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2025
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| Online Access: | https://doi.org/10.5281/zenodo.14768587 |
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| _version_ | 1866901454563835904 |
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| author | Messmer, Jerome |
| author_facet | Messmer, Jerome |
| contents | <p><span>Inventory</span></p> <p><span>landslides_southernAK.gpkg</span></p> <p>Landslide inventory derived through manual mapping</p> <p>includes attributes:</p> <p>landslide_ID: ID</p> <p>movement_confidence: confidence in active movement</p> <p>delineation_confidence: confidence of delineation</p> <p>ident_aerial: identifiability in multispectral satellite imagery</p> <p>ident_DEM: identifiability in DEM</p> <p>ident_GSSICB: identifiability in radar coherence</p> <p>ident_ts: identifiability in multispectral satellite imagery time series</p> <p> </p> <p><span>Model</span></p> <p><span>mrcnn_landslide_detection_notebook.ipynb</span></p> <p>Jupyter notebook for model training and inference</p> <p><span>model_weights.h5</span></p> <p>Best performing weights from model training, can be used together with mrcnn_landslide notebook</p> <p><span>dataset_landslide_detection.zip</span></p> <p>Contains normalized tiles and masks for training</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_14768587 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Towards detection and understanding of paraglacial landslides in Southern Alaska using surface velocity data and deep learning. Supplementary files Messmer, Jerome <p><span>Inventory</span></p> <p><span>landslides_southernAK.gpkg</span></p> <p>Landslide inventory derived through manual mapping</p> <p>includes attributes:</p> <p>landslide_ID: ID</p> <p>movement_confidence: confidence in active movement</p> <p>delineation_confidence: confidence of delineation</p> <p>ident_aerial: identifiability in multispectral satellite imagery</p> <p>ident_DEM: identifiability in DEM</p> <p>ident_GSSICB: identifiability in radar coherence</p> <p>ident_ts: identifiability in multispectral satellite imagery time series</p> <p> </p> <p><span>Model</span></p> <p><span>mrcnn_landslide_detection_notebook.ipynb</span></p> <p>Jupyter notebook for model training and inference</p> <p><span>model_weights.h5</span></p> <p>Best performing weights from model training, can be used together with mrcnn_landslide notebook</p> <p><span>dataset_landslide_detection.zip</span></p> <p>Contains normalized tiles and masks for training</p> |
| title | Towards detection and understanding of paraglacial landslides in Southern Alaska using surface velocity data and deep learning. Supplementary files |
| url | https://doi.org/10.5281/zenodo.14768587 |