Constructs spatial weights (neighborhood structure) from sf geometries. Wraps spdep functions with a convenient interface.
Usage
sp_weights(
data,
type = c("queen", "rook", "knn", "distance"),
k = NULL,
d = NULL,
...
)Arguments
- data
An sf object with polygon or point geometries.
- type
Type of weights. One of:
"queen" (default): Polygons sharing any boundary point are neighbors
"rook": Polygons sharing an edge are neighbors
"knn": K-nearest neighbors based on centroid distance
"distance": All units within a distance threshold are neighbors
- k
Number of nearest neighbors. Required when
type = "knn".- d
Distance threshold. Required when
type = "distance". Units match the CRS of the data (e.g., meters for projected CRS).- ...
Additional arguments passed to spdep functions.
Details
Choosing a weight type:
Use queen/rook for polygon data where physical adjacency matters
Use knn when you need guaranteed connectivity (no isolates) or for point data
Use distance for point data or when interaction depends on proximity
KNN weights always produce a connected graph (if k >= 1), making them useful for datasets with islands or disconnected polygons.
Examples
if (FALSE) { # \dontrun{
library(sf)
nc <- st_read(system.file("shape/nc.shp", package = "sf"))
# Queen contiguity (default)
w_queen <- sp_weights(nc, type = "queen")
# K-nearest neighbors (guarantees connectivity)
w_knn <- sp_weights(nc, type = "knn", k = 6)
# Distance-based (e.g., 50km for projected data)
nc_proj <- st_transform(nc, 32119) # NC State Plane
w_dist <- sp_weights(nc_proj, type = "distance", d = 50000)
} # }