A long-term daily gridded snow depth dataset for the Northern Hemisphere from 1980 to 2019 based on machine learning

Author:

Hu Yanxing12,Che Tao13,Dai Liyun1,Zhu Yu4,Xiao Lin5,Deng Jie1,Li Xin3

Affiliation:

1. Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China

2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China

3. State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China

4. Yunnan Key Laboratory of International Rivers and Transboundary Eco-Security, Institute of International Rivers and Eco-Security, Yunnan University, Kunming, China

5. National Forestry and Grassland Administration Key Laboratory of Forest Resource Conservation and Ecological Safety on the Upper Reaches of the Yangtze River, Sichuan Province Key Laboratory of Ecological Forestry Engineering on the Upper Reaches of the Yangtze River, College of Forestry, Sichuan Agricultural University, Chengdu, China

Funder

the National Science Fund for Distinguished Young Scholars

the National Nature Science Foundation of China

the CAS ‘Light of West China’ Program

Publisher

Informa UK Limited

Subject

Computers in Earth Sciences,Computer Science Applications

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