%0 Dataset
%T SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/643d320b-315a-4984-868b-be6aae30da55
%W NCDC
%R 10.5281/zenodo.8214871
%A LI Zhuohong
%A Zhang Hongyan
%K 1m resolution;land cover;deep learning
%X This dataset is based on a deep learning framework and open access data (including Global Land Cover (GLC) products, Open Street Maps (OSM), and Google Earth Images) to establish China's first national scale land cover map SinoLC-1 with a resolution of 1 meter. Combine three 10 m GLC products with OSM data to generate reliable training labels. Use these training labels and 1m resolution images from Google Earth to train the proposed framework. This framework solves label noise caused by resolution mismatch between images and labels by combining resolution preserving backbone, weakly supervised module, and self supervised loss function, thereby automatically improving VHR land cover results without the need for manual annotation. Based on large-scale storage and computing servers, the 73.25 TB dataset was processed to obtain SinoLC-1 covering approximately 9.6 million square kilometers throughout China.