segdata: Hypothetical Patterns of Segregation

In seg: Measuring Spatial Segregation

Description

This data set contains eight different spatial configurations that were used by Morrill (1991) and Wong (1993) to test their segregation measures.

Usage

data(segdata)

Format

An object of class data.frame. The data set contains 16 columns, representing eight idealised spatial patterns. Each column indicates the following information:

[,1]	A1	Pattern A, Group 1
[,2]	A2	Pattern A, Group 2
[,3]	B1	Pattern B, Group 1
[,4]	B2	Pattern B, Group 2
[,5]	C1	Pattern C, Group 1
[,6]	C2	Pattern C, Group 2
[,7]	D1	Pattern D, Group 1
[,8]	D2	Pattern D, Group 2
[,9]	E1	Pattern E, Group 1
[,10]	E2	Pattern E, Group 2
[,11]	F1	Pattern F, Group 1
[,12]	F2	Pattern F, Group 2
[,13]	G1	Pattern G, Group 1
[,14]	G2	Pattern G, Group 2
[,15]	H1	Pattern H, Group 1
[,16]	H2	Pattern H, Group 2

Source

Morrill, R. L. (1991). On the measure of geographic segregation. Geography Research Forum, 11, 25-36.

Wong, D. W. S. (1993). Spatial Indices of Segregation. Urban Studies, 30, 559-572.

Examples

data(segdata)
grd <- GridTopology(cellcentre.offset=c(0.5,0.5),
                    cellsize=c(1,1), cells.dim=c(10,10))
grd.sp <- as.SpatialPolygons.GridTopology(grd)

pd <- par()
par(mfrow = c(2, 4), mar = c(0, 1, 0, 1))
for (i in 1:8) {
  full <- segdata[,(2*i)-1] == 100
  half <- segdata[,(2*i)-1] == 50
  plot(grd.sp)
  plot(grd.sp[full,], col = "Black", add = TRUE)
  if (any(half))
    plot(grd.sp[half,], col = "Grey", add = TRUE)
  text(5, 11.5, labels = paste("Pattern", LETTERS[i]))
}
par(mfrow = pd$mfrow, mar = pd$mar)

seg documentation built on Dec. 19, 2019, 1:09 a.m.