spdep (version 1.1-12)

dnearneigh: Neighbourhood contiguity by distance

Description

The function identifies neighbours of region points by Euclidean distance between lower (greater than or equal to (changed from version 1.1-7)) and upper (less than or equal to) bounds, or with longlat = TRUE, by Great Circle distance in kilometers.

Usage

dnearneigh(x, d1, d2, row.names = NULL, longlat = NULL, bounds=c("GE", "LE"),
use_kd_tree=TRUE, symtest=FALSE, use_s2=FALSE, max_cells=200, dwithin=FALSE)

Arguments

x

matrix of point coordinates, an object inheriting from SpatialPoints or an "sf" or "sfc" object; if the "sf" or "sfc" object geometries are in geographical coordinates (use_s2=FALSE, sf::st_is_longlat(x) == TRUE and sf::sf_use_s2() == TRUE), s2 will be used to find the neighbours because it will (we hope) use spatial indexing https://github.com/r-spatial/s2/issues/125 as opposed to the legacy method which uses brute-force (at present s2 also uses brute-force)

d1

lower distance bound

d2

upper distance bound

row.names

character vector of region ids to be added to the neighbours list as attribute region.id, default seq(1, nrow(x))

longlat

TRUE if point coordinates are longitude-latitude decimal degrees, in which case distances are measured in kilometers; if x is a SpatialPoints object, the value is taken from the object itself, and overrides this argument if not NULL

bounds

character vector of length 2, default c("GE", "LE"), (GE: greater than or equal to, LE: less than or equal to) that is the finite and closed interval [d1, d2], d1 <= x <= d2. The first element may also be "GT" (GT: greater than), the second "LT" (LT: less than) for finite, open intervals excluding the bounds; the first bound default was changed from "GT" to "GE" in release 1.1-7. When creating multiple distance bands, finite, half-open right-closed intervals may be used until the final interval to avoid overlapping on bounds: "GE", "LT", that is [d1, d2), d1 <= x < d2

use_kd_tree

default TRUE, if TRUE, use dbscan frNN if available (permitting 3D distances).

symtest

Default FALSE; before release 1.1-7, TRUE - run symmetry check on output object, costly with large numbers of points.

use_s2

default=FALSE, as of s2 1.0-5, distance bound compuations do not use spatial indexing so even if sf::sf_use_s2() is TRUE, s2 will not be used for distances on the sphere for "sf" or "sfc" objects; the default will change when/if spatial indexing becomes available. Until then, setting set.coresOption to a positive integer will experimentaly use that number of cores on .Platform\$OS.type== "unix" systems.

max_cells

default 200; if use_s2=TRUE, sf::st_is_longlat(x) == TRUE, sf::sf_use_s2() == TRUE and dwithin=FALSE, set max_cells in s2::s2_buffer_cells()

dwithin

default FALSE to use s2::s2_buffer_cells() and s2::s2_intersects_matrix(), if TRUE, use s2::s2_dwithin_matrix(), both if use_s2=TRUE, sf::st_is_longlat(x) == TRUE and sf::sf_use_s2() == TRUE; both yield the same lists of neighbours.

Value

The function returns a list of integer vectors giving the region id numbers for neighbours satisfying the distance criteria. See card for details of “nb” objects.

Examples

# NOT RUN {
coords <- st_centroid(st_geometry(columbus), of_largest_polygon=TRUE)
rn <- row.names(columbus)
k1 <- knn2nb(knearneigh(coords))
col.nb.0.all <- dnearneigh(coords, 0, all.linked, row.names=rn)
summary(col.nb.0.all, coords)
plot(st_geometry(columbus), border="grey", reset=FALSE,
main=paste("Distance based neighbours 0-",  format(all.linked), sep=""))
par(opar)
(sfc_obj <- st_centroid(st_geometry(columbus)))
col.nb.0.all_sf <- dnearneigh(sfc_obj, 0, all.linked, row.names=rn)
all.equal(col.nb.0.all, col.nb.0.all_sf, check.attributes=FALSE)
data(state)
package="spdep"))
if (as.numeric(paste(version\$major, version\$minor, sep="")) < 19) {
m50.48 <- match(us48.fipsno\$"State.name", state.name)
} else {
m50.48 <- match(us48.fipsno\$"State_name", state.name)
}
xy <- as.matrix(as.data.frame(state.center))[m50.48,]
llk1 <- knn2nb(knearneigh(xy, k=1, longlat=FALSE))
ll.nb <- dnearneigh(xy, 0, all.linked, longlat=FALSE)
summary(ll.nb, xy, longlat=TRUE, scale=0.5)
gck1 <- knn2nb(knearneigh(xy, k=1, longlat=TRUE))
gc.nb <- dnearneigh(xy, 0, all.linked, longlat=TRUE)
summary(gc.nb, xy, longlat=TRUE, scale=0.5)
plot(ll.nb, xy)
plot(diffnb(ll.nb, gc.nb), xy, add=TRUE, col="red", lty=2)
title(main="Differences Euclidean/Great Circle")

xy1 <- SpatialPoints((as.data.frame(state.center))[m50.48,],
proj4string=CRS("+proj=longlat +ellps=GRS80"))
gck1a <- knn2nb(knearneigh(xy1, k=1))
summary(gc.nb, xy1, scale=0.5)

xy1 <- st_as_sf((as.data.frame(state.center))[m50.48,], coords=1:2,
crs=st_crs("+proj=longlat +ellps=GRS80"))
old_use_s2 <- sf_use_s2()
sf_use_s2(TRUE)
gck1b <- knn2nb(knearneigh(xy1, k=1))
system.time(o <- nbdists(gck1b, xy1))
# use s2 brute-force buffer/intersect approach (with two passes if d1 > 0)
system.time(gc.nb <- dnearneigh(xy1, 0, all.linked, use_s2=TRUE))
summary(gc.nb, xy1, scale=0.5)
# use s2 brute-force buffer/intersect approach with smaller max_cells
system.time(gc.nb <- dnearneigh(xy1, 0, all.linked, use_s2=TRUE, max_cells=500))
summary(gc.nb, xy1, scale=0.5)
# use s2 brute-force dwithin_matrix approach
system.time(gc.nb <- dnearneigh(xy1, 0, all.linked, use_s2=TRUE, dwithin=TRUE))
summary(gc.nb, xy1, scale=0.5)
# use legacy symmetric brute-force approach