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Classify GRaster cell values

Source: R/classify.r
classify.Rd

This function classifies a `GRaster“ so that cells that have values within a given range are assigned a new value. The subst() function is a simpler method for replacing specific values or category levels.

Usage

# S4 method for class 'GRaster'
classify(x, rcl, include.lowest = FALSE, right = TRUE, others = NULL)

Arguments

x

A GRaster.

rcl

Reclassification system:

  • A single integer: Number of "bins" into which to divide values. Arguments include.lowest and right apply.

  • A vector of numeric values: Breakpoints of bins into which to divide values. These will be sorted from lowest to highest before classification. Arguments include.lowest and right apply.

  • A 2-column matrix, data.frame, or data.table: The first column provides specific values in x to be replaced, and the second provides the values they are replaced with. This method is only useful for classifying integer GRasters. Arguments include.lowest and right are ignored. Cells will be classified in the order in which values are listed in the first column.

  • A 3-column matrix, data.frame, or data.table: The first column provides the lower value of a bin, the second the upper value, and the third the value to assign to the cells in the bin. Arguments include.lowest and right apply. Cells will be classified in the order of how intervals are listed (intervals will not be sorted).

include.lowest, right

Logical: These arguments determine how cells that have values exactly equal to the lower or upper ends of an interval are classified.

  • include.lowest = TRUE and right = TRUE: All intervals will be "left-open, right-closed" except for the lowest interval, which will be "left-closed/right-closed".

  • include.lowest = FALSE and right = FALSE: Intervals will be "left-closed/right-open". Cells with values equal to the highest higher boundary will not be reclassified.

  • include.lowest = TRUE and right = FALSE: All intervals will be "left-closed/right-open", except for the highest interval, which will be "right-closed/left-closed".

  • right = NA: Only useful for classifying integer GRasters. All intervals are "left-closed/right-closed". This is easier than accounting for "open" intervals when dealing with integers. Argument include.lowest is ignored.

others

Integer or NULL (default), or NA: Value to assign to cells that do not fall into the set intervals. Cells with NA values are not reclassified. Setting others equal to NULL or NA replaces all other values with NA. The value will be coerced to an integer value.

Value

A GRaster. The raster will be a categorical GRaster if the original values were continuous (i.e., a single- or double-precision raster), or of type "integer" if the input was an integer. See vignette("GRasters", package = "fasterRaster").

See also

terra::classify(), subst()

Examples

if (grassStarted()) {

# Setup
library(terra)

# Example data
madElev <- fastData("madElev")

# Convert a SpatRaster to a GRaster:
elev <- fast(madElev)

# Classify using a scalar indicating number of bins
scalar <- classify(elev, 5)
scalar
levels(scalar)

# Classify using a vector, indicating bin break points
vector <- classify(elev, rcl = c(0, 100, 200, 300, 400, 500, 600))
vector
levels(vector)

# Classify using a 2-column matrix (only valid for integer rasters)
rcl <- data.frame(is = c(1:3, 5, 10), becomes = c(100:102, 105, 110))
twoCol <- classify(elev, rcl = rcl)
twoCol

# Classify using a 3-column table
rcl <- data.frame(
   from = c(0, 100, 200, 300, 400, 500),
   to = c(100, 200, 300, 400, 500, 600),
   becomes = c(1, 2, 3, 10, 12, 15)
)
threeCol <- classify(elev, rcl = rcl)
threeCol
levels(threeCol)

# Convert all values outside range to NA (default)
rcl <- c(100, 200, 300)
v1 <- classify(elev, rcl = rcl)
v1
plot(v1)

# Convert all values outside range to -1
rcl <- c(100, 200, 300)
v2 <- classify(elev, rcl = rcl, others = -1)
v2
plot(v2)

### Left-open/right-closed (default)
minmax(elev) # note min/max values
rcl <- c(1, 200, 570)
v3 <- classify(elev, rcl = rcl, others = 10)
levels(v3)
plot(v3)

### Left-closed/right-open
minmax(elev) # note min/max values
rcl <- c(1, 200, 570)
v4 <- classify(elev, rcl = rcl, others = 10, right = FALSE)
levels(v4)

# Left-open except for lowest bin/right-closed
minmax(elev) # note min/max values
rcl <- c(1, 200, 570)
v5 <- classify(elev, rcl = rcl, others = 10, include.lowest = TRUE)
v5 <- droplevels(v5)
levels(v5)

# Left-closed/right-open except for highest bin
minmax(elev) # note min/max values
rcl <- c(1, 200, 570)
v6 <- classify(elev, rcl = rcl, others = 10,
   right = FALSE, include.lowest = TRUE)
v6 <- droplevels(v6)
levels(v6)

}