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.
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.
the Creative Commons Attribution 4.0 License.
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
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, PR China
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, PR China
Mofan Cheng
School of Electronic Information, Wuhan University, Wuhan, 430079, PR China
Jingxin Hu
School of Electronic Information, Wuhan University, Wuhan, 430079, PR China
Guangyi Yang
School of Electronic Information, Wuhan University, Wuhan, 430079, PR China
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, PR China
School of Computer Science, China University of Geosciences, Wuhan, 430074, PR China
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Saved (final revised paper)
Latest update: 09 Jun 2026
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.
Nowadays, a very-high-resolution land-cover (LC) map with national coverage is still unavailable...
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