Global Spatially-Disaggregated Crop Production Statistics Data for 2010

A new version of high-resolution global crop production dataset (known as SPAM) for 2010 is out!
Workflow of Spatial Production Allocation Model (SPAM)

Supported by CGIAR Platform for Big Data in Agriculture, IFPRI’s Spatial Data and Analytics team published a new version of Global Spatially-Disaggregated Crop Production Statistics Data (also known as Spatial Production Allocation Mode, or SPAM) for 2010. This new version, available to download from the Dataverse, marks the third generation of the SPAM data series, following 2000 and 2005.

International Food Policy Research Institute, 2019, “Global Spatially-Disaggregated Crop Production Statistics Data for 2010 Version 2.0”,, Harvard Dataverse, V4

SPAM provides key crop production indicators, including area, production, and yield, for 42 crops — disaggregated at the input-levels (e.g., irrigated/rainfed and high/low-input) on 10 km grids globally. The SPAM team at IFPRI (Liangzhi YouUlrike Wood-SichraZhe Guo, Yating Ru, and Jawoo Koo) works closely with CGIAR’s crop commodity-focused centers (e.g., CIMMYT for maize and wheat, AfricaRice and IRRI for rice, IITA and CIAT for tropical crops such as banana, plantains, and cassava, CIP for potatoes, and ICRISAT for sorghum, millet, and pulses) to collect data, review model results, and improve overall data quality. Over the years IFPRI released two major updates (SPAM 2000 and SPAM 2005) and a number of minor releases. This new version of SPAM 2010 v2.0 addresses all the feedback the team received on the earlier beta version of SPAM 2010.

All data files and documentation are openly provided as a global public good through IFPRI’s data repository, Dataverse. The methodology of SPAM has been thoroughly reviewed and published as peer-reviewed journal articles and technical documents. A number of initiatives and academic journal articles are already using SPAM as their basis of analysis. If you haven’t, try SPAM and join the SPAM Community — your feedback is always welcome!