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Change the coordinate reference system of a GRaster or GVector

Source: R/project.r
project.Rd

project() changes the coordinate reference system (CRS) of a GRaster or GVector. It has three use cases:

  • x is a GRaster and y is a GRaster: x will be projected to the CRS of y and resampled to have the same resolution as y. If argument align is FALSE, then it will also be cropped to the extent of y.

  • x is a GRaster and y is a GVector or a CRS string (typically in Well-Known Text format): x will be projected to the CRS specified by y and resampled but not cropped.

  • x is a GVector and y is a GRaster, GVector, or CRS string: The vector will be projected to the CRS of y.

Usage

# S4 method for class 'GRaster'
project(
  x,
  y,
  align = FALSE,
  method = NULL,
  fallback = TRUE,
  res = "fallback",
  wrap = FALSE,
  verbose = FALSE
)

# S4 method for class 'GVector'
project(x, y, wrap = FALSE)

Arguments

x

A GRaster or GVector to be projected.

y

A character or GLocation object (i.e., typically a GRaster or GVector): Used to set the focal GRaster or GVector's new CRS (and resolution and possibly extent, for GRasters).

align

Logical: If FALSE (default), and x and y are GRasters, then the extent of x will be cropped to the extent of y. If TRUE, no cropping is performed.

method

Character or NULL (for GRasters only): Method to use to conduct the transformation (rasters only). Partial matching is used.

  • NULL (default): Automatically choose based on raster properties (near for categorical data, bilinear for continuous data).

  • "near": Nearest neighbor. Best for categorical data, and often a poor choice for continuous data. If datatype() is integer, this method will be used by default.

  • "bilinear": Bilinear interpolation (default for non-categorical data; uses weighted values from 4 cells).

  • "bicubic": Bicubic interpolation (uses weighted values from 16 cells).

  • "lanczos": Lanczos interpolation (uses weighted values from 25 cells).

Note #1: If x and y are GRasters, and res = "terra", then the same method is used to resample x to the resolution of y before projecting x.

Note #2: Methods that use multiple cells will cause the focal cell to become NA if there is at least one cell with an NA in the cells it draws from. These NA cells can often be filled using the fallback argument.

fallback

Logical (for projecting GRasters only): If TRUE (default), then use "lower" resampling methods to fill in NA cells when a "higher" resampling method is used. For example, if method = "bicubic", NA cells will be filled in using the bilinear method, except when that results in NAs, in which case the near method will be used. Fallback causes fewer cells to revert to NA values, so may be better at capturing complex "edges" (e.g., coastlines). Fallback does increase processing time because each "lower" method must be applied, then results merged. Fallback is not used if method = "near".

res

Character (for projecting GRasters only): Method used to set the resolution of a GRaster in the new CRS. This can be one of three options. Partial matching is used and case ignored:

  • "terra": This method creates an output raster that is as close as possible in values and resolution to the one that terra::project() would create. However, for large rasters (i.e., many cells), this can fail because terra::project() encounters memory limits (it is used internally to create a template). This method resamples the focal raster in its starting CRS, then projects it to the destination CRS.

  • "template": This method can only be used if y is a GRaster. The output will have the same resolution as y and possibly the same extent (depending on the value of align). However, unlike the "terra" method, cell values will not necessarily be as close as possible to what terra::project() would generate (unless method = "near"). Unlike the "terra" method, this method does not resample the focal raster in its starting CRS before projecting. For large rasters it will be faster than the "terra" method (especially if "method = "near"), and it should be less likely to fail because of memory limits.

  • Two numeric values: Values for the new resolution (x- and y-dimensions).

  • "center": This method locates the centroid of the raster to be projected (in the same CRS as the original raster). It then creates four points north, south, east, and west of the centroid, each spaced one cell's width from the centroid. This set of points is then projected to the new CRS. The new cell size in the x-dimension will be the average of the distance between the east and west points from the centroid, and in the y-dimension the average from the centroid to the north and south points.

  • "fallback" (default): This applies the terra method first, but if that fails, then tries template, then center. This process can take a long time for large rasters.

wrap

Logical:

  • GRasters: When projecting rasters that "wrap around" (i.e., whole-world rasters or rasters that have edges that actually circle around to meet on the globe), wrap should be TRUE to avoid removing rows and columns from the "edge" of the map. The default is FALSE.

  • GVectors: When projecting vectors that span the international date line at 180E/W, wrap should be TRUE to avoid an issue where the coordinates are incorrectly mapped to the range -180 to 180.

verbose

Logical (for projecting GRasters only): If TRUE, display progress. Default is FALSE.

Value

A GRaster or GVector.

Details

When projecting a raster, the "fallback" methods in GRASS module r.import are actually used, even though the method argument takes the strings specifying non-fallback methods. See the manual page for the r.import GRASS module.

See also

terra::project(), sf::st_transform(), modules r.proj, r.import, and v.proj in GRASS

Examples

if (grassStarted()) {

### Setup for all examples
##########################

library(sf)
library(terra)

# Climate raster, elevation raster, rivers vector
madElev <- fastData("madElev")
madRivers <- fastData("madRivers")
madChelsa <- fastData("madChelsa")

# Convert objects into fasterRaster formats
chelsa <- fast(madChelsa)
elev <- fast(madElev)
rivers <- fast(madRivers)

### Project raster without resampling
elevWGS84 <- project(elev, crs(chelsa))
elevWGS84

### Project raster and resample to resolution of another raster
elevWGS84Resamp <- project(elev, chelsa)
elevWGS84Resamp

res(elevWGS84)
res(elevWGS84Resamp)
res(chelsa)

### Project vector
riversWGS84 <- project(rivers, chelsa)
riversWGS84
cat(crs(rivers)) # using "cat()" to make it look nice
cat(crs(riversWGS84))

}