spdep: knearneigh – R documentation

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knearneigh

K nearest neighbours for spatial weights

Description

The function returns a matrix with the indices of points belonging to the set of the k nearest neighbours of each other. If longlat = TRUE, Great Circle distances are used. A warning will be given if identical points are found.

Usage

knearneigh(x, k=1, longlat = NULL, use_kd_tree=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 (`sf::st_is_longlat(x) == TRUE` and `sf::sf_use_s2() == TRUE`), s2 will be used to find the neighbours because it uses spatial indexing https://github.com/r-spatial/s2/issues/125 as opposed to the legacy method which uses brute-force
`k`	number of nearest neighbours to be returned
`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; longlat will override `kd_tree`
`use_kd_tree`	logical value, if the dbscan package is available, use for finding k nearest neighbours when longlat is FALSE, and when there are no identical points; from https://github.com/r-spatial/spdep/issues/38, the input data may have more than two columns if dbscan is used

Details

The underlying legacy C code is based on the knn function in the class package.

Value

A list of class knn

`nn`	integer matrix of region number ids
`np`	number of input points
`k`	input required k
`dimension`	number of columns of x
`x`	input coordinates

Author(s)

Roger Bivand Roger.Bivand@nhh.no

Examples

columbus <- st_read(system.file("shapes/columbus.shp", package="spData")[1], quiet=TRUE)
coords <- st_centroid(st_geometry(columbus), of_largest_polygon=TRUE)
col.knn <- knearneigh(coords, k=4)
plot(st_geometry(columbus), border="grey")
plot(knn2nb(col.knn), coords, add=TRUE)
title(main="K nearest neighbours, k = 4")
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,]
llk4.nb <- knn2nb(knearneigh(xy, k=4, longlat=FALSE))
gck4.nb <- knn2nb(knearneigh(xy, k=4, longlat=TRUE))
plot(llk4.nb, xy)
plot(diffnb(llk4.nb, gck4.nb), xy, add=TRUE, col="red", lty=2)
title(main="Differences between Euclidean and Great Circle k=4 neighbours")
summary(llk4.nb, xy, longlat=TRUE, scale=0.5)
summary(gck4.nb, xy, longlat=TRUE, scale=0.5)

xy1 <- SpatialPoints((as.data.frame(state.center))[m50.48,],
  proj4string=CRS("+proj=longlat +ellps=GRS80"))
gck4a.nb <- knn2nb(knearneigh(xy1, k=4))
summary(gck4a.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)
system.time(gck4a.nb <- knn2nb(knearneigh(xy1, k=4)))
summary(gck4a.nb, xy1, scale=0.5)
sf_use_s2(FALSE)
system.time(gck4a.nb <- knn2nb(knearneigh(xy1, k=4)))
summary(gck4a.nb, xy1, scale=0.5)
sf_use_s2(old_use_s2)

# https://github.com/r-spatial/spdep/issues/38
if (require("dbscan", quietly=TRUE)) {
  set.seed(1)
  x <- cbind(runif(50), runif(50), runif(50))
  out <- knearneigh(x, k=5)
  knn2nb(out)
  try(out <- knearneigh(rbind(x, x[1:10,]), k=5))
}

spdep

Spatial Dependence: Weighting Schemes, Statistics

v1.1-11

GPL (>= 2)

Authors

Roger Bivand [cre, aut] (<https://orcid.org/0000-0003-2392-6140>), Micah Altman [ctb], Luc Anselin [ctb], Renato Assunção [ctb], Olaf Berke [ctb], Andrew Bernat [ctb], Guillaume Blanchet [ctb], Eric Blankmeyer [ctb], Marilia Carvalho [ctb], Bjarke Christensen [ctb], Yongwan Chun [ctb], Carsten Dormann [ctb], Stéphane Dray [ctb], Virgilio Gómez-Rubio [ctb], Martin Gubri [ctb], Rein Halbersma [ctb], Elias Krainski [ctb], Pierre Legendre [ctb], Nicholas Lewin-Koh [ctb], Angela Li [ctb], Hongfei Li [ctb], Jielai Ma [ctb], Abhirup Mallik [ctb, trl], Giovanni Millo [ctb], Werner Mueller [ctb], Hisaji Ono [ctb], Pedro Peres-Neto [ctb], Gianfranco Piras [ctb], Markus Reder [ctb], Jeff Sauer [ctb], Michael Tiefelsdorf [ctb], René Westerholt [ctb], Levi Wolf [ctb], Danlin Yu [ctb]

Initial release

2021-09-07