Global Land Cover

Short description

Global Land Cover products at 100 m resolution are delivered annually by the global component of the Copernicus Land Service. The most recent collection 3 (version 3.0.1) of 100 m Land Cover products for the years 2015 - 2019 were generated from the PROBA-V 100 m and 300 m satellite observations and several other ancillary datasets with global coverage. As from 2020, (2019-conso and 2020-nrt products) are planned to be generated from the combination of Sentinel-1 and Sentinel-2 satellite observations following end of PROBA-V operations. These Land Cover products provide a main discrete land cover classification map according to UN-FAO Land Cover Classification System LCCS. Additional continuous fractional layers for all basic land cover classes which give the percentage of a 100 m pixel that is filled with a specific land cover class, are also included in the Land Cover products to provide more detailed information on each land cover class.

Update frequency

A new product is generated annually using an 'epoch', where an epoch consists of 3 years input data (one year before and one year after the reference year) in three processing modes. See Product User Manual for more details on the procesing modes.

Temporal availability

The following epochs are available:
Epoch year Product generation mode
2015 base
2016 consolidated
2017 consolidated
2018 consolidated
2019 near real time

Band information

The available bands include: a main discrete classification with 23 classes aligned with UN-FAO's Land Cover Classification System, a discrete classification probability map, fractional cover maps for the 10 main classes, a forest type layer, quality layer on input data density and on the confidence of the detected land cover change (only delivered for maps produced in conso or nrt mode)
Reference: Product User ManualTable 1: Bands
Name Units Values Description
Discrete_Classification_map 0 - 200 main discrete land cover classification according to FAO LCCS scheme
Discrete_Classification_proba % 0 - 100 Classification probability, a quality indicator for the discrete classification
Forest_Type_layer 0 - 5 Forest type for all pixels where tree cover fraction is bigger than 1 %
Bare_CoverFraction_layer % 0 - 100 Fractional cover (%) for the bare and sparse vegetation class
Crops_CoverFraction_layer % 0 - 100 Fractional cover (%) for the cropland class
Grass_CoverFraction_layer % 0 - 100 Fractional cover (%) for the herbaceous vegetation class
MossLichen_CoverFraction_layer % 0 - 100 Fractional cover (%) for the moss & lichen class
Shrub_CoverFraction_layer % 0 - 100 Fractional cover (%) for the shrubland class
Snow_CoverFraction_layer % 0 - 100 Fractional cover (%) for the snow & ice class
Tree_CoverFraction_layer % 0 - 100 Fractional cover (%) for the forest class
BuiltUp_CoverFraction_layer % 0 - 100 Fractional cover (%) for the built-up class
PermanentWater_CoverFraction_layer % 0 - 100 Fractional cover (%) for the permanent inland water bodies class
SeasonalWater_CoverFraction_layer % 0 - 100 Fractional cover (%) for the seasonal inland water bodies class
DataDensityIndicator 0 - 100 Data density indicator showing quality of the EO input data (0 = bad, 100 = perfect data)
Change_Confidence_layer 0 - 3 Quality layer regarding the change detection of the current mapped year to the previous mapped year. It is a 3 level confidence mask for all CONSO and NRT maps with value definitions as:
  • 0 = No change.
  • 1 - Potential confidence.
  • 2 - Medium confidence.
  • 3 = High confidence.
NOTE: The values of Change_Confidence_layer band in 2015 data are not shown correctly, therefore this band in 2015 data should not be used.
Table 2: Discrete_Classsification_map classes A visualisation script can be found in our custom scripts repository.
Value Color Color Code Label
0 0x282828 No input data available
20 0xffbb22 Shrubs
30 0xffff4c Herbaceous vegetation
40 0xf096ff Cultivated and managed vegetation/agriculture (cropland)
50 0xfa0000 Urban / built up
60 0xb4b4b4 Bare / sparse vegetation
70 0xf0f0f0 Snow and Ice
80 0x0032c8 Permanent water bodies
90 0x0096a0 Herbaceous wetland
100 0xfae6a0 Moss and lichen
111 0x58481f Closed forest, evergreen needle leaf
112 0x009900 Closed forest, evergreen, broad leaf
113 0x70663e Closed forest, deciduous needle leaf
114 0x00cc00 Closed forest, deciduous broad leaf
115 0x4e751f Closed forest, mixed
116 0x007800 Closed forest, unknown
121 0x666000 Open forest, evergreen needle leaf
122 0x8db400 Open forest, evergreen broad leaf
123 0x8d7400 Open forest, deciduous needle leaf
124 0xa0dc00 Open forest, deciduous broad leaf
125 0x929900 Open forest, mixed
126 0x648c00 Open forest, unknown
200 0x000080 Open sea
255 No data
Table 3: Forest_Type_Layer classes
Value Label
0 Unknown, doesn’t match any of the other types
1 Evergreen needle leaf
2 Evergreen broad leaf
3 Deciduous needle leaf
4 Deciduous broad leaf
5 Mix of forest type
255 No data

More information

Discrete classification map  for parts of North Africa 2019 nrt discrete land cover classification map for parts of North Africa visualised in EO browserforest type map for Dominican Republic2019 nrt forest type Map over Dominican Republic and Haiti visualised in EO browser