This study utilized 250m MODIS (MODerate Resolution Imaging Spectroradiometer) data to map global production cropland extent. A set of multi-year MODIS metrics incorporating four MODIS land bands, NDVI (Normalized Difference Vegetation Index) and thermal data was employed to depict cropland phenology over the period 2000-2008. Sub-pixel training datasets were used to generate a set of global classification tree models, resulting in a global per-pixel cropland probability layer. The probability product was then thresholded to create a discrete cropland/non-cropland indicator map using data from the USDA-FAS (Foreign Agricultural Service) Production, Supply and Distribution (PSD) database describing per-country acreage of production field crops.

Five global land cover classifications were subsequently used to perform regional evaluations of the global MODIS cropland extent map. The global probability layer was further examined with reference to four principal global food crops: corn, soybeans, wheat and rice. Overall results indicate that the MODIS layer best depicts regions of intensive broadleaf crop production (corn and soybean), both in correspondence with existing maps and in associated high probability matching thresholds. Probability thresholds for wheat-growing regions were lower, while areas of rice production had the lowest associated confidence. Regions absent of agricultural intensification, such as Africa, are poorly characterized regardless of crop type. The results reflect the value of MODIS as a generic global cropland indicator for intensive agriculture production regions, but with little sensitivity in areas of low agricultural intensification.

This study was conducted as part of the Global Agriculture Monitoring Project (GLAM), a joint NASA, USDA, University of Maryland and South Dakota State University initiative. GLAM has built a global agricultural monitoring system that provides the USDA Foreign Agricultural Service (FAS) scientifically-validated, near-real-time, earth observations products, and analysis tools for crop-condition monitoring and production assessment.

With a spatial resolution of 250m, the Global Cropland Extent product represents the finest-scale global cropland map derived using synoptic inputs, and due to the inclusion of 9 years of MODIS data it is designed to be relatively insensitive to inter-annual variability in depicting core cropland production areas. These products will be incorporated into the decision support system used by FAS analysts to produce global crop production forecasts.

The Global Cropland Extent project was made possible through funding provided by the NASA Applied Science Program and the USDA Foreign Agricultural Service via the Global Agriculture Monitoring (GLAM) project, grant code NNS06AA03A.

The probability and discrete cropland/non-cropland data are available for download by MODIS tile at the full ~250m resolution or as global mosaics at ~1km resolution.

These data may be used for valid scientific or educational purposes as long as proper citations are used. We ask that you credit the Global Cropland Extent data as follows:

Pittman, K., Hansen, M.C., Becker-Reshef, I., Potapov, P.V., Justice, C.O. (2010) Estimating Global Cropland Extent with Multi-year MODIS Data. Remote Sensing, in press.

For further information, please contact:

Dr. Matthew Hansen
Department of Geographical Sciences - UMD
Phone: (301) 405-9714

Dr. Peter Potapov
Department of Geographical Sciences - UMD
Phone: (301) 405-2129