Illinois Data Bank - Dataset

Data for: Probabilistic global maps of crop-specific areas from 1961 to 2014
Cite this dataset:
Jackson, Nicole; Konar, Megan; Debaere, Peter; Estes, Lyndon (2019): Data for: Probabilistic global maps of crop-specific areas from 1961 to 2014. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7439710_V1
Dataset Description

Agriculture has substantial socioeconomic and environmental impacts that vary between crops. However, information on how the spatial distribution of specific crops has changed over time across the globe is relatively sparse. We introduce the Probabilistic Cropland Allocation Model (PCAM), a novel algorithm to estimate where specific crops have likely been grown over time. Specifically, PCAM downscales annual and national-scale data on the crop-specific area harvested of 17 major crops to a global 0.5-degree grid from 1961-2014.

The resulting database presented here provides annual global gridded likelihood estimates of crop-specific areas. Both mean and standard deviations of grid cell fractions are available for each of the 17 crops. Each netCDF file contains an individual year of data with an additional variable ("crs") that defines the coordinate reference system used. Our results provide new insights into the likely changes in the spatial distribution of major crops over the past half-century. For additional information, please see the related paper by Jackson et al. (2019) in Environmental Research Letters (https://doi.org/10.1088/1748-9326/ab3b93).
Subject Technology and Engineering
Keywords global; gridded; probabilistic allocation; crop suitability; agricultural geography; time series
License CC BY
Funder U.S. National Science Foundation (NSF)-Grant:ACI-1639529
Funder U.S. National Science Foundation (NSF)-Grant:EAR-1534544
Funder U.S. National Science Foundation (NSF)-Grant:CBET-1844773
Corresponding Creator Megan Konar
Downloaded 3996 times
Version DOI Comment Publication Date
1 10.13012/B2IDB-7439710_V1 2019-09-01

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Contact the Research Data Service for help interpreting this log.

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Dataset update: {"publication_state"=>["file embargo", "released"]} 2019-09-28T06:00:07Z
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Creator update: {"email"=>["lestes@princeton.edu", "lestes@clarku.edu"]} 2019-08-28T14:34:18Z
Dataset update: {"description"=>["Agriculture has substantial socioeconomic and environmental impacts that vary between crops. However, information on how the spatial distribution of specific crops has changed over time across the globe is relatively sparse. We introduce the Probabilistic Cropland Allocation Model (PCAM), a novel algorithm to estimate where specific crops have likely been grown over time. Specifically, PCAM downscales annual and national-scale data on the crop-specific area harvested of 17 major crops to a global 0.5-degree grid from 1961-2014. \r\n\r\nThe resulting database presented here provides annual global gridded likelihood estimates of crop-specific areas. Both mean and standard deviations of grid cell fractions are available for each of the 17 crops. Our results provide new insights into the likely changes in the spatial distribution of major crops over the past half-century. For additional information, please see the related paper by Jackson et al. (2019) in Environmental Research Letters (https://doi.org/10.1088/1748-9326/ab3b93).", "Agriculture has substantial socioeconomic and environmental impacts that vary between crops. However, information on how the spatial distribution of specific crops has changed over time across the globe is relatively sparse. We introduce the Probabilistic Cropland Allocation Model (PCAM), a novel algorithm to estimate where specific crops have likely been grown over time. Specifically, PCAM downscales annual and national-scale data on the crop-specific area harvested of 17 major crops to a global 0.5-degree grid from 1961-2014. \r\n\r\nThe resulting database presented here provides annual global gridded likelihood estimates of crop-specific areas. Both mean and standard deviations of grid cell fractions are available for each of the 17 crops. Each netCDF file contains an individual year of data with an additional variable (\"crs\") that defines the coordinate reference system used. Our results provide new insights into the likely changes in the spatial distribution of major crops over the past half-century. For additional information, please see the related paper by Jackson et al. (2019) in Environmental Research Letters (https://doi.org/10.1088/1748-9326/ab3b93)."]} 2019-08-28T14:34:18Z
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Dataset update: {"publication_state"=>["released", "file embargo"]} 2019-08-27T13:38:27Z