Global Croplands and Watering Source

Global cropland extent including information regarding if the crops are rainfed or irrigated

  • Source: USGS/BAERI/SESES/ICRISAT/USGS EROS/U Wisconsin/UNH/NASA GSFC
  • Last update: -

The Global Food Security-Support Analysis Data (GFSAD) set is an aggregate of 4 global cropland products. Together they produce a unified global cropland extent map at nominal 1 km resolution called the Global Cropland Extent, Version 1 (GCE V1.0). Developing an advanced global cropland area database (GCAD) with an ability to map global croplands and their attributes routinely, rapidly, consistently, and with sufficient accuracies helps determine how global croplands are used and how they might be better managed to optimize use of resources in food production. The process of aggregating the 4 global cropland products involved resampling each global cropland product to a common resolution of 1 km and then performing GIS data overlays to determine where the cropland extents mapped by these products match and where they differ. All 4 products have considerable uncertainties in determining the precise location of the croplands. The great degree of uncertainty in the cropland products can be attributed to factors such as coarse resolution, methods used, approaches adopted, and limitations of the data such as saturation. The 3 global cropland maps were produced by Thenkabail et al. (Thenkabail et al. 2009b; Biradar et al. 2009; Thenkabail et al. 2011; Pittman et al. 2010; Yu et al. 2013). A recent MODIS global land cover and land use map where croplands have also been mapped created by Friedl et al. (2010) was also used. Thenkabail et al. (2009b, 2011) used a combination of AVHRR (Advanced High Resolution Radiometer), SPOT VGT (Satellite pour l’Observation de la Terre, Végétation), and numerous secondary (e.g., precipitation, temperature, and elevation) data to produce a global irrigated area map (Thenkabail et al. 2009b, 2011) and a global map of rainfed cropland areas (Biradar et al. 2009; Thenkabail et al. 2011, Figure 8, Table 3). Pittman et al. (2010) used MODIS (Moderate Resolution Imaging Spectroradiometer) 250 m data to develop cropland extent of the world. More recently, Yu et al. (2013) produced a nominal 30 m resolution cropland extent of the world. The result of the aggregation produced 5 classes: (0) Noncroplands; (1) Croplands, Irrigation major; (2) Croplands, Irrigation minor; (3) Croplands, Rainfed; (4) Croplands, Rainfed minor fragments; (5) Croplands, Rainfed very minor fragments. Resource Watch shows only a subset of the data set. For access to the full data set and additional information, see the Learn More link.

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Formal name

Global Cropland Extent and Watering Source

Cautions

Only 20% of the total cropland extent is matched precisely in all 4 products. Further, 49% of the total cropland areas match in at least 3 of the 4 products. This implies that all 4 products have considerable uncertainties in determining the precise location of the croplands. The great degree of uncertainty in the cropland products can be attributed to factors such as the following: (1) Coarse resolution of the imagery used in the study; (2) Definition of mapping; (3) Methods used; (4) Approaches adopted; and (5) Limitations of the data such as saturation.

Suggested citation

(1) Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Food Security-Support Analysis Data (GFSAD). 2015. GFSAD 30-Meter Cropland Extent Products. Sioux Falls, SD: NASA EOSDIS Land Processes DAAC, USGS Earth Resources Observation and Science (EROS) Center (https://lpdaac.usgs.gov). Accessed December 20, 2017. https://lpdaac.usgs.gov/about/news_archive/release_gfsad_30_meter_cropland_extent_products. Accessed through Resource Watch, (date). www.resourcewatch.org.

(2) Thenkabail, P.S., J.W. Knox, M. Ozdogan, M.K. Gumma, R.G. Congalton, Z. Wu, C. Milesi, A. Finkral, M. Marshall, I. Mariotto, S. You, C. Giri, and P. Nagler. 2012. “Assessing Future Risks to Agricultural Productivity, Water Resources, and Food Security: How Can Remote Sensing Help?” In “Global Croplands,” special issue of Photogrammetric Engineering and Remote Sensing 78 (8) (August 2012): 773-82. Accessed through Resource Watch, (date). www.resourcewatch.org.

(3) Teluguntla, P., P.S. Thenkabail, J. Xiong, M.K. Gumma, C. Giri, C. Milesi, M. Ozdogan, R. Congalton, J. Tilton, T.R. Sankey, R. Massey, A. Phalke, and K. Yadav. 2014. “Global Cropland Area Database (GCAD).” Derived from “Remote Sensing in Support of Food Security in the Twenty-First Century: Current Achievements and Future Possibilities,” chap. 7 of Land Resources Monitoring, Modeling, and Mapping with Remote Sensing, edited by Prasad S. Thenkabail, vol. 2 of Remote Sensing Handbook. Boca Raton, FL: CRC, 2015. Accessed through Resource Watch, (date). www.resourcewatch.org.

Sources

United States Geological Survey (USGS)
Bay Area Environmental Research Institute (BAERI)
School of Earth Sciences and Environmental Sustainability, Northern Arizona University (SESES Northern Arizona U)
International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
United States Geological Survey EROS Center (USGS EROS)
National Aeronautics and Space Agency Ames Research Center (NASA Ames Research Center)
University of Wisconsin (U Wisconsin)
University of New Hampshire (UNH)
National Aeronautics and Space Administration Goddard Space Flight Centre (NASA GSFC)

Geographic coverage

Global

Spatial resolution

1 km

Date of content

2010

Published language

en

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