connected.pixels: Connected Components Labelling

In jeffreyevans/landmetrics: Legacy landscape metrics from spatialEco

Connected Components Labelling

Description

Unique Patch Labelling using Connected Components

Usage

connected.pixels(mat)

Arguments

mat	is a binary matrix of data with 0 representing background and 1 representing environment of interest. NA values are acceptable. The matrix can be a raster of class 'asc' (this & adehabitat package), 'RasterLayer' (raster package) or 'SpatialGridDataFrame' (sp package)

Value

A matrix of the same dim and class of mat in which unique components (individual patches) are numbered 1:n with 0 remaining background value.

Note

connected.pixels is a 1 pass implementation of connected components labelling. Here it is applied to identify disjunct patches within a distribution. The raster matrix can be a raster of class 'asc' (adehabitat package), 'RasterLayer' (raster package) or 'SpatialGridDataFrame' (sp package).

Author(s)

Jeremy VanDerWal (depreciated/orphaned SDMTools package) and Jeffrey S. Evans

References

Chang, F., C.J. Chen, and C.J. Lu. 2004. A linear-time component-labeling algorithm using contour tracing technique. Comput. Vis. Image Underst. 93:206-220.

Examples

library(raster)
library(sp)
#define a simple binary matrix
tmat = { matrix(c( 0,0,0,1,0,0,1,1,0,1,
                   0,0,1,0,1,0,0,0,0,0,
                   0,1,NA,1,0,1,0,0,0,1,
                   1,0,1,1,1,0,1,0,0,1,
                   0,1,0,1,0,1,0,0,0,1,
                   0,0,1,0,1,0,0,1,1,0,
                   1,0,0,1,0,0,1,0,0,1,
                   0,1,0,0,0,1,0,0,0,1,
                   0,0,1,1,1,0,0,0,0,1,
                   1,1,1,0,0,0,0,0,0,1),nr=10,byrow=TRUE) }
					
# perform connected component labelling
( ccl.mat = connected.pixels(tmat) )
image(t(ccl.mat[10:1,]),col=c('grey',rainbow(length(unique(ccl.mat))-1)))

jeffreyevans/landmetrics documentation built on Nov. 14, 2023, 3:13 p.m.