Land Cover
10 classes
Water
Trees
Grass
Flooded Vegetation
Crops
Scrub/Shrub
Built Area
Bare Ground
Snow/Ice
Clouds
No data
Global map of land use/land cover (LULC). The map is derived from ESA Sentinel-2 imagery at 10 m resolution. It is a composite of LULC predictions for 10 classes throughout the year in order to generate a representative snapshot of 2020. This map was produced by a deep learning model trained using over 5 billion hand-labeled Sentinel-2 pixels, sampled from over 20,000 sites distributed across all major biomes of the world. The underlying deep learning model uses 6 bands of Sentinel-2 surface reflectance data: visible blue, green, red, near infrared, and two shortwave infrared bands. To create the final map, the model is run on multiple dates of imagery throughout the year, and the outputs are composited into a final representative map of 2020. Processing platform Sentinel-2 L2A/B data was accessed via Microsoft’s Planetary Computer and scaled using Microsoft Azure Batch. You can find more information here Kontgis, C. (2021, June 24).
ESRI
2021 Esri Karra, Kontgis, et al. “Global land use/land cover with Sentinel-2 and deep learning.” IGARSS 2021-2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2021
Global map of land use/land cover (LULC) for 2020. The map is derived from ESA Sentinel-2 imagery at 10 m resolution. It is a composite of LULC predictions for 10 classes throughout the year in order to generate a representative snapshot of 2020.
Global coverage
10 m spatial resolution
Period of observation:
2020