Full catalog/clms_vlcc_tree-cover-presence-change-confidence-layer_europe_20m_3yearly_v1
clms_vlcc_tree-cover-presence-change-confidence-layer_europe_20m_3yearly_v1·dataset

Reliability of European tree-cover change maps (Copernicus)

CLMS VLCC Tree Cover Presence Change Confidence Layer (TCPCCL) Europe 20m 3-yearly V1
biosphere ESA ESA Copernicus active
In plain English

What it measures. A quality-support layer that accompanies the maps of where tree cover has appeared or disappeared. It indicates how confident the change detection is at each location.

How it's made. Produced on a three-year cycle by the EU's Copernicus Land Monitoring Service as 20-metre grid tiles covering 38 European countries plus French overseas departments.

How & where you'd use it. Helps users judge how much weight to put on a reported gain or loss of trees before drawing conclusions. It is a companion layer rather than the change map itself.

What's measured

CLMSCopernicusEuropeRasterLand coverLand useTree cover densityForestTree coverTCD

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 Tree Cover Presence Change Confidence Layer (TCPCCL) dataset provides a quality support raster product. 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, with a 3-yearly update cycle. High Resolution Layer Tree Cover and Forest 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_tree-cover-presence-change-confidence-layer_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.