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# DEM Super-Resolution
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This repository contains a pipeline for generating synthetic high-resolution Digital Elevation Models (DEMs) by super-resolving 30m SRTM data to 10m resolution, fused with Sentinel-2 imagery. The model is trained on high-resolution LiDAR DEM data from McKinley Mine, NM, and applied to generate DEMs for Marrakech, Morocco.
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The notebook includes checks for:
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- Input data statistics and validity
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- Training fit (MAE/RMSE on validation crops)
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- Output alignment and correlation with SRTM trend
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## Citation
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If you use this work, please cite the original DeepDEM paper and datasets used.
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## License
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[Add your license here]</content>
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<parameter name="filePath">/home/besudo/Git/deepdem/DEM_SuperRes/README.md
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---
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license: mit
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tags:
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- pytorch
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- pytorch-lightning
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- dem
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- super-resolution
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- remote-sensing
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- geospatial
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---
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# DEM Super-Resolution
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This repository contains a pipeline for generating synthetic high-resolution Digital Elevation Models (DEMs) by super-resolving 30m SRTM data to 10m resolution, fused with Sentinel-2 imagery. The model is trained on high-resolution LiDAR DEM data from McKinley Mine, NM, and applied to generate DEMs for Marrakech, Morocco.
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The notebook includes checks for:
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- Input data statistics and validity
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- Training fit (MAE/RMSE on validation crops)
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- Output alignment and correlation with SRTM trend
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