xinluo2018/WatNet
A deep learning model for surface water mapping based on satellite optical image.
This project helps environmental scientists, geographers, and urban planners automatically identify and map surface water bodies from satellite images. You provide Sentinel-2 optical images, and it outputs a precise map highlighting where water is present. This is ideal for monitoring changes in water bodies, assessing flood risk, or managing water resources.
117 stars. No commits in the last 6 months.
Use this if you need an accurate, automated way to delineate surface water from Sentinel-2 satellite imagery for environmental monitoring or mapping.
Not ideal if you are working with satellite images from other sources or require real-time water detection without processing existing images.
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117
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37
Language
Jupyter Notebook
License
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Last pushed
Aug 17, 2021
Commits (30d)
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