SQD1/RESTORE-DiT
[RSE 2025] RESTORE-DiT: Reliable satellite image time series reconstruction by multimodal sequential diffusion transformer
This project helps environmental scientists and agricultural planners reconstruct missing data in satellite image time series, especially in areas with persistent cloud cover. It takes a sequence of radar (SAR) satellite images and date information to produce a complete, cloud-free optical satellite image time series. This is useful for monitoring highly dynamic land surfaces like vegetation health or crop growth.
No commits in the last 6 months.
Use this if you need to reliably fill in gaps in optical satellite image sequences caused by clouds, using radar data to help improve accuracy.
Not ideal if your primary goal is real-time processing or if you do not have access to corresponding SAR image time series data.
Stars
54
Forks
6
Language
Python
License
MIT
Category
Last pushed
Jul 07, 2025
Commits (30d)
0
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