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Full catalog/clms_dmp_global_300m_10daily_v1
clms_dmp_global_300m_10daily_v1·dataset

Global plant growth rate, sharper 300m view (Copernicus)

CLMS DMP Global 300m 10-daily V1
biosphere ESA ESA Copernicus COGNetCDF
In plain English

What it measures. Measures how quickly vegetation is adding dry biomass, expressed in kilograms per hectare per day for farming use. A higher value means plants are growing faster.

How it's made. Made by ESA Copernicus from PROBA-V data through mid-2020 and Sentinel-3 OLCI data afterwards, with a new estimate every ten days at about 300-metre detail.

How & where you'd use it. Helps monitor crops, grazing land and drought stress, and supports productivity research. Covers January 2014 to June 2020.

What's measured

CopernicusCLMSDMPDry Matter Productivityvegetation productivityglobal10-daily300mSentinel-3OLCIPROBA-V

Coverage & cadence

  • Time span2014-01-01 → 2026-02-28
  • 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

Represents the overall growth rate or dry biomass increase of the vegetation and is directly related to ecosystem Net Primary Production (NPP), however with units customized for agro-statistical purposes (kg/ha/day). Every 10-days estimates are available in near real time at global scale in the spatial resolution of about 300 m from January 2014 to June 2020 based upon PROBA-V data with version 1.0 and from July 2020 onwards based upon Sentinel-3/OLCI data with version 1.1.

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_dmp_global_300m_10daily_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.