GDHY (0.1 degree grid)
DATASET OVERVIEW
Transfer data from GDHY to 0.1degree grid.The GDHY offers spatially explicit global analyses on crop yields and is especially useful for addressing recent patterns in crop yields and the impacts of recent climate variability and change on global food production; additionally, the GDHY can be used to evaluate global gridded crop model simulations and provide a basis for global and seasonal crop forecasting systems.
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GDHY Author: Toshichika Iizumi
GDHY Publish Year: 2019
Country yield statistics:FAOSTAT
Spatial resolution:0.5°
Time coverage:1981–2016
Satellite products:Hybrid of dataset versions 1.2 and 1.3
Harvested area:M3-Crops (0.083° and average around 2000)
Crop calendar:SAGE [0.5°and average around 2000]
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Factor Type(s):year of crop yield data collection
Period:1981–2016
Grid:0.1°
Format:.csv
Crops:Maize (major/second), soybean, rice (major/second), wheat (winter/spring)
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COLUMN DESCRIPTIONS
year:yield (tonnes per hectare,1981–2016)
lat:latitude
lon:longitude
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Country | wheat | wheat spring | rice | maize | soybean |
Argentina | √ | √ | √ | ||
Australia | √ | √ | |||
Bangladesh | √ | ||||
Bolivia | √ | ||||
Brazil | √ | √ | √ | √ | |
Canada | √ | √ | √ | ||
China | √ | √ | √ | √ | √ |
Egypt | √ | ||||
Ethiopia | √ | √ | √ | ||
European | √ | √ | √ | √ | |
India | √ | √ | √ | √ | |
Indonesia | √ | √ | |||
Iran | √ | √ | |||
kazakhstan | √ | ||||
Malaysia | √ | ||||
Mexico | √ | ||||
Myanmar | √ | ||||
Nigeria | √ | √ | √ | ||
Pakistan | √ | √ | |||
Paraguay | √ | ||||
Philippine | √ | ||||
Russia | √ | √ | √ | ||
SouthAfrica | √ | √ | |||
Thailand | √ | ||||
Turkey | √ | ||||
Ukraine | √ | √ | √ | ||
USA | √ | √ | √ | √ | |
Uzbekistan | √ | ||||
Viet Nam | √ |
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DATA SOURCE DECLARATION
The following data sources were used to create this dataset. If there is any inconsistency with the SOURCE DATA POLICY, please contact us for modification.
The global dataset of historical yields for major crops 1981–2016 (GDHY)