Global Land Cover

Download a SpatRaster from the Global Land Cover from the Copernicus Global Land Service.

Usage

fd_landcover_copernicus(
  x,
  lon = NULL,
  lat = NULL,
  year = 2019,
  layer = "forest",
  crop = FALSE,
  ...
)

Arguments

x

an sf or SpatVector object. It will retrieve the necessary tiles to cover the area (if lat and lon are specified, this argument is ignored)

lon

a number specifying the longitude of the area where we want the tile

lat

a number specifying the latitude of the area where we want the tile

year

year of the forest extent data. One of 2015:2019 or 'all'

layer

a character vector of the layer(s) to use from the Global Land Cover. See details

crop

when x is specified, whether to crop the tiles(s) to the object

...

additional arguments passed to the crop function

Value

SpatRaster object

Details

There are 14 different layers that can be downloaded:

- "discrete": land cover discrete classification

- "classification": land cover classification probability

- "bare": cover fraction of bare and sparse vegetation

- "builtup": cover fraction of builtup

- "crops": cover fraction of cropland

- "tree": cover fraction of forest

- "grass": cover fraction of herbaceous vegetation

- "mosslichen": cover fraction of moss and lichen

- "seasonalwater": cover fraction of seasonal inland water

- "shrub": cover fraction of shrubland

- "snow": cover fraction of snow and ice

- "permanentwater": cover fraction of permanent inland water

- "forest" (default): forest types. (0): unknown; (1): evergreen needle leaf forest; (2): evergreen broad leaf forest; (3): deciduous needle leaf; (4): deciduous broad leaf; (5): mix of forest types

- "datadensityindicator": input data density

References

Buchhorn, M.; Smets, B.; Bertels, L.; De Roo, B.; Lesiv, M.; Tsendbazar, N. - E.; Herold, M.; Fritz, S. Copernicus Global Land Service: Land Cover 100m: collection 3: epoch 2019: Globe 2020. DOI 10.5281/zenodo.3939050

Examples

# \donttest{
 # Get tile for Galicia (Spain) and year 2019
 galicia_forest_extent <- fd_landcover_copernicus(
  lat  = 42.7,
  lon  = -7.8,
  year = 2019
 )
#> 1 tile(s) were found.
 # Get forest and discrete classification tiles for all years
 galicia_forest_extent <- fd_landcover_copernicus(
  lat  = 42.7,
  lon  = -7.8,
  year = "all",
  layer = c("forest", "discrete")
 )
#> 10 tile(s) were found.
 # }