Biome names

Obtain biome names from the map created by Hengl et al. (2018) , using the ID_BIOME.

biome_name(.data, ...)

# S3 method for tbl_df
biome_name(.data, ...)

# S3 method for numeric
biome_name(.data, ...)

Arguments

.data

Numeric vector or data frame (tibble object with a column called ID_BIOME) with values linked to a biome provided by the map created by Hengl (2018) . (See pnv_classes).

...

Optional parameters (not used).

Value

Table (tibble object) with biome metadata.

References

Hengl T (2018). “Global Maps of Potential Natural Vegetation at 1 km resolution.” doi:10.7910/DVN/QQHCIK .

Hengl T, Walsh MG, Sanderman J, Wheeler I, Harrison SP, Prentice IC (2018). “Global mapping of potential natural vegetation: an assessment of machine learning algorithms for estimating land potential.” PeerJ, 6, e5457. doi:10.7717/peerj.5457 .

See also

Other utils biome: extract_biome(), plot_biome()

Examples

`%>%` <- magrittr::`%>%`
data <- tibble::tibble(entity_name = "University of Reading",
                        latitude = 51.4414,
                        longitude = -0.9418)
data %>%
  extract_biome() %>%
  biome_name()
#> Error in loadNamespace(x): there is no package called ‘rgdal’

biome_name(1:10)
#> # A tibble: 7 × 3
#>   ID_BIOME description                                         colour 
#>      <dbl> <chr>                                               <chr>  
#> 1        1 tropical evergreen broadleaf forest                 #1C5510
#> 2        2 tropical semi-evergreen broadleaf forest            #659208
#> 3        3 tropical deciduous broadleaf forest and woodland    #AE7D20
#> 4        4 warm-temperate evergreen broadleaf and mixed forest #000065
#> 5        7 cool-temperate rainforest                           #BBCB35
#> 6        8 cool evergreen needleleaf forest                    #009A18
#> 7        9 cool mixed forest                                   #CAFFCA