ESA CCI / C3S Land Cover¶

ESA Land Cover CCI (1992–2015, v2.0.7cds) + Copernicus C3S Land cover classification gridded maps (2016 onward, v2.1.1) (annual global 300 m land cover maps, 22-class UN LCCS legend)

Update delayed

At a glance¶

Note on period: 1992–2015 is the ESA CCI v2.0.7cds record; from 2016 the record continues as C3S v2.1.1 produced with the same processing chain (2016–2022 in the CDS request form on 2026-10-13). The 2023–2025 maps are under ECMWF review with no announced release date.

Overview¶

A single continuous record that joins the annual 300 m global land cover maps produced from 1992 onward by ESA's Climate Change Initiative (CCI) Land Cover project with the maps the Copernicus Climate Change Service (C3S) has produced from 2016 with the same processing chain. A baseline map is built from the 2003–2012 MERIS archive and then back- and up-dated with change detection from AVHRR (1992–1999), SPOT-VGT (1998–2012) and PROBA-V, Sentinel-3 OLCI and SLSTR (from 2013). The maps use a 22-class legend based on the FAO LCCS (plus regional sub-classes) with four quality flags, and are widely used for plant-functional-type maps in climate models and for long-term land cover change studies.

What changes with the successor¶

ESA CCI Land Cover v2.0.7cds (1992–2015) → C3S Land Cover v2.1.1 (2016 onward)¶

Transition: 2019-10

C3S took over the 1992–2015 ESA CCI record and has extended it yearly from 2016 with the same processing chain. The two versions are designed to form one series but differ in producer, input sensors and file names.

Sources: CDS — Land cover classification gridded maps from 1992 to present (overview) · ESA CCI — Release of C3S Global Land Cover products for 2016, 2017 & 2018 · ESA CCI Land Cover download page (release history by year)

Available variables¶

NetCDF variable names as given in ESA CCI and C3S release notes and v2.0.7cds file metadata. All are dimensionless integers, and the CDS delivers all variables in one request. The class code table (0 = no data, 10–220) is in the PUG and the Quick User Guide.

instantaneous mean accumulated maximum minimum static — instantaneous: value at the time stamp · mean/accumulated/maximum/minimum: over the indicated interval · static: does not change with time

Land cover classification (classification for the year)¶

Quality flags¶

The full variable list is in the official documentation.

How to get the data¶

• Copernicus CDS — Land cover classification gridded maps from 1992 to present — Web download / CDS API (cdsapi)
  • Choose the year and the version (v2_0_7cds for 1992–2015, v2_1_1 for 2016–2022). Area subsetting is available; files are NetCDF-4 (CF-1.6). Requires an ECMWF account and acceptance of all three licences (CC BY, ESA CCI, VITO).
• CEDA archive — ESA Land_Cover_cci Global Land Cover Maps v2.0.7 (1992–2015) — HTTPS download (NetCDF and GeoTIFF)
  • The original ESA CCI package (58 files, about 67 GB). Use the CDS for 2016 onward.
• ESA CCI Land Cover viewer and download page (UCLouvain) — Web viewer / download / CCI-LC User Tool
  • Map preview plus the PFT maps (v2.0.8), the water body map and the user tool for re-gridding and PFT conversion.

Example code¶

Put the url (https://cds.climate.copernicus.eu/api) and your API key in ~/.cdsapirc and accept the dataset licences on the CDS web page first. Request version "v2_1_1" for 2016 onward and "v2_0_7cds" for 1992–2015. The download may be zipped, so unpack it before opening.

# pip install --upgrade cdsapi xarray netCDF4
import cdsapi

client = cdsapi.Client()
client.retrieve(
    "satellite-land-cover",
    {
        "variable": "all",
        "year": ["2022"],
        "version": ["v2_1_1"],          # use "v2_0_7cds" for 1992–2015
        "area": [39, 124, 33, 132],      # north, west, south, east (around Korea)
    },
    "c3s_lc_2022_korea.zip",
)

# Unpack (file name e.g. C3S-LC-L4-LCCS-Map-300m-P1Y-2022-v2.1.1.nc)
import glob, zipfile
import xarray as xr
if zipfile.is_zipfile("c3s_lc_2022_korea.zip"):
    zipfile.ZipFile("c3s_lc_2022_korea.zip").extractall("c3s_lc")
    nc = glob.glob("c3s_lc/*.nc")[0]
else:
    nc = "c3s_lc_2022_korea.zip"   # delivered as a single NetCDF without zipping
ds = xr.open_dataset(nc)
lc = ds["lccs_class"]            # class codes (e.g. 190 = urban, 210 = water bodies)
forest = lc.isin([50, 60, 61, 62, 70, 71, 72, 80, 81, 82, 90])   # tree cover classes

