Visualising Neighbourhood Weights

vis_nb_wghts_sf.R

library(sp)
library(spdep)
library(tidyverse)
library(sf)

data(meuse)

nb.boundary.radius <- 750

nb.obj <- dnearneigh(x = select(meuse, x, y) %>% as.matrix(), d1 = 0, d2 = nb.boundary.radius, row.names = NULL, longlat = NULL, bounds=c("GT", "LE"))

nb.lstw <- nb2listw(neighbours = nb.obj, zero.policy = TRUE)

nb.dsts <- nbdists(nb = nb.obj, coords = select(meuse, x, y) %>% as.matrix())

# borrowed directly from the `spdep` docs:

inv.dst.weights <- lapply(nb.dsts, function(x) 1/(x/1e3))

inv.dst.lstw <- nb2listw(neighbours = nb.obj, glist = inv.dst.weights, style = 'B', zero.policy = TRUE)

ID.nb.spldf <- listw2lines(listw = inv.dst.lstw, coords = select(meuse, x, y) %>% as.matrix())

ID.nb.sf <- st_as_sf(x = ID.nb.spldf)

ggplot() + 
  geom_sf(data = ID.nb.sf %>% arrange(wt), aes(col = wt)) + 
  scale_colour_continuous(type = 'viridis', direction = -1) + 
  theme_bw() + 
  labs(colour = 'weight')