Global Ensemble Digital Terrain Model
The Global Ensemble Digital Terrain Model (GEDTM30) is a globally consistent, 30m resolution DTM created using a machine learning-based data fusion approach. It combines multiple global elevation datasets including Copernicus DEM, ALOS World 3D, and object height models, and refines them using nearly 30 billion high-quality ground elevation points from ICESat-2 and GEDI. A two-stage random forest model ensures both global coherence and local accuracy, producing a bare-earth terrain model that minimizes the effects of vegetation, buildings, and DEM artifacts. For more details on this project see the following resources: GEDTM30 Zenodo Repository GEDTM30 Codeberg Repository GEDTM30 Publication Disclaimer: This data product was generated using machine learning methods. Users are advised to exercise caution and independently verify results before using this product for critical applications, engineering design, or decision-making purposes.
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Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[ "000:00" ] |
| contactPoint |
{ "fn": "OpenTopography Support", "@type": "vcard:Contact", "hasEmail": "mailto:info@opentopography.org" } |
| description | The Global Ensemble Digital Terrain Model (GEDTM30) is a globally consistent, 30m resolution DTM created using a machine learning-based data fusion approach. It combines multiple global elevation datasets including Copernicus DEM, ALOS World 3D, and object height models, and refines them using nearly 30 billion high-quality ground elevation points from ICESat-2 and GEDI. A two-stage random forest model ensures both global coherence and local accuracy, producing a bare-earth terrain model that minimizes the effects of vegetation, buildings, and DEM artifacts. For more details on this project see the following resources: GEDTM30 Zenodo Repository GEDTM30 Codeberg Repository GEDTM30 Publication Disclaimer: This data product was generated using machine learning methods. Users are advised to exercise caution and independently verify results before using this product for critical applications, engineering design, or decision-making purposes. |
| distribution |
[ { "@type": "dcat:Distribution", "title": "OpenTopography Data Download Page", "accessURL": "https://doi.org/10.5069/G9BV7DT1", "mediaType": "text/html" } ] |
| identifier | OT.082025.4326.1 |
| keyword |
[ "ALOS", "Copernicus", "DSM", "DTM", "GEDI", "ICESat-2", "Satellite", "lidar", "machine learning" ] |
| license | https://creativecommons.org/licenses/by/4.0 |
| modified | 2025-08-04 |
| programCode |
[ "000:000" ] |
| publisher |
{ "name": "OpenTopography", "@type": "org:Organization" } |
| spatial | -180.0,-62.01,180.0,83.69 |
| title | Global Ensemble Digital Terrain Model |
