adjacency_matrix: Adjacency matrix

In prioritizr: Systematic Conservation Prioritization in R

Adjacency matrix

Description

Create a matrix showing which planning units are spatially adjacent to each other.

Usage

adjacency_matrix(x, ...)

## S3 method for class 'Raster'
adjacency_matrix(x, directions = 4, ...)

## S3 method for class 'SpatRaster'
adjacency_matrix(x, directions = 4, ...)

## S3 method for class 'SpatialPolygons'
adjacency_matrix(x, ...)

## S3 method for class 'SpatialLines'
adjacency_matrix(x, ...)

## S3 method for class 'SpatialPoints'
adjacency_matrix(x, ...)

## S3 method for class 'sf'
adjacency_matrix(x, ...)

## Default S3 method:
adjacency_matrix(x, ...)

Arguments

x	terra::rast() or sf::sf() object representing planning units.
...	not used.
directions	integer If x is a terra::rast() object, the number of directions in which cells should be considered adjacent: 4 (rook's case), 8 (queen's case), 16 (knight and one-cell queen moves), or "bishop" to for cells with one-cell diagonal moves.

Details

Spatial processing is completed using sf::st_intersects() for sf::sf() objects, and terra::adjacent() for terra::rast() objects. Note that spatially overlapping planning units are considered adjacent.

Value

A dsCMatrix sparse symmetric matrix. Each row and column represents a planning unit. Cells values indicate if different planning units are adjacent to each other or not (using ones and zeros). To reduce computational burden, cells among the matrix diagonal are set to zero. Furthermore, if the argument to x is a terra::rast() object, then cells with NA values are set to zero too.

Notes

In earlier versions (< 5.0.0), this function was named as the connected_matrix function. It has been renamed to be consistent with other spatial association matrix functions.

Examples

## Not run: 
# load data
sim_pu_raster <- get_sim_pu_raster()
sim_pu_polygons <- get_sim_pu_polygons()

# create adjacency matrix using raster data
## crop raster to 9 cells
r <- terra::crop(sim_pu_raster, terra::ext(c(0, 0.3, 0, 0.3)))

## make adjacency matrix
am_raster <- adjacency_matrix(r)

# create adjacency matrix using polygon data
## subset 9 polygons
ply <- sim_pu_polygons[c(1:3, 11:13, 20:22), ]

## make adjacency matrix
am_ply <- adjacency_matrix(ply)

# plot data and the adjacency matrices

## plot raster and adjacency matrix
plot(r, main = "raster", axes = FALSE)
Matrix::image(am_raster, main = "adjacency matrix")

## plot polygons and adjacency matrix
plot(ply[, 1], main = "polygons")
Matrix::image(am_ply, main = "adjacency matrix")


## End(Not run)

prioritizr documentation built on Aug. 9, 2023, 1:06 a.m.