc.subject | FROM-GLC-agg | - |
dc.title | FROM-GC: 30 m global cropland extent derived through multisource data integration | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1080/17538947.2013.822574 | - |
dc.identifier.scopus | eid_2-s2.0-84888134923 | - |
dc.identifier.volume | 6 | - |
dc.identifier.issue | 6 | - |
dc.identifier.spage | 521 | - |
dc.identifier.epage | 533 | - |
dc.identifier.eissn | 1753-8955 | - |
dc.identifier.isi | WOS:000330015800001 | - |
dc.identifier.issnl | 1753-8947 | - |