Satellite detection of rising maize yield heterogeneity in the U.S. Midwest

David Lobell and George Azzari



The future trajectory of crop yields in the United States will influence food supply and land use worldwide. We examine maize and soybean yields for 2000–2015 in the Midwestern U.S. using a new satellite-based dataset on crop yields at 30m resolution. We quantify heterogeneity both within and between fields, and find that the difference between average and top yielding fields is typically below 30% for both maize and soybean, as expected in advanced agricultural regions. In most counties, within-field heterogeneity is at least half as large as overall heterogeneity, illustrating the importance of non-management factors such as soil and landscape position. Surprisingly, we find that yield heterogeneity is rising in maize, both between and within fields, with average yield differences between the best and worst soils more than doubling since 2000. Heterogeneity trends were insignificant for soybean. The findings are consistent both with recent adoption of precision agriculture technologies and with recent trends toward denser sowing in maize, which disproportionately raise yields on better soils. The results imply that yield gains in the region are increasingly derived from the more productive land, and that sub-field precision management of nutrients and other inputs is increasingly warranted.


  • Landsat-based SCYM average maize yield for US corn belt

  • MODIS-based SCYM average maize yield for US corn belt

  • Landsat-based SCYM average soybean yield for US corn belt

  • MODIS-based SCYM average soybean yield for US corn belt

David Lobell and George Azzari

Satellite Detection of Rising Maize Yield Heterogeneity in the U.S. Midwest.

Environmental Research Letter, 2017, Volume 12, Number 1.