文献类型： 外文期刊

作者： Qiu, Bingwen ¹ ; Wu, Fangzheng ¹ ; Hu, Xiang ¹ ; Yang, Peng ² ; Wu, Wenbin ² ; Chen, Jin ³ ; Chen, Xuehong ³ ; He, Liyin ⁴ ; Joe, Berry ⁵ ; Tubiello, Francesco N. ⁶ ; Qian, Jianping ² ; Wang, Laigang ⁷ ;

作者机构： 1.Fuzhou Univ, Acad Digital China Fujian, Minist Educ, Key Lab Spatial Data Min & Informat Sharing, Fuzhou 350116, Peoples R China

2.Minist Agr & Rural Affairs, Key Lab Agr Remote Sensing, Beijing, Peoples R China

3.Beijing Normal Univ, Fac Geog Sci, Beijing, Peoples R China

4.Duke Univ, Nicholas Sch Environm, Durham, NC 27708 USA

5.Carnegie Inst Sci, Dept Global Ecol, Stanford, CA 94305 USA

6.Food & Agr Org United Nations, Stat Div, Rome, Italy

7.Henan Acad Agr Sci, Inst Agr Informat Technol, Zhengzhou, Peoples R China

关键词： Cropping patterns mapping; Model generalization; Dual-driven models; Crop diversity; Sentinel-1/2

期刊名称：ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING （ 影响因子：12.2； 五年影响因子：13.7 ）

ISSN： 0924-2716

年卷期： 2025 年 224 卷

页码：

收录情况： SCI

摘要： Complex cropping patterns with crop diversity are an underexploited treasure for global food security. However, significant methodological and dataset gaps in fully characterizing cropland cultivated with multiple crops and rotation sequences hinder our ability to understand and promote sustainable agricultural systems. Existing crop mapping models are challenged by the deficiency of ground reference data and the limited transferability capabilities across large spatial domains. This study aimed to fill these gaps by proposing a robust Complex Cropping Pattern Mapping framework (CCPM) capable of national-scale automatic applications using the Sentinel-1 SAR and Sentinel-2 MSI time series datasets. The CCPM framework addresses these challenges by integrating knowledge-based approaches & data-driven algorithms (Dual-driven model) and Phenological Normalization. The CCPM framework was implemented over conterminous China with complex cropping systems dominated by smallholder farms, and the first national-scale 10-m Cropping pattern map with descriptions of cropping intensity and 10 crops in China (ChinaCP-T10) in 2020 was produced. The efficiency of the CCPM framework was validated when evaluated by 18,706 ground-truth reference datasets, with an overall accuracy of 91.47 %. Comparisons with existing crop data products revealed that the ChinaCP-T10 offered more comprehensive and consistent information on diverse cropping patterns. Dominant cropping patterns diversified from single maize in northern China, winter wheat-maize in North China Plain, single oilseeds in Western China, to single rice or double rice in Southern China. The key cropping patterns changed from double-grain cropping, single grain to single cash cropping with increasing altitudes. There were 151,744 km2 planted areas of double grain cropping patterns in China, and multiple cropping accounted for 36.1 % of grain cultivated area nationally. Over 80 % of grain production was mainly implemented at lower altitudes as the Non-Grain Production (NGP) ratio enhanced from 32 % within elevations below 200 m to over 70 % among elevations above 700 m. Consistent datasets on complex cropping patterns are essential, given the significant roles of diversification and crop rotations in sustainable agriculture and the frequently observed inconsistencies in existing crop data products based on thematic mapping.