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Full catalog/clms_ndvi-lts_global_1km_10daily_v3
clms_ndvi-lts_global_1km_10daily_v3·dataset

Normal vegetation greenness benchmark, 2015-2025 (Copernicus)

CLMS NDVI LTS Global 1km 10-daily V3
biosphere ESA ESA Copernicus COGNetCDF
In plain English

What it measures. Provides long-run statistics, the minimum, mean, median, and maximum greenness, for each ten-day period of the year, based on observations from 2015 to 2025.

How it's made. Generated by ESA Copernicus from SPOT-VEGETATION and PROBA-V data at roughly 1-kilometer resolution.

How & where you'd use it. Acts as an updated 'what's typical' baseline so analysts can flag when vegetation is unusually green or stressed, aiding drought and agriculture watch.

What's measured

CopernicusCLMSNDVI-LTSNDVI Long-Term Statisticsvegetation monitoringglobal10-daily1kmSPOTVEGETATIONPROBA-V

Coverage & cadence

  • Time span1999-01-01 → 2019-12-31
  • Spatial extent-179.9999999, -59.9955357, 179.9955357, 80.0044643
  • 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

Provides long-term statistics (minimum, mean, median, maximum) of the 10-daily NDVI at global scale in the spatial resolution of about 1 km over the period from 2015 to 2025.

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_ndvi-lts_global_1km_10daily_v3"],   # 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.