Earth Data School
About
Full catalog/clms_vlcc_grassland-change_europe_20m_3yearly_v1
clms_vlcc_grassland-change_europe_20m_3yearly_v1·dataset

Where Europe gained or lost grassland (Copernicus)

CLMS VLCC Grassland Change (GRAC) Europe 20m 3-yearly V1
biosphere ESA ESA Copernicus active
In plain English

What it measures. Maps changes in grassland between two reference years, marking where grassland was newly gained, lost, stayed unchanged, or where the change could not be confirmed.

How it's made. Refreshed every three years from satellite imagery by the EU's Copernicus Land Monitoring Service as a 20-metre grid across Europe's 38 countries, including French overseas territories.

How & where you'd use it. Helps conservationists and planners track the spread or decline of meadows and pastures, important for biodiversity, carbon storage, and land-use policy.

What's measured

CLMSCopernicusEuropeRasterLand coverLand useGrasslandGRA

Coverage & cadence

  • Time span2018-01-01 → ongoing
  • Spatial extent-180, -90, 180, 90

What you can do with it

  • Map vegetation, forests and biomass
  • Monitor ecosystem productivity and carbon
  • Support habitat and biodiversity studies
Official description

The High Resolution Layer Grassland Change (GRAC) dataset provides information on changes in grassland vegetation cover between two reference years, with thematic classes indicating all non-grassland areas, grassland gain, grassland loss, unchanged grassland in both years, and unverified grassland gain and loss areas. This dataset is provided in 20 meter rasters (fully conformant with the EEA reference grid) in 100 x 100 km tiles covering the EEA38 countries. High Resolution Layer Grasslands product is part of the European Union's Copernicus Land Monitoring Service. This dataset includes data from the French Overseas Territories (DOMs).

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_vlcc_grassland-change_europe_20m_3yearly_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.