sdm_area | R Documentation |
sdm_area
objectThis function creates a new sdm_area
object.
sdm_area(x, cell_size = NULL, crs = NULL, variables_selected = NULL,
gdal = TRUE, crop_by = NULL, lines_as_sdm_area = FALSE)
get_sdm_area(i)
add_sdm_area(sa1, sa2)
x |
A shape or a raster. Usually a shape from |
cell_size |
|
crs |
|
variables_selected |
A |
gdal |
Boolean. Force the use or not of GDAL when available. See details. |
crop_by |
A shape from |
lines_as_sdm_area |
Boolean. If |
i |
A |
sa1 |
A |
sa2 |
A |
The function returns a sdm_area
object with a grid built upon the x
parameter.
There are two ways to make the grid and resample the variables in sdm_area
: with and
without gdal. As standard, if gdal is available in you machine it will be used
(gdal = TRUE
),
otherwise sf/stars will be used.
get_sdm_area
will return the grid built by sdm_area
.
add_sdm_area
will sum two sdm_area
objects. As geoprocessing in caretSDM
is
performed using sf
objects, add_sdm_area
simply applies a rbind
in the two
different areas.
A sdm_area
object containing:
grid |
|
cell_size |
|
Luíz Fernando Esser (luizesser@gmail.com) and Reginaldo Ré. https://luizfesser.wordpress.com
WorldClim_data parana input_sdm, add_predictors
# Create sdm_area object:
sa_area <- sdm_area(parana, cell_size = 50000, crs = 6933)
# Create sdm_area using a subset of rivs (lines):
sa_rivers <- sdm_area(rivs[c(1:100),], cell_size = 100000, crs = 6933, lines_as_sdm_area = TRUE)
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