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Towards automation of national scale cropping pattern mapping by coupling Sentinel-1/2 data: A 10-m map of crop rotation systems for wheat in China

Author

Listed:
  • Qiu, Bingwen
  • Li, Zhengrong
  • Yang, Peng
  • Wu, Wenbin
  • Chen, Xuehong
  • Wu, Bingfang
  • Zhang, Miao
  • Duan, Yuanlin
  • Kurniawan, Syahrul
  • Tryjanowski, Piotr
  • Takacs, Viktoria

Abstract

Wheat, as the world's largest cereal crop, contributes significantly to agricultural intensification through crop rotation systems. Updated knowledge of cropping patterns (CP) describing crop rotations is crucial for the development of sustainable agricultural systems. However, there is a gap in data availability and finer resolution CP maps are not available for most countries, which hampers our knowledge of geographically targeted crop rotation for sustainable management. It is challenging to automatically map CP at large scales due to the lack of ground-truth datasets, the complexity of crop rotation systems, and the limited applicability of existing algorithms.

Suggested Citation

  • Qiu, Bingwen & Li, Zhengrong & Yang, Peng & Wu, Wenbin & Chen, Xuehong & Wu, Bingfang & Zhang, Miao & Duan, Yuanlin & Kurniawan, Syahrul & Tryjanowski, Piotr & Takacs, Viktoria, 2025. "Towards automation of national scale cropping pattern mapping by coupling Sentinel-1/2 data: A 10-m map of crop rotation systems for wheat in China," Agricultural Systems, Elsevier, vol. 227(C).
    • Handle: RePEc:eee:agisys:v:227:y:2025:i:c:s0308521x25000782
    DOI: 10.1016/j.agsy.2025.104338
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