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Full catalog/clms_ndvi-lts_global_1km_10daily_v2
clms_ndvi-lts_global_1km_10daily_v2·dataset

Normal vegetation greenness benchmark, 1999-2017 (Copernicus)

CLMS NDVI LTS Global 1km 10-daily V2
biosphere ESA ESA Copernicus COGNetCDF
In plain English

What it measures. Summarizes what 'normal' plant greenness looks like for each ten-day slot of the year, giving the lowest, average, middle, and highest values measured over the 1999-2017 period.

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

How & where you'd use it. Serves as a reference for judging whether current vegetation is healthier or more stressed than usual, useful for drought and crop-condition monitoring.

What's measured

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

Coverage & cadence

  • Time span1999-01-01 → 2017-12-31
  • 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 1999 to 2017.

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_v2"],   # 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.