dnearneigh: Neighbourhood contiguity by distance

In spdep: Spatial Dependence: Weighting Schemes, Statistics

Neighbourhood contiguity by distance

Description

The function identifies neighbours of region points by Euclidean distance in the metric of the points 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. If x is an "sf" object and use_s2= is TRUE, spherical distances in km are used.

Usage

dnearneigh(x, d1, d2, row.names = NULL, longlat = NULL, bounds=c("GE", "LE"),
 use_kd_tree=TRUE, symtest=FALSE, use_s2=packageVersion("s2") > "1.0.7", k=200,
 dwithin=TRUE)

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 in the metric of the points if planar coordinates, in km if in geographical coordinates
d2	upper distance boundd in the metric of the points if planar coordinates, in km if in geographical coordinates
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 geographical 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=packageVersion("s2") > "1.0.7", as of s2 > 1.0-7, distance bound computations use spatial indexing so when sf::sf_use_s2() is TRUE, s2::s2_dwithin_matrix() will be used for distances on the sphere for "sf" or "sfc" objects if s2 > 1.0-7.
k	default 200, the number of closest points to consider when searching when using s2::s2_closest_edges()
dwithin	default TRUE, if FALSE, use s2::s2_closest_edges(), both if use_s2=TRUE, sf::st_is_longlat(x) == TRUE and sf::sf_use_s2() == TRUE; s2::s2_dwithin_matrix() yields the same lists of neighbours as s2::s2_closest_edges() is k= is set correctly.

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.

Author(s)

Roger Bivand [e-mail]

See Also

knearneigh, card

Examples

columbus <- st_read(system.file("shapes/columbus.shp", package="spData")[1], quiet=TRUE)
coords <- st_centroid(st_geometry(columbus), of_largest_polygon=TRUE)
rn <- row.names(columbus)
k1 <- knn2nb(knearneigh(coords))
all.linked <- max(unlist(nbdists(k1, coords)))
col.nb.0.all <- dnearneigh(coords, 0, all.linked, row.names=rn)
summary(col.nb.0.all, coords)
opar <- par(no.readonly=TRUE)
plot(st_geometry(columbus), border="grey", reset=FALSE,
 main=paste("Distance based neighbours 0-",  format(all.linked), sep=""))
plot(col.nb.0.all, coords, add=TRUE)
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)
us48.fipsno <- read.geoda(system.file("etc/weights/us48.txt",
 package="spdep")[1])
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))
(all.linked <- max(unlist(nbdists(llk1, xy, 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))
(all.linked <- max(unlist(nbdists(gck1, xy, 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))
#(all.linked <- max(unlist(nbdists(gck1a, xy1))))
#gc.nb <- dnearneigh(xy1, 0, all.linked)
#summary(gc.nb, xy1, scale=0.5)

xy1 <- st_as_sf((as.data.frame(state.center))[m50.48,], coords=1:2,
  crs=st_crs("OGC:CRS84"))
old_use_s2 <- sf_use_s2()
sf_use_s2(TRUE)
gck1b <- knn2nb(knearneigh(xy1, k=1))
system.time(o <- nbdists(gck1b, xy1))
(all.linked <- max(unlist(o)))
# use s2 brute-force dwithin_matrix approach for s2 <= 1.0.7
system.time(gc.nb.dwithin <- dnearneigh(xy1, 0, all.linked, use_s2=TRUE, dwithin=TRUE))
summary(gc.nb, xy1, scale=0.5)
# use s2 closest_edges approach s2 > 1.0.7
if (packageVersion("s2") > "1.0.7") {
(system.time(gc.nb.closest <- dnearneigh(xy1, 0, all.linked, dwithin=FALSE)))
}
if (packageVersion("s2") > "1.0.7") {
system.time(gc.nb.dwithin <- dnearneigh(xy1, 0, all.linked, use_s2=TRUE, dwithin=TRUE))
}
if (packageVersion("s2") > "1.0.7") {
summary(gc.nb.dwithin, xy1, scale=0.5)
}
if (packageVersion("s2") > "1.0.7") {
summary(gc.nb.closest, xy1, scale=0.5)
}
# use legacy symmetric brute-force approach
system.time(gc.nb.legacy <- dnearneigh(xy1, 0, all.linked, use_s2=FALSE))
summary(gc.nb, xy1, scale=0.5)
if (packageVersion("s2") > "1.0.7") all.equal(gc.nb.closest, gc.nb.dwithin, check.attributes=FALSE)
# legacy is ellipsoidal, s2 spherical, so minor differences expected
if (packageVersion("s2") > "1.0.7") all.equal(gc.nb, gc.nb.closest, check.attributes=FALSE)
all.equal(gc.nb, gc.nb.dwithin, check.attributes=FALSE)
sf_use_s2(old_use_s2)
# example of reading points with readr::read_csv() yielding a tibble
load(system.file("etc/misc/coords.rda", package="spdep"))
class(coords)
k1 <- knn2nb(knearneigh(coords, k=1))
all.linked <- max(unlist(nbdists(k1, coords)))
dnearneigh(coords, 0, all.linked)

spdep documentation built on Nov. 23, 2023, 9:06 a.m.