ECfunc: A function to compute environmental centralization index

Description

Environmental Centralization index compares the spatial distribution of two social groups around a specific environmental (dis-)amenity, located at one or more points.

Usage

ECfunc (x, distmin = NULL, dist = NULL, K = NULL, kdist = NULL,
spatobj1 = NULL, folder1 = NULL, shape1 = NULL,
spatobj2 = NULL, folder2 = NULL, shape2 = NULL)

Value

The matrix with environmental centralization index values

Arguments

x: - a matrix with the groups distributions across spatial units
distmin: - an optional vector with the minimal distance between each spatial unit and all the environmental localisations. If not provided, it will be computed in the function
dist: - an optional matrix with the distance between all spatial units and environmental localisations. If not provided, it will be computed in the function
K: - if provided, the version of the index constrained to the K nearest neighbors
kdist: - if provided, the version of the index constrained to the nearest neighbors within a distance of kdist
spatobj1: - polygons spatial objects for population distribution to compute distances matrix (necessary if distance not provided).
folder1: - a character vector with the folder (directory) name indicating where the shapefile with geographical info of population distribution is located on the drive (necessary if distance and spatial object are not provided).
shape1: - a character vector with the name of the shapefile (without the .shp extension) with geographical info of population distribution
spatobj2: - points spatial objects for (dis-)amenity location to compute distances matrix (necessary if distance not provided).
folder2: - a character vector with the folder (directory) name indicating where the shapefile with geographical info of (dis-)amenity distribution is located on the drive (necessary if distance and spatial object are not provided).
shape2: - a character vector with the name of the shapefile (without the .shp extension) with geographical info of (dis-)amenity spatial location

References

Schaeffer Y. and Tivadar M. (2019) Measuring Environmental Inequalities: Insights from the Residential Segregation Literature. Ecological Economics, 164, 106329

Tivadar M. (2019) OasisR: An R Package to Bring Some Order to the World of Segregation Measurement. Journal of Statistical Software, 89 (7), pp. 1-39

Duncan O. D. and Duncan B. (1955) Residential Distribution and Occupational Stratification. American Journal of Sociology, 60 (5), pp. 493-503

Folch D.C and Rey S. J (2016) The centralization index: A measure of local spatial segregation. Papers in Regional Science, 95 (3), pp. 555-576

Examples

Run this code

data(segdata, package = "OasisR")
# segdata - theoretical distributions on a 10x10 grid map
# We consider A1 and A2 - two populations distribution and
# the amenities are located in the grid center
distance <- sf::st_distance(sf::st_centroid(sf::st_as_sf(segdata)),
sf::st_centroid(sf::st_union(sf::st_as_sf(segdata))))
ECfunc (segdata@data[,3:4], dist = distance)