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Full catalog/clms_ba_global_300m_daily_v4
clms_ba_global_300m_daily_v4·dataset

Daily global map of fresh fire burn scars (Copernicus, 2025-now)

CLMS BA Global 300m daily V4
biosphere ESA ESA Copernicus active COGNetCDF
In plain English

What it measures. Shows the burned ground left by wildfires worldwide, identifying where vegetation has been destroyed and the surface darkened by ash. Refreshed daily at roughly 300-metre detail.

How it's made. Generated by ESA Copernicus using the OLCI and SLSTR instruments aboard the Sentinel-3 satellites, with results delivered within a day of acquisition.

How & where you'd use it. Supports near-real-time wildfire monitoring, damage assessment and fire research. This is the newer edition, running from January 2025 to the present.

What's measured

CopernicusCLMSBABurnt Areafire disturbanceglobaldaily300mSentinel-3OLCISLSTR

Coverage & cadence

  • Time span2024-12-01 → ongoing
  • Spatial extent-179.9999999, -59.9985119, 179.9985119, 80.0014881
  • FormatsCOG, NetCDF

What you can do with it

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

Maps burn scars, surfaces which have been sufficiently affected by fire to display significant changes in the vegetation cover (destruction of dry material, reduction or loss of green material) and in the ground surface (temporarily darker because of ash). Daily datasets are available at global scale, in the spatial resolution of 300 m, and within 24 hours after the satellite acquisition. They cover the period from January 2025 to present.

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_ba_global_300m_daily_v4"],   # 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.