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Cropland for sub‐Saharan Africa: A synergistic approach using five land cover data sets
Author(s) -
Fritz Steffen,
You Liangzhi,
Bun Andriy,
See Linda,
McCallum Ian,
Schill Christian,
Perger Christoph,
Liu Junguo,
Hansen Matt,
Obersteiner Michael
Publication year - 2011
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2010gl046213
Subject(s) - land cover , cover (algebra) , land use , agriculture , agricultural land , environmental science , maximum likelihood , pixel , remote sensing , geography , statistics , computer science , mathematics , artificial intelligence , mechanical engineering , civil engineering , engineering , archaeology
This paper presents a methodology for the creation of a cropland map for Africa through the combination of five existing land cover products: GLC‐2000, MODIS Land Cover, GlobCover, MODIS Crop Likelihood and AfriCover. A synergy map is created in which the products are ranked by experts, which reflects the likelihood or probability that a given pixel is cropland. The cropland map is then calibrated with national and sub‐national crop statistics using a novel approach. Preliminary validation of the map was undertaken and the results are presented. The resulting cropland map has an accuracy of 83%, which is higher than the accuracy of any of the individual maps. The cropland map is freely available at agriculture.geo‐wiki.org.