An Improved Spatiotemporal Fusion Algorithm for Monitoring Daily Snow Cover Changes With High Spatial Resolution

Author:

Wang Yuhan1,Gu Lingjia1ORCID,Li Xiaofeng2,Gao Fang3ORCID,Jiang Tao2,Ren Ruizhi1

Affiliation:

1. College of Electronic Science and Engineering, Jilin University, Changchun, China

2. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China

3. Chang Guang Satellite Technology Company Ltd., Changchun, China

Funder

National Natural Science Foundation of China

Project of Jilin Province Development and Reform Commission

Technological Research and Development Projects of Jilin

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Using Partial Cloud-Free Images to Improve Spatiotemporal Fusion for Terrestrial Latent Heat Flux: The Multiphase Self-Adaptive (MSA) Model;IEEE Transactions on Geoscience and Remote Sensing;2024

2. Multiscale Attention Spatiotemporal Fusion Model Based on Pyramidal Network Constraints;IEEE Geoscience and Remote Sensing Letters;2024

3. An Effective Fractional Snow Cover Estimation Method Using Deep Feature Snow Index;IEEE Geoscience and Remote Sensing Letters;2024

4. FastVSDF: An Efficient Spatiotemporal Data Fusion Method for Seamless Data Cube;IEEE Transactions on Geoscience and Remote Sensing;2024

5. Remote Sensing Single Image Super-Resolution Benchmarking with Transfer Learning Algorithms;2023 7th International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech);2023-12-18

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