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Full catalog/clms_vlcc_dominant-leaf-type_europe_10m_yearly_v1
clms_vlcc_dominant-leaf-type_europe_10m_yearly_v1·dataset

Map of broadleaf versus conifer trees across Europe (Copernicus)

CLMS VLCC Dominant Leaf Type (DLT) Europe 10m yearly V1
biosphere ESA ESA Copernicus active
In plain English

What it measures. Sorts the land into three simple categories: areas with no trees, areas dominated by broadleaved trees (like oak or beech), and areas dominated by conifers (like pine or spruce).

How it's made. Generated yearly from 2018 onward by the EU's Copernicus Land Monitoring Service as a 10-metre grid covering Europe's 38-country reference area, including French overseas territories.

How & where you'd use it. Useful for forest inventories, biodiversity studies, and climate work that needs to know which kind of forest grows where. A companion reliability layer is available.

What's measured

CLMSCopernicusEuropeRasterLand coverLand useDominant Leaf TypeDLTForestTree cover

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 Dominant Leaf Type (DLT) raster product provides a basic land cover classification with 3 thematic classes (all non-tree covered areas, broadleaved and coniferous). This dataset is provided annually starting with 2018 in 10 meter rasters (fully conformant with the EEA reference grid) in 100 x 100 km tiles covering the EEA38 countries. High Resolution Layer Tree Cover and Forest product is part of the European Union’s Copernicus Land Monitoring Service. Confidence layer available for the dataset. 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_dominant-leaf-type_europe_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.