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Full catalog/clms_lcm_global_10m_yearly_v1
clms_lcm_global_10m_yearly_v1·dataset

High-detail yearly global land cover map, 10m (Copernicus)

CLMS LCM Global 10m yearly V1
land ESA ESA Copernicus active COG
In plain English

What it measures. Classifies the Earth's surface into cover types such as tree cover, grassland, cropland, permanent water and wetlands, at a fine 10-metre detail that resolves small features.

How it's made. Produced by ESA Copernicus from the Sentinel-2 satellites' MSI camera, updated once a year starting with a 2020 base map.

How & where you'd use it. Supports detailed monitoring of deforestation, urban growth and other land changes, plus planning and conservation. Available yearly for 2020 to 2026.

What's measured

CopernicusCLMSLCMLand Coverland use land coverglobalyearly10mSentinel-2MSI

Coverage & cadence

  • Time span2020-01-01 → ongoing
  • Spatial extent-179.9999999, -60, 179.9999999, 84
  • FormatsCOG

What you can do with it

  • Track deforestation, fire scars and land-cover change
  • Monitor crop and vegetation health (NDVI/EVI)
  • Map how built-up vs. green an area is over time
Official description

Provides at global level information on different types (classes) of physical coverage of the Earth's surface, e.g. tree cover, grasslands, croplands, permanent water bodies, wetlands at 10 m spatial resolution for the 2020 base year. The data are updated annually and will be available for the 2020-2026 years. This dataset builds upon initiatives like the 100 m Copernicus Global Land Cover layers (2015-2019) and offers enhanced spatial detail that facilitates more effective monitoring of global land cover changes, including deforestation, urbanization, and other environmental transformations.

Get the data

copernicus_access.py
# ESA Copernicus Data Space — open STAC API (free account)
from pystac_client import Client

cat = Client.open("https://stac.dataspace.copernicus.eu/v1")
search = cat.search(
    collections=["clms_lcm_global_10m_yearly_v1"],   # add _cog or _nc for a format variant
    bbox=(-10, 35, 30, 60),             # your area (W,S,E,N)
    datetime="2024-01-01/2024-12-31",
)
items = list(search.items())            # then read assets with rioxarray / xarray
Browsing the Copernicus STAC is open; downloading bytes needs a free Copernicus Data Space account.