yc-cui/Deep-Learning-Spatiotemporal-Fusion-Survey
[Information Fusion 2026] A collection of deep learning models for remote sensing spatiotemporal fusion.
This project offers a comprehensive collection of deep learning models specifically designed for fusing remote sensing satellite data across space and time. It takes in satellite images with different resolutions or temporal frequencies and produces enhanced, unified spatiotemporal data products. Remote sensing researchers and practitioners who need to analyze environmental changes with greater detail would find this invaluable.
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Use this if you are a remote sensing professional or researcher who needs to combine coarse-resolution, frequently updated satellite imagery with fine-resolution, less frequently updated imagery to get a complete, high-quality view of land surface conditions.
Not ideal if your work does not involve remote sensing imagery or if you are looking for a plug-and-play software tool without engaging with deep learning models and research papers.
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Language
Python
License
MIT
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Last pushed
Sep 10, 2025
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