Practical tips¶

• Sub-classes are separate codes from their parent class. Class 60 (broadleaved deciduous tree cover, >15%) does not contain the pixels coded 61 (>40%) or 62 (15–40%), so total broadleaved deciduous tree cover is the sum of 60, 61 and 62 (likewise 70/71/72 and 80/81/82). The project team confirmed this on the ECMWF forum in September 2026.
• v2.0.7cds (1992–2015) and v2.1.1 (2016 onward) are designed to join into one series, but the producer and input sensors change at 2016. If the 2015→2016 change looks unusually large, suspect a seam.
• Because change detection only captures transitions between IPCC categories and requires changes to persist for two or more years, forest type replacement, changes within cropland and short-lived disturbances do not appear. Treat area-change statistics as a conservative lower bound.
• These are class codes: when moving them to another grid use mode aggregation or nearest neighbour, never averaging or bilinear interpolation. If you need PFT fractions for a climate model, the project's PFT maps (v2.0.8) or the CCI-LC User Tool are more accurate.
• The documentation notes poorer baseline quality where MERIS coverage was sparse (western Amazon, Chile, western Congo basin, Gulf of Guinea, eastern Russia, eastern China, Indonesia, among others).
• Preliminary validation in PUG v2 gave an overall accuracy of about 71–75%, with low accuracy for mosaic natural vegetation, lichens and mosses, sparse vegetation and fresh-water flooded forest.
• CDS requests fail if the version does not match the year (for example 2018 with v2_0_7cds).

Notices and change history¶

References for your paper¶

Dataset citation¶

C3S land cover maps, 1992 to present (CDS) — DOI 10.24381/cds.006f2c9a

@misc{c3s_landcover,
  author    = {{Copernicus Climate Change Service}},
  title     = {Land cover classification gridded maps from 1992 to present derived from satellite observations},
  year      = {2019},
  publisher = {ECMWF},
  doi       = {10.24381/cds.006f2c9a},
  note      = {Accessed on DD-MMM-YYYY}
}

ESA CCI Land Cover Maps v2.0.7 (CEDA, no DOI)

@misc{esacci_lc_v207,
  author    = {{ESA Land Cover CCI project team} and Defourny, Pierre},
  title     = {{ESA} Land Cover Climate Change Initiative ({Land\_Cover\_cci}): Global Land Cover Maps, Version 2.0.7},
  year      = {2019},
  publisher = {Centre for Environmental Data Analysis},
  url       = {https://catalogue.ceda.ac.uk/uuid/b382ebe6679d44b8b0e68ea4ef4b701c}
}

Reference papers¶

Land Cover CCI Product User Guide v2.0 — no DOI

@techreport{defourny2017lccipug,
  author      = {Defourny, Pierre and others},
  title       = {Land Cover {CCI} Product User Guide Version 2.0},
  institution = {UCLouvain-Geomatics},
  number      = {CCI-LC-PUGV2},
  year        = {2017},
  url         = {https://climate.esa.int/media/documents/CCI_Land_Cover_PUG_v2.0.pdf}
}

PFT maps (1992–2020) derived from the same series — DOI 10.5194/essd-15-1465-2023

@article{harper2023pft,
  author  = {Harper, Kandice L. and Lamarche, C{\'e}line and Hartley, Andrew and Peylin, Philippe and Ottl{\'e}, Catherine and Bastrikov, Vladislav and San Mart{\'i}n, Rodrigo and Bohnenstengel, Sylvia I. and Kirches, Grit and Boettcher, Martin and Shevchuk, Roman and Brockmann, Carsten and Defourny, Pierre},
  title   = {A 29-year time series of annual 300 m resolution plant-functional-type maps for climate models},
  journal = {Earth System Science Data},
  volume  = {15},
  number  = {3},
  pages   = {1465--1499},
  year    = {2023},
  doi     = {10.5194/essd-15-1465-2023}
}

Acknowledgements¶

If you downloaded from the CDS, cite the CDS dataset DOI with an access date. The ESA CCI Land Cover project asks users to credit the ESA Climate Change Initiative and its Land Cover project as the data source, acknowledge the project in scientific publications and send a copy to contact@esa-landcover-cci.org. The project's reference paper for the annual maps (Defourny et al., land-use change 1992–2020) was still listed as 'in preparation' on 2026-10-13.

Information on the datasets used in this study was compiled with the help of the Korean Climate Data Navigator (KCDN) (Sim, 2026; https://doi.org/10.5281/zenodo.23300923).

Links¶

• CDS — Land cover classification gridded maps from 1992 to present
• Land Cover CCI Product User Guide v2.0 (method, legend, limitations)
• ESA CCI LC Quick User Guide v2.0.7 (legend codes, quality flags)
• C3S v2.1.1 Product User Guide and Specification (PUGS, 2021–2022 Sentinel-3)
• ESA Climate Office — Land Cover CCI data
• ECMWF forum — answer on sub-classes (60/61/62)