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Full catalog/clms_lst-tci_global_5km_10daily_v1
clms_lst-tci_global_5km_10daily_v1·dataset

Land heat and stress index, 2017-2021 (Copernicus)

CLMS LST-TCI Global 5km 10-daily V1
land ESA ESA Copernicus COGNetCDF
In plain English

What it measures. A ten-day summary of ground-surface temperature for each pixel together with a Thermal Condition Index marking how unusual the heat or cold is. This early version covers 2017 to 2021.

How it's made. Created by ESA Copernicus from geostationary satellite thermal data at roughly 5-kilometer pixels.

How & where you'd use it. Supports historical drought and heat-stress assessment and provides a baseline for comparing thermal conditions across past years.

What's measured

CopernicusCLMSLST-TCILand Surface Temperaturethermal infraredglobal10-daily5km

Coverage & cadence

  • Time span2017-01-01 → 2021-01-10
  • Spatial extent-179.9999999, -79.9776824, 179.9776872, 80.0223214
  • FormatsCOG, NetCDF

What you can do with it

  • Track deforestation, fire scars and land-cover change
  • Monitor crop and vegetation health (NDVI/EVI)
  • Map how built-up vs. green an area is over time
Official description

Provides a statistical overview of the land surface temperature over each 10-day compositing period for every image pixel, including a Thermal Condition Index. The data are available at global scale in the spatial resolution of about 5 km and cover the period from 2017 to 2021.

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_lst-tci_global_5km_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.