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Global Gridded Crop Production Dataset at 10 km Resolution from 2010 to 2020.

Xingli Qin1, Bingfang Wu2,3, Hongwei Zeng1

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A new global gridded crop production dataset (GGCP10) offers 10km resolution for key crops from 2010-2020. This high-resolution data enhances understanding of global food security and agricultural development.

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Area of Science:

  • Agricultural Science
  • Geospatial Data Science
  • Environmental Science

Background:

  • Existing global crop production datasets suffer from coarse resolution and discontinuous time spans.
  • Accurate, high-resolution data is crucial for understanding global food security and agricultural sustainability.

Purpose of the Study:

  • To develop a high-resolution (10km) global gridded crop production dataset (GGCP10) for maize, wheat, rice, and soybean covering 2010-2020.
  • To address limitations of existing datasets regarding spatial and temporal resolution.
  • To provide reliable data for research on global food security and sustainable agriculture.

Main Methods:

  • Developed adaptively trained, data-driven spatial estimation models for crop production.
  • Integrated multiple data sources: statistical, gridded production, agroclimatic, agronomic, satellite, and ground data.
  • Trained models on agroecological zones and calibrated estimates with regional statistics.

Main Results:

  • Generated the Global Gridded Crop Production dataset at 10km resolution (GGCP10) for 2010-2020.
  • Validated model performance through cross-validation and evaluated dataset accuracy using diverse data sources.
  • Revealed spatiotemporal distribution patterns of global crop production for key commodities.

Conclusions:

  • GGCP10 provides unprecedented detail on global crop production, improving upon existing datasets.
  • The dataset is crucial for understanding the drivers of crop production changes.
  • GGCP10 supports research critical for global food security and sustainable agricultural development.