GlobalWR-2025: The first global 10-meter winter rapeseed dataset developed by knowledge-guided temporal features
• Knowledge-guided optical-SAR temporal features enable transferable winter rapeseed mapping. • GlobalWR-2025 provides the first global 10 m winter rapeseed map for 2025 • The WROS algorithm achieves an overall accuracy of 92.21%. • Time-series maps capture the 2023 peak and subsequent conflict-related contraction in Ukraine.
Authors
- Piotr Tryjanowski (ORCID: https://orcid.org/0000-0002-8358-0797)
- Yufeng Peng (ORCID: https://orcid.org/0000-0003-0942-3141)
- Viktória Takács (ORCID: https://orcid.org/0000-0001-6340-0253)
- Bingwen Qiu (ORCID: https://orcid.org/0000-0001-7666-9163)
- Feifei Cheng (ORCID: https://orcid.org/0009-0006-1502-4701)
- Chunting Li
- Wenbin Wu
- Bingfang Wu (ORCID: https://orcid.org/0000-0001-5546-365X)
- Si Wang
- Xiuchun Dong
- Peng Yang
- Xuehong Chen
Institutions
- Chinese Academy of Sciences (CN)
- Beijing Normal University (CN)
- Aerospace Information Research Institute (CN)
- Ministry of Agriculture and Rural Affairs (CN)
- Sichuan Academy of Agricultural Sciences (CN)
- University of Life Sciences in Poznań (PL)
- Fuzhou University (CN)
Publication Details
- Journal
- International Journal of Applied Earth Observation and Geoinformation
- Published
- 2026-05-29
- DOI
- https://doi.org/10.1016/j.jag.2026.105365
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Fujian Provincial Department of Science and Technology