Download and process Global Future Land Use/Cover layers (2020-2100)

This function downloads, processes, and extracts simulated global land use and land cover (LULC) data for the period 2020-2100.

Usage

gcamlandcover(x, vars = "landcover", ssp = 126, year = 2020, ...)

Arguments

x: The output from `par_set()` defining the area or locations for extraction, the reference system, and the buffer.
vars: Character. Currently unused/ignored as this function returns the landcover map defined by `year` and `ssp`, but kept for consistency. Default is "landcover".
ssp: Numeric or Character. The SSP scenario code (126, 245, 370, 434, 585). Ignored if `year` is 2020.
year: Numeric. The year of simulation (2020, 2030, 2050, 2070, 2100).
...: Additional arguments (currently unused).

Value

If `par_set()` contained a raster/polygon/points with buffer: a `SpatRaster` stack. If `par_set()` contained spatial points without buffer: a `data.frame`.

Details

The data represents 1 km resolution LULC maps. The original data is in World Mercator projection and will be automatically reprojected to the CRS defined in `par_set()`.

Land cover codes

1 - Cropland
2 - Forest
3 - Grassland
4 - Urban
5 - Barren
6 - Water

Available Years

2020, 2030, 2050, 2070, 2100

Available SSPs (Shared Socioeconomic Pathways)

126 (SSP1-2.6)
245 (SSP2-4.5)
370 (SSP3-7.0)
434 (SSP4-3.4)
585 (SSP5-8.5)

Citation:
Zhang T, Cheng C, Wu X (2023). "Mapping the spatial heterogeneity of global land use and land cover from 2020 to 2100 at a 1 km resolution." Scientific Data 10, 748. https://doi.org/10.1038/s41597-023-02637-7

Examples

# \donttest{
# Get Baseline (2020)
processed <- par_set(country= "Italy", crs=4326) %>% 
  gcamlandcover(year = 2020)

# Get Future (SSP5-8.5 in 2050)
processed <- par_set(country= "Italy", crs=4326) %>% 
  gcamlandcover(ssp = 585, year = 2050)
# }