k_means: k_means

In rspatial/terra: Spatial Data Analysis

k_means

Description

Compute k-means clusters for a SpatRaster. For large SpatRasters (with ncell(x) > maxcell) this is done in two steps. First a sample of the cells is used to compute the cluster centers. Then each cell is assigned to a cluster by computing the distance to these centers.

Usage

## S4 method for signature 'SpatRaster'
k_means(x, centers=3, ..., maxcell=1000000, filename="", overwrite=FALSE, wopt=list())

Arguments

x	SpatRaster
centers	either the number of clusters, or a set of initial (distinct) cluster centres. If a number, a random set of (distinct) cells in x is chosen as the initial centres
...	additional arguments passed to kmeans
maxcell	positive integer. The size of the regular sample used if it is smaller than ncell(x)
filename	character. Output filename (ignored if as.raster=FALSE)
overwrite	logical. If TRUE, filename is overwritten
wopt	list with additional arguments for writing files as in writeRaster

Value

SpatRaster

See Also

kmeans

Examples

f <- system.file("ex/logo.tif", package = "terra")
r <- rast(f)
km <- k_means(r, centers=5)
km

rspatial/terra documentation built on Nov. 5, 2024, 5:13 p.m.