AI-generated Key Takeaways
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The ESA WorldCover 10 m 2020 product provides a global land cover map for 2020 at 10-meter resolution.
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This dataset is based on Sentinel-1 and Sentinel-2 data and includes 11 distinct land cover classes.
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It was created as part of the ESA WorldCover project, within the European Space Agency's EOEP-5 program.
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The dataset is freely available under the CC-BY-4.0 license and can be accessed through Google Earth Engine.
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Users can find more information, including a user manual and validation report, on the ESA WorldCover website.

- Dataset Availability
- 2020-01-01T00:00:00Z–2021-01-01T00:00:00Z
- Dataset Provider
- ESA WorldCover Consortium
- Tags
Description
The European Space Agency (ESA) WorldCover 10 m 2020 product provides a global land cover map for 2020 at 10 m resolution based on Sentinel-1 and Sentinel-2 data. The WorldCover product comes with 11 land cover classes and has been generated in the framework of the ESA WorldCover project, part of the 5th Earth Observation Envelope Programme (EOEP-5) of the European Space Agency.
See also:
Bands
Pixel Size
10 meters
Bands
Name | Pixel Size | Description |
---|---|---|
Map |
meters | Landcover class |
Map Class Table
Value | Color | Description |
---|---|---|
10 | #006400 | Tree cover |
20 | #ffbb22 | Shrubland |
30 | #ffff4c | Grassland |
40 | #f096ff | Cropland |
50 | #fa0000 | Built-up |
60 | #b4b4b4 | Bare / sparse vegetation |
70 | #f0f0f0 | Snow and ice |
80 | #0064c8 | Permanent water bodies |
90 | #0096a0 | Herbaceous wetland |
95 | #00cf75 | Mangroves |
100 | #fae6a0 | Moss and lichen |
Terms of Use
Terms of Use
Citations
Zanaga, D., Van De Kerchove, R., De Keersmaecker, W., Souverijns, N., Brockmann, C., Quast, R., Wevers, J., Grosu, A., Paccini, A., Vergnaud, S., Cartus, O., Santoro, M., Fritz, S., Georgieva, I., Lesiv, M., Carter, S., Herold, M., Li, Linlin, Tsendbazar, N.E., Ramoino, F., Arino, O., 2021. ESA WorldCover 10 m 2020 v100. (doi:10.5281/zenodo.5571936)
Explore with Earth Engine
Code Editor (JavaScript)
var dataset = ee.ImageCollection('ESA/WorldCover/v100').first(); var visualization = { bands: ['Map'], }; Map.centerObject(dataset); Map.addLayer(dataset, visualization, 'Landcover');
import ee import geemap.core as geemap
Colab (Python)
dataset = ee.ImageCollection('ESA/WorldCover/v100').first() visualization = { 'bands': ['Map'], } m = geemap.Map() m.center_object(dataset) m.add_layer(dataset, visualization, 'Landcover') m