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Full catalog/clms_clcplus_lulucf-instance_europe_100m_yearly_v1
clms_clcplus_lulucf-instance_europe_100m_yearly_v1·dataset

Yearly Europe land-use map for climate reporting (Copernicus)

CLMS CLCplus LULUCF Instance Europe 100m yearly V1
land ESA ESA Copernicus
In plain English

What it measures. A consistent yearly map of how land across Europe is used, sorting every 100-metre cell into one of six broad categories (forest, grassland, cropland, settlements, wetlands and other land) plus 27 finer sub-classes.

How it's made. Compiled by ESA Copernicus by combining several pan-European Copernicus Land Monitoring Service datasets into a single 100-metre layer, available for 2018, 2021, 2022 and 2023 and moving to annual updates.

How & where you'd use it. Designed to help European countries report greenhouse-gas emissions and removals from land use under EU climate (LULUCF) rules, and to support broader land-use and environmental analysis.

What's measured

CLMSCopernicusEuropeRasterLand coverLand useCLCplusLULUCFInstance

Coverage & cadence

  • Time span2018-01-01 → 2023-12-31
  • Spatial extent-180, -90, 180, 90

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

This dataset refers to the CORINE Land Cover Plus Land Use, Land-Use Change and Forestry Instance (CLCplus LULUCF Instance), an annually updated, pan-European, spatially consistent and seamless geospatial proxy for land use reporting under the LULUCF regulation. The product is delivered as a single raster layer with a spatial resolution of 100 m, derived from multiple pan-European Copernicus Land Monitoring Service (CLMS) high resolution input datasets. The LULUCF Instance is available for the reference years 2018, 2021, 2022 and 2023, with production moving to an annual update cycle starting from the 2021 product. Each raster cell represents a dominant LULUCF land-use class, assigned according to thematic and spatial rulesets implemented during the extraction process. While each pixel corresponds primarily to one of the six main LULUCF land use categories - forest land, grassland, cropland, settlements, wetlands, and other lands - the dataset further differentiates these categories into sub classes, resulting in a total of 27 classes. This classification structure supports greenhouse gas reporting and other applications within the LULUCF sector by providing a harmonised and policy relevant representation of land use across Europe. This product is fundamentally different from other CLMS products, as it is not based directly on satellite image classification or visual interpretation. Instead, it is produced through the combination and integration of existing CLMS data layers. Consequently, the dataset does not introduce fundamentally new information; rather, its novelty lies

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_clcplus_lulucf-instance_europe_100m_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.