Historical Crop Data
Originators of data
Dr. Navin Ramankutty and Dr. Jonathan Foley
Data provider's notes
Data format and file size: NetCDF, 46 Mbytes
The data presented here derive from a compilation of secondary data, not primary data. Agriculture inventory data were compiled from around the world over a period of a few years and calibrated them against satellite data.
There are two sources of global land cover/land use data. The most recent estimates are derived from satellite measurements, and are available in a spatially-explicit fashion for roughly the last 30 years. The other estimate is based on ground-based sources such as census statistics, land surveys, estimates by historical geographers, etc. These land inventory data are only available at the scale of political units, but have the advantage of being historical.
Ramankutty and Foley (1998) derived a spatially-explicit data set of croplands in 1992 by synthesizing remotely-sensed land cover data with contemporary land inventory data. Furthermore, Ramankutty and Foley (1999) extended this data set into the past (back to 1700) using historical land inventory data.
1 km resolution global land cover classification data developed at the EROS data center (Loveland et al., 2000). The base satellite data for the 1 km land cover product was monthly composites of the AVHRR NDVI measurements over the April 1992-March 1993 period.
Ground-based sources such as national census statistics (usually based on questionnaires), compilation/estimates by historical geographers (often based on tax records, land surveys, cadastral maps, etc.)
The data set should only be used for continental-to-global scale analysis and modeling. The data set captures the broad patterns of cropland change over history, but not necessarily the fine details at local to regional scales - please check the data quality before using it at fine spatial scales. The quality of historical data for the Russian Federation and African continent is poor. The quality of data prior to 1850 is poor -- only continental-scale historical data were used for that period.
The definition of croplands is problematic - different countries report the data differently. Our calibration procedure avoids some of the most egregious problems, but unknown errors in the census data likely persist. Also, there is inconsistency between what the satellite instrument is capable of seeing, compared to the ground-based observations. For example, tree crops are considered croplands in the ground-based inventory, but it is not clear how the satellite-based land-cover data classified that category.
These data were filtered prior to use. When the satellite-based land-cover data set was calibrated against the ground-based inventory data, outliers in the regression were omitted from the regression (presumed errors in the census data). Under these circumstances, satellite data was used instead.
Center for Sustainability and the Global Environment
University of Wisconsin-Madison, U.S.A.
Use restrictions on data set: None
Instrumental information
Instrumental limitations
Corrections applied to these data
Publications describing these data: