This function is a wrapper of several steps (functions) implemented in the raceland package: create_realizations(), create_densities(), calculate_metrics(), and create_grid().
quantify_raceland(
x,
n,
window_size,
neighbourhood = 4,
fun,
size = NULL,
na_action = "replace",
base = "log2",
ordered = TRUE,
threshold = 0.5
)SpatRaster with race-specific population densities assign to each cell
A number of realizations
Size, expressed in the number of cells, of a square-shaped local window for which local densities will be calculated; it is recommended to use the small window_size, i.e., 10
The number of directions in which cell adjacencies are considered as neighbours: 4 (rook's case), 8 (queen's case). The default is 4.
Function to calculate values from adjacent cells to contribute to exposure matrix, "mean" - calculate average values of local population densities from adjacent cells, "geometric_mean" - calculate geometric mean values of local population densities from adjacent cells, or "focal" assign value from the focal cell
Expressed in the numbers of cells, is a length of the side of a square-shaped block of cells. It defines the extent of a local pattern. If size=NULL calculations are performed for a whole area
Decides on how to behave in the presence of missing values in w. Possible options are "replace", "omit", "keep". The default, "replace", replaces missing values with 0, "omit" does not use cells with missing values, and "keep" keeps missing values.
The unit in which entropy is measured. The default is "log2", which compute entropy in "bits". "log" and "log10" can be also used
The type of pairs considered. Either ordered (TRUE) or unordered (FALSE). The default is TRUE
The share of NA cells to allow metrics calculation in a square-shaped window
An sf polygon object with five columns - row and col allowing for identification of each square polygon, ent - entropy measuring racial diversity, mutinf - mutual information, which is associated with measuring racial segregation, and geometry containing spatial geometries.
library(terra)
race_raster = rast(system.file("extdata/race_raster.tif", package = "raceland"))
rl = quantify_raceland(race_raster, n = 10, window_size = 10,
neighbourhood = 4, fun = "mean", size = 20)