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    • Reconstruction of high spatiotemporal resolution snow cover remote sensing range data from multiple sources based on deep learning model： A case study in the Qilian Mountains

    • “The latest research utilizes U-Net++network to develop a 30 meter resolution daily snow cover reconstruction algorithm, which effectively monitors changes in snow cover in mountainous areas and is of great significance for water resource management, hydrological processes, and ecological protection.”
    • Vol. 29, Issue 4, Pages: 867-882(2025)   

      Received：26 December 2023，

      Published：07 April 2025

    • DOI： 10.11834/jrs.20253541     

    移动端阅览

  • Gao B，Hao X H，He D C，Zhao Q，Ji W Z，Ren H R，Li H Y，Liu Y and Zhu P. 2025. Reconstruction of high spatiotemporal resolution snow cover remote sensing range data from multiple sources based on deep learning model： A case study in the Qilian Mountains. National Remote Sensing Bulletin， 29（4）：867-882 DOI： 10.11834/jrs.20253541.
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Shunshi HU 湖南师范大学 资源与环境科学学院;湖南师范大学 地理空间大数据挖掘与应用湖南省重点实验室
Chenlu ZHANG 湖南师范大学 资源与环境科学学院
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Tao ZHONG 中国科学院遥感与数字地球研究所 遥感科学国家重点实验室;中国科学院大学 资源与环境学院
TANG Yijie 同济大学 测绘与地理信息学院
WANG Qunming 同济大学 测绘与地理信息学院
ZHANG Kai 北京师范大学遥感科学国家重点实验室遥感与地理信息系统研究中心地理学与遥感学院

相关机构

College of Resources and Environmental Sciences, Hunan Normal University
Key Laboratory of Geospatial Big Data Mining and Application
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Science
College of Resources and Environment, University of Chinese Academy of Sciences
College of Surveying and Geo-Informatics, Tongji University
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