Learn R Programming

raster (version 3.4-5)

crop: Crop

Description

crop returns a geographic subset of an object as specified by an Extent object (or object from which an extent object can be extracted/created). If x is a Raster* object, the Extent is aligned to x. Areas included in y but outside the extent of x are ignored (see extend if you want a larger area).

Usage

# S4 method for Raster
crop(x, y, filename="", snap='near', datatype=NULL, ...)

# S4 method for Spatial crop(x, y, ...)

Arguments

x

Raster* object or SpatialPolygons*, SpatialLines*, or SpatialPoints* object

y

Extent object, or any object from which an Extent object can be extracted (see Details)

filename

Character, output filename. Optional

snap

Character. One of 'near', 'in', or 'out', for use with alignExtent

datatype

Character. Output dataType (by default it is the same as the input datatype)

...

Additional arguments as for writeRaster

Value

RasterLayer or RasterBrick object; or SpatialLines or SpatialPolygons object.

Details

Objects from which an Extent can be extracted/created include RasterLayer, RasterStack, RasterBrick and objects of the Spatial* classes from the sp package. You can check this with the extent function. New Extent objects can be also be created with function extent and drawExtent by clicking twice on a plot.

To crop by row and column numbers you can create an extent like this (for Raster x, row 5 to 10, column 7 to 12) crop(x, extent(x, 5, 10, 7, 15))

See Also

extend, merge

Examples

Run this code
# NOT RUN {
r <- raster(nrow=45, ncol=90)
values(r) <- 1:ncell(r)
e <- extent(-160, 10, 30, 60)
rc <- crop(r, e)	

# use row and column numbers:
rc2 <- crop(r, extent(r, 5, 10, 7, 15))

# crop Raster* with Spatial* object
b <- as(extent(6, 6.4, 49.75, 50), 'SpatialPolygons')
crs(b) <- crs(r)
rb <- crop(r, b)

# crop a SpatialPolygon* object with another one
if (require(rgdal) & require(rgeos)) {
  p <- shapefile(system.file("external/lux.shp", package="raster"))
  pb <- crop(p, b)
}
# }

Run the code above in your browser using DataLab