Learn R Programming

raster (version 2.5-8)

reclassify: Reclassify

Description

Reclassify values of a Raster* object. The function (re)classifies groups of values to other values. For example, all values between 1 and 10 become 1, and all values between 11 and 15 become 2 (see functions subs and cut for alternative approaches).

Reclassification is done with matrix rcl, in the row order of the reclassify table. Thus, if there are overlapping ranges, the first time a number is within a range determines the reclassification value.

Usage

# S4 method for Raster
reclassify(x, rcl, filename='', include.lowest=FALSE, right=TRUE, ...)

Arguments

x

Raster* object

rcl

matrix for reclassification. This matrix must have 3 columns. The first two columns are "from" "to" of the input values, and the third column "becomes" has the new value for that range. (You can also supply a vector that can be coerced into a n*3 matrix (with byrow=TRUE)). You can also provide a two column matrix ("is", "becomes") which can be useful for integer values. In that case, the right argument is automatically set to NA

filename

character. Output filename (optional)

include.lowest

logical, indicating if a value equal to the lowest value in rcl (or highest value in the second column, for right = FALSE) should be included. The default is FALSE

right

logical, indicating if the intervals should be closed on the right (and open on the left) or vice versa. The default is TRUE. A special case is to use right=NA. In this case both the left and right intervals are open

...

additional arguments as for writeRaster

Value

Raster* object

See Also

subs, cut, calc

Examples

Run this code
# NOT RUN {
r <- raster(ncols=36, nrows=18)
r[] <- runif(ncell(r)) 
# reclassify the values into three groups 
# all values >= 0 and <= 0.25 become 1, etc.
m <- c(0, 0.25, 1,  0.25, 0.5, 2,  0.5, 1, 3)
rclmat <- matrix(m, ncol=3, byrow=TRUE)
rc <- reclassify(r, rclmat)

# equivalent to
rc <- reclassify(r, c(-Inf,0.25,1, 0.25,0.5,2, 0.5,Inf,3))
# }

Run the code above in your browser using DataLab