extract_biome | R Documentation |
Extracts biome for a point (latitude
, longitude
) based on the
map with Potential Natural Vegetation (PNV) created by Hengl et al., 2018.
extract_biome(.data, ...)
## S3 method for class 'tbl_df'
extract_biome(
.data,
...,
reference = smpds::PNV_1km,
buffer = 12000,
all = FALSE
)
## S3 method for class 'sf'
extract_biome(
.data,
...,
reference = smpds::PNV_1km,
buffer = 12000,
all = FALSE
)
parallel_extract_biome(
.data,
reference = smpds::PNV_1km,
buffer = 12000,
cpus = 2,
all = FALSE
)
.data |
Table containing columns for |
... |
Arguments passed on to |
reference |
Reference map with biomes, default: |
buffer |
numeric. The radius of a buffer around each point from which to extract cell values. If the distance between the sampling point and the center of a cell is less than or equal to the buffer, the cell is included. The buffer can be specified as a single value, or as a vector of the length of the number of points. If the data are not projected (latitude/longitude), the unit should be meters. Otherwise it should be in map-units (typically also meters). |
all |
Boolean flag to indicate whether or not to return all the detected
biomes, default: |
cpus |
Number of CPUs to be used in parallel, default = 2. |
Table with the original data and matched biome(s):
if all = FALSE
(default): Only returns the dominant biome:
ID_BIOME
if all = TRUE
: Returns all the detected biome -
ID_BIOME
and px
, the number of pixels detected for each
biome.
Other utils biome:
biome_name()
,
plot_biome()
`%>%` <- magrittr::`%>%`
data <- tibble::tibble(entity_name = "University of Reading",
latitude = 51.44140,
longitude = -0.9418)
data %>%
extract_biome()
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