make.RapData {raptr} | R Documentation |
Make data for RAP using minimal inputs
Description
This function prepares spatially explicit planning unit, species data, and
landscape data layers for RAP processing.
Usage
make.RapData(
pus,
species,
spaces = NULL,
amount.target = 0.2,
space.target = 0.2,
n.demand.points = 100L,
kernel.method = c("ks", "hypervolume")[1],
quantile = 0.5,
species.points = NULL,
n.species.points = ceiling(0.2 * terra::global(species, "sum", na.rm = TRUE)[[1]]),
include.geographic.space = TRUE,
scale = TRUE,
verbose = FALSE,
...
)
Arguments
pus |
sf::st_as_sf() with planning unit data.
|
species |
terra::rast() with species probability
distribution data.
|
spaces |
list of/or terra::rast() representing
projects of attribute space over geographic space. Use a list to
denote separate attribute spaces.
|
amount.target |
numeric vector for area targets (%) for each
species. Defaults to 0.2 for each attribute space for each species.
|
space.target |
numeric vector for attribute space targets (%)
for each species. Defaults to 0.2 for each attribute space for each
species and each space.
|
n.demand.points |
integer number of demand points to use for
each attribute space for each species. Defaults to 100L.
|
kernel.method |
character name of kernel method to use to
generate demand points. Use either "ks" or "hypervolume" .
|
quantile |
numeric quantile to generate demand points within. If
species.points intersect. Defaults to 0.5.
|
species.points |
list of/or sf::st_sf() object species presence
records. Use a
list of objects to represent different species. Must have the same
number of elements as species . If not supplied then use
n.species.points to sample points from the species distributions.
|
n.species.points |
numeric vector specifying the number points
to sample the species distributions to use to generate demand points.
Defaults to 20% of the distribution.
|
include.geographic.space |
logical should the geographic space
be considered an attribute space?
|
scale |
logical scale the attribute spaces to unit mean and
standard deviation? This prevents overflow. Defaults to TRUE .
|
verbose |
logical print statements during processing?
|
... |
additional arguments to calcBoundaryData() and
calcSpeciesAverageInPus() .
|
Value
A new RapData
object.
See Also
RapData, RapData()
.
Examples
## Not run:
# load data
cs_pus <- sf::read_sf(
system.file("extdata", "cs_pus.gpkg", package = "raptr")
)
cs_spp <- terra::rast(
system.file("extdata", "cs_spp.tif", package = "raptr")
)
cs_space <- terra::rast(
system.file("extdata", "cs_space.tif", package = "raptr")
)
# make RapData object using the first 10 planning units in the dat
x <- make.RapData(cs_pus[1:10,], cs_spp, cs_space,
include.geographic.space = TRUE)
# print object
print(x)
## End(Not run)
[Package
raptr version 1.0.1
Index]