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High-resolution annual continental European land use / land cover data since 2000

Probability and uncertainty maps of 43 CORINE land use / land cover classes in Europe, namely:

  • 111 - Continuous urban fabric;
  • 112 - Discontinuous urban fabric;
  • 121 - Industrial or commercial units;
  • 122 - Road and rail networks and associated land;
  • 123 - Port areas;
  • 124 - Airports;
  • 131 - Mineral extraction sites;
  • 132 - Dump sites;
  • 133 - Construction sites;
  • 141 - Green urban areas;
  • 142 - Sport and leisure facilities;
  • 211 - Non-irrigated arable land;
  • 212 - Permanently irrigated arable land;
  • 213 - Rice fields;
  • 221 - Vineyards;
  • 222 - Fruit trees and berry plantations;
  • 223 - Olive groves;
  • 231 - Pastures;
  • 241 - Annual crops associated with permanent crops;
  • 242 - Complex cultivation patter;
  • 243 - Land principally occupied by agriculture with significant areas of natural vegetation;
  • 244 - Agro-forestry areas;
  • 311 - Broad-leaved forest;
  • 312 - Coniferous forest;
  • 313 - Mixed forest;
  • 321 - Natural grasslands;
  • 322 - Moors and heathland;
  • 323 - Sclerophyllous vegetation;
  • 324 - Transitional woodland-shrub;
  • 331 - Beaches, dunes, sand;
  • 332 - Bare rocks;
  • 333 - Sparsely vegetated areas;
  • 334 - Burnt areas;
  • 335 - Glaciers and perpetual snow;
  • 411 - Inland marshes;
  • 412 - Peat bogs;
  • 421 - Salt marshes;
  • 422 - Salines;
  • 423 - Intertidal flats;
  • 511 - Water courses;
  • 512 - Water bodies;
  • 521 - Coastal lagoons;
  • 522 - Estuaries.

Files are named according to the following naming convention, e.g:

  • lcv_landcover.111_lucas.corine.eml_p_30m_0..0cm_2020_eumap_epsg3035_v0.2.tif

with the following fields:

  • theme: e.g. lcv,
  • land use / land cover class: e.g. landcover.111,
  • estimation method: e.g. lucas.corine.eml,
  • variable type: e.g. p ( = class probability),
  • resolution in meters e.g. 30m,
  • reference depths (vertical dimension): e.g. 0..0cm,
  • reference period: e.g. 2020,
  • reference area: e.g. eumap,
  • coordinate system: e.g. epsg3035,
  • data set version: e.g. v0.2.

This naming convention makes it easy to identify the file names of probability and uncertainty maps for each land use / land cover class:

  • lcv_landcover.111_lucas.corine.eml_p: Probability of class 111: Continuous Urban Fabric 
  • lcv_landcover.311_lucas.corine.eml_md: Model Disagreement of class 311: Broad-leaved forest

Code on structure and applications of the dataset is available on GitLab

European coverage, 30m resolution, Cloud Optimized Geotiff, https download

EPSG:3035

Witjes, Martijn;  Parente, Leandro; van Diemen, Chris; Hengl, Tomislav; Landa, Martin; Brodský, Lukáš; Halounova, Lena; Križan, Josip; Antonić, Luka; Ilie, Codrina Maria; Craciunescu, Vasile; Kilibarda, Milan; Antonijevic Ognjen & Glusica, Luka. (2022).  Continental Europe land cover mapping at 30m resolution based on CORINE and LUCAS samples [Data set]. Zenodo. https://doi.org/10.5281/zenodo.4725429

The datasets can be accessed on Zenodo. Check the Related identifiers section on the right to access the individual classes.

				
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# Driver: GTiff/GeoTIFF
# Files: /vsicurl/http://s3.eu-central-1.wasabisys.com/eumap/lcv/lcv_landcover.hcl_lucas.corine.rf_p_30m_0..0cm_2019_eumap_epsg3035_v0.1.tif
# Size is 188000, 151000
# Coordinate System is:
# PROJCRS["ETRS89-extended / LAEA Europe",
#     BASEGEOGCRS["ETRS89",
#         DATUM["European Terrestrial Reference System 1989",
#             ELLIPSOID["GRS 1980",6378137,298.257222101,
#                 LENGTHUNIT["metre",1]]],
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#             ANGLEUNIT["degree",0.0174532925199433]],
#         ID["EPSG",4258]],
#     CONVERSION["Europe Equal Area 2001",
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#             ORDER[1],
#             LENGTHUNIT["metre",1]],
#         AXIS["easting (X)",east,
#             ORDER[2],
#             LENGTHUNIT["metre",1]],
#     USAGE[
#         SCOPE["unknown"],
#         AREA["Europe - LCC & LAEA"],
#         BBOX[24.6,-35.58,84.17,44.83]],
#     ID["EPSG",3035]]
# Data axis to CRS axis mapping: 2,1
# Origin = (900000.000000000000000,5460010.000000000000000)
# Pixel Size = (30.000000000000000,-30.000000000000000)
# Metadata:
#   1=111 - Urban fabric
#   10=212 - Permanently irrigated arable land
#   11=213 - Rice fields
#   12=221 - Vineyards
#   13=222 - Fruit trees and berry plantations
#   14=223 - Olive groves
#   15=231 - Pastures
#   16=311 - Broad-leaved forest
#   17=312 - Coniferous forest
#   18=321 - Natural grasslands
#   19=322 - Moors and heathland
#   2=122 - Road and rail networks and associated land
#   20=323 - Sclerophyllous vegetation
#   21=324 - Transitional woodland-shrub
#   22=331 - Beaches, dunes, sands
#   23=332 - Bare rocks
#   24=333 - Sparsely vegetated areas
#   25=334 - Burnt areas
#   26=335 - Glaciers and perpetual snow
#   27=411 - Inland wetlands
#   28=421 - Maritime wetlands
#   29=511 - Water courses
#   3=123 - Port areas
#   30=512 - Water bodies
#   31=521 - Coastal lagoons
#   32=522 - Estuaries
#   33=523 - Sea and ocean
#   4=124 - Airports
#   5=131 - Mineral extraction sites
#   6=132 - Dump sites
#   7=133 - Construction sites
#   8=141 - Green urban areas
#   9=211 - Non-irrigated arable land
#   AREA_OR_POINT=Area
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