Land Cover - ESRI 2020

Parameter 

Land Cover 

10 classes


 

 


Represented classes

Water 

Trees 

Grass 

Flooded Vegetation 

Crops

Scrub/Shrub

Built Area 

Bare Ground

Snow/Ice

Clouds

No data 

Description 

Global map of land use/land cover (LULC). The map is derived from ESA Sentinel-2 imagery at 10m 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). 

Impact Observatory for ESRI  

Source data

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 

Land Cover Map 

Description 

Global map of land use/land cover (LULC) for 2020. The map is derived from ESA Sentinel-2 imagery at 10m resolution. It is a composite of LULC predictions for 10 classes throughout the year in order to generate a representative snapshot of 2020. 

Spatial resolution 

Global coverage

10 m spatial resolution

Temporal resolution

Period of observation: 

2020