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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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-
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- ## Citation
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-
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- If you use this work, please cite the original DeepDEM paper and datasets used.
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-
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- ## License
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-
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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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+
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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