D5_vegetation.zip
Data related to Space4iCity WP5: Characterization of Vegetation
Instead of simply computing NDVI, a UNet model was trained to identify different land cover classes at 10m resolution based on Sentinel-2 bands 2, 3, 4 and 8. This has the advantage of being able to distinguish taller vegetation (trees) from lower vegetation (grass).
Target classes are based on the ESA WorldCover scheme: https://esa-worldcover.org/en
Details on the training procedure and evaluation results are found in the attached report.
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Zusätzliche Informationen
| Feld | Wert |
|---|---|
| Daten wurden zuletzt aktualisiert | 27. Januar 2026 |
| Metadaten zuletzt aktualisiert | 27. Januar 2026 |
| Erstellt | 27. Januar 2026 |
| Format | .zip |
| Lizenz | Creative Commons Attribution |
| Id | e833696e-99f9-41a6-895f-281cbbec0490 |
| Mimetype | application/zip |
| On same domain | True |
| Package id | f1ee3b35-235d-4429-be67-79cb83d6d8f1 |
| Position | 1 |
| Size | 31,8 MiB |
| State | active |
| Url type | upload |