SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data (Central of China)

The SinoLC-1 was created by the Low-to-High Network (L2HNet), which can be found at: L2HNet. A more detailed description of the data can be found in the paper. 

Click to check all the data versions and download the data (点击查看/下载所有数据版本)

NOTE: If you have any data questions, contact us at ashelee@whu.edu.cn (Zhuohong Li, 李卓鸿). 

More related work can be found on my homepage. (访问我的主页查看近年所有相关工作)

• March 2024: The land-cover mapping method with Python code is open-access at Code link. You can now update the high-resolution land-cover map by yourself with the code! The updated method is accepted by CVPR 2024 (Paper link). 
• March 2026: We updated SinoLC-1 and released a building-level urban functional mapping product for China (SinoBF-1), which was accepted by Nature Communications (Paper link), and the dataset has been released (Data download).

2024年3月:我们的制图算法被计算机视觉顶会CVPR2024接收(Paper link),代码开源在:Code link,您可以利用该代码高效地更新自己数据集的高分土地覆盖图。

2026年3月:我们对SinoLC-1进行了更新,推出了"中国楼栋尺度的建筑功能制图产品(SinoBF-1)",包含109个城市建筑功能(住宅、学校、医院、行政、工厂、文体等), 该产品被Nature Communications接收 (Paper link), 数据已经开源 (Data download)

Citation format of the paper:

Li, Z., He, W., Cheng, M., Hu, J., Yang, G., and Zhang, H.: SinoLC-1: the first 1 m resolution national-scale land-cover map of China created with a deep learning framework and open-access data, Earth Syst. Sci. Data, 15, 4749–4780, 2023. 

Li, Z., Zhang, H., Lu, F., Xue, R., Yang, G. and Zhang, L.: Breaking the resolution barrier: A low-to-high network for large-scale high-resolution land-cover mapping using low-resolution labels, ISPRS Journal of Photogrammetry and Remote Sensing. 192, pp.244-267, 2022.