%0 Dataset
%T Daily 5-km Gap-free AVHRR snow cover extent product over Three-River Source（1980-2020）
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/e27fdedb-c078-413b-ae5e-3c8caf4308be
%W NCDC
%R 10.12072/ncdc.nieer-snow.db6814.1
%A Zhao Zisheng
%A Xiaohua Hao 
%A Li Hangxuan
%A Zhong Xinyue
%A Wu Xiaodong
%K SCE;long term;AVHRR
%X As a sensitive indicator of climate change, snow cover plays a vital role in climate research, and long-term snow cover data are an essential foundation for such studies. Although existing snow cover extent datasets offer good quality and relatively high spatial and temporal resolution, their temporal coverage is often limited. In this study, we developed a daily snow cover extent product with a spatial resolution of 5 km covering the Sanjiangyuan region from 1980 to 2020. The product was generated using AVHRR surface reflectance data and Landsat-5 TM imagery, in combination with ground-based snow depth observations, China’s long-term daily snow depth dataset, land surface temperature, and DEM data. By applying an improved cloud detection algorithm, a multi-level snow discrimination algorithm, and a gap-filling strategy, we produced a reliable snow cover product. Validation results show that, compared to existing AVHRR-based snow cover products (e.g., the JASMES AVHRR product), our product demonstrates a significant improvement in overall accuracy by approximately 15%, with the omission error reduced from 60.8% to 19.7%, the commission error reduced from 31.9% to 21.3%, and the Cohen’s kappa coefficient increased by more than 114%. This dataset provides valuable support for monitoring snow cover dynamics and conducting climate change research in the Sanjiangyuan region.