Articles | Volume 17, issue 12
https://doi.org/10.5194/essd-17-6703-2025
https://doi.org/10.5194/essd-17-6703-2025
Data description paper
 | 
03 Dec 2025
Data description paper |  | 03 Dec 2025

CropLayer: a 2 m resolution cropland map of China for 2020 from Mapbox and Google satellite imagery

Hao Jiang, Mengjun Ku, Xia Zhou, Qiong Zheng, Yangxiaoyue Liu, Jianhui Xu, Dan Li, Chongyang Wang, Jiayi Wei, Jing Zhang, Shuisen Chen, and Jianxi Huang

Viewed

Total article views: 3,919 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,919 920 80 3,919 66 112
  • HTML: 2,919
  • PDF: 920
  • XML: 80
  • Total: 3,919
  • BibTeX: 66
  • EndNote: 112
Views and downloads (calculated since 12 Mar 2025)
Cumulative views and downloads (calculated since 12 Mar 2025)

Viewed (geographical distribution)

Total article views: 3,919 (including HTML, PDF, and XML) Thereof 3,897 with geography defined and 22 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 15 Jan 2026
Download
Short summary
Existing cropland datasets in China show significant discrepancies. We created a high-resolution cropland map of China for 2020, using imagery from Mapbox and Google. By combining image quality assessments, active learning for semantic segmentation, and results integration. The accuracy achieved to 88.73 %, with 30 out of 32 provincial units reporting area estimates within ±10 % of official statistics. In contrast, only 9 to 1 provinces from 7 existing datasets meet the same accuracy standard.
Share
Altmetrics
Final-revised paper
Preprint