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

作者：Bingwen Qiu, Zhengrong Li, Peng Yang, Wenbin Wu, Xuehong Chen, Bingfang Wu, Miao Zhang, Ye Duan, Syahrul Kurniawan, Piotr Tryjanowski, Viktória Takács · 发表于：Agricultural Systems · 年份：2025 · DOI：10.1016/j.agsy.2025.104338 · 被引用次数：8 · 研究领域：Remote Sensing in Agriculture、Remote Sensing and Land Use、Remote Sensing and LiDAR Applications

Context 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. Objective This paper has three objectives: 1) propose approaches for automatic mapping of wheat cropping patterns; 2) assess its capability through its applications over conterminous China; 3) explore the distribution patterns for wheat of crop rotation systems in China. Methods This study introduced a novel framework for automatic agricultural mapping by proposing CP indices based on coupled patterns of multi-source imagery and inter-seasonal variations. This study developed the first 10-m wheat Cropping Patterns (ChinaCP-Wheat10m) distribution map over conterminous China by proposing a robust algorithm for mapping Wheat cropping Patterns by fusing Sentinel-1 SAR and Sentinel-2 MSI data (WPSS). Results and conclusion The ChinaCP-Wheat10m map showed that wheat dominated the north of the Yangtze River and e...