SinoLC-1: the first 1&thinsp;m resolution national-scale land-cover map of China created with a deep  learning framework and open-access data

Li, Zhuohong; He, Wei; Cheng, Mofan; Hu, Jingxin; Yang, Guangyi; Zhang, Hongyan

doi:https://doi.org/10.5194/essd-15-4749-2023

Articles | Volume 15, issue 11

https://doi.org/10.5194/essd-15-4749-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-15-4749-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 11

Data description paper

|

30 Oct 2023

Data description paper |

| 30 Oct 2023

SinoLC-1: the first 1 m resolution national-scale land-cover map of China created with a deep learning framework and open-access data

Zhuohong Li, Wei He, Mofan Cheng, Jingxin Hu, Guangyi Yang, and Hongyan Zhang

Data sets

SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data Zhuohong Li, Wei He, Mofan Cheng, Jingxin Hu, Xiao An, Yan Huang, Guangyi Yang, and Hongyan Zhang https://doi.org/10.5281/zenodo.7707461

Short summary

Nowadays, a very-high-resolution land-cover (LC) map with national coverage is still unavailable in China, hindering efficient resource allocation. To fill this gap, the first 1 m resolution LC map of China, SinoLC-1, was built. The results showed that SinoLC-1 had an overall accuracy of 73.61 % and conformed to the official survey reports. Comparison with other datasets suggests that SinoLC-1 can be a better support for downstream applications and provide more accurate LC information to users.