uw-cryo/DeepDEM
DeepDEM: Digital Elevation Model refinement using deep learning
This project helps refine digital elevation models (DEMs) created from satellite imagery. It takes raw stereo satellite images and an initial DEM as input, then uses deep learning to produce a more accurate, corrected DEM. This is for geoscientists, cartographers, or environmental researchers who need precise topographic data for their work.
Use this if you need to improve the accuracy of digital elevation models derived from satellite photos, especially when aiming for precision comparable to lidar data.
Not ideal if you don't have access to stereo satellite imagery, initial DEMs, or ground truth lidar data for training and validation.
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28
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4
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Nov 11, 2025
Commits (30d)
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