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Identify polygon neighbors

Source: R/neighbors.R
st_contiguity.Rd

Given an sf geometry of type POLYGON or MULTIPOLYGON identify contiguity based neighbors.

Usage

st_contiguity(geometry, queen = TRUE, ...)

Arguments

geometry

an sf or sfc object.

queen

default TRUE. For more see ?spdep::poly2nb

...

additional arguments passed to spdep::poly2nb()

Value

a list of class nb

Details

Utilizes spdep::poly2nb()

See also

Other neighbors: st_dist_band(), st_knn()

Examples

# on basic polygons
geo <- sf::st_geometry(guerry)
st_contiguity(geo)
#> Neighbour list object:
#> Number of regions: 85 
#> Number of nonzero links: 420 
#> Percentage nonzero weights: 5.813149 
#> Average number of links: 4.941176 

# in a pipe
library(magrittr)
guerry %>%
  dplyr::mutate(nb = st_contiguity(geometry), .before = 1)
#> Simple feature collection with 85 features and 27 fields
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 47680 ymin: 1703258 xmax: 1031401 ymax: 2677441
#> CRS:           NA
#> # A tibble: 85 × 28
#>    nb        code_d…¹ count ave_i…²  dept region depar…³ crime…⁴ crime…⁵ liter…⁶
#>  * <nb>      <fct>    <dbl>   <dbl> <int> <fct>  <fct>     <int>   <int>   <int>
#>  1 <int [4]> 01           1      49     1 E      Ain       28870   15890      37
#>  2 <int [6]> 02           1     812     2 N      Aisne     26226    5521      51
#>  3 <int [6]> 03           1    1418     3 C      Allier    26747    7925      13
#>  4 <int [4]> 04           1    1603     4 E      Basses…   12935    7289      46
#>  5 <int [3]> 05           1    1802     5 E      Hautes…   17488    8174      69
#>  6 <int [7]> 07           1    2249     7 S      Ardeche    9474   10263      27
#>  7 <int [3]> 08           1   35395     8 N      Ardenn…   35203    8847      67
#>  8 <int [3]> 09           1    2526     9 S      Ariege     6173    9597      18
#>  9 <int [5]> 10           1   34410    10 E      Aube      19602    4086      59
#> 10 <int [5]> 11           1    2807    11 S      Aude      15647   10431      34
#> # … with 75 more rows, 18 more variables: donations <int>, infants <int>,
#> #   suicides <int>, main_city <ord>, wealth <int>, commerce <int>,
#> #   clergy <int>, crime_parents <int>, infanticide <int>,
#> #   donation_clergy <int>, lottery <int>, desertion <int>, instruction <int>,
#> #   prostitutes <int>, distance <dbl>, area <int>, pop1831 <dbl>,
#> #   geometry <MULTIPOLYGON>, and abbreviated variable names ¹​code_dept,
#> #   ²​ave_id_geo, ³​department, ⁴​crime_pers, ⁵​crime_prop, ⁶​literacy
#> # ℹ Use `print(n = ...)` to see more rows, and `colnames()` to see all variable names