Hydrology and Land Surface Studies

Cropland for sub-Saharan Africa: A synergistic approach using five land cover data sets

  1. Steffen Fritz1,
  2. Liangzhi You2,
  3. Andriy Bun1,
  4. Linda See1,
  5. Ian McCallum1,
  6. Christian Schill3,
  7. Christoph Perger4,
  8. Junguo Liu5,
  9. Matt Hansen6,
  10. Michael Obersteiner1

Article first published online: 23 FEB 2011

DOI: 10.1029/2010GL046213

Issue

Geophysical Research Letters

Geophysical Research Letters

Additional Information

How to Cite

Fritz, S., L. You, A. Bun, L. See, I. McCallum, C. Schill, C. Perger, J. Liu, M. Hansen, and M. Obersteiner (2011), Cropland for sub-Saharan Africa: A synergistic approach using five land cover data sets, Geophys. Res. Lett., 38, L04404, doi:10.1029/2010GL046213.

Author Information

  1. 1

    IIASA, Laxenburg, Austria

  2. 2

    International Food Policy Research Institute, Washington, DC, USA

  3. 3

    Felis, University of Freiburg, Freiburg, Germany

  4. 4

    Fachbereich Geoinformatik, Fachhochschule Wiener Neustadt, Wiener Neustadt, Austria

  5. 5

    School of Nature Conservation, Beijing Forestry University, Beijing, China

  6. 6

    Geographic Information Science Center of Excellence, South Dakota State University, Brookings, South Dakota, USA

Publication History

  1. Issue published online: 23 FEB 2011
  2. Article first published online: 23 FEB 2011
  3. Manuscript Accepted: 12 JAN 2011
  4. Manuscript Revised: 5 JAN 2011
  5. Manuscript Received: 19 NOV 2010

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Keywords:

  • land cover validation;
  • cropland;
  • synergy map;
  • Africa

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.

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