gdalProject is a thin wrapper around sf::gdal_utils('gdalwarp', ...) with specific options set, notably, -r to method (in the ...), -t_srs to the crs of the toRas, -te to the extent of the toRas, -te_srs to the crs of the toRas, -dstnodata = NA, and -overwrite.

gdalResample is a thin wrapper around sf::gdal_utils('gdalwarp', ...) with specific options set, notably, "-r", "near", -te, -te_srs, tr, -dstnodata = NA, -overwrite.

gdalMask is a thin wrapper around sf::gdal_utils('gdalwarp', ...) with specific options set, notably, -cutline, -dstnodata = NA, and -overwrite.

gdalProject(
  fromRas,
  toRas,
  filenameDest,
  verbose = getOption("reproducible.verbose"),
  ...
)

gdalResample(
  fromRas,
  toRas,
  filenameDest,
  verbose = getOption("reproducible.verbose"),
  ...
)

gdalMask(
  fromRas,
  maskToVect,
  writeTo = NULL,
  verbose = getOption("reproducible.verbose"),
  ...
)

Arguments

fromRas

see from argument from postProcessTo(), but can only be a SpatRaster.

toRas

see to argument from postProcessTo(), but can only be a SpatRaster.

filenameDest

A filename with an appropriate extension (e.g., .tif) for gdal to write the output to. Since this function is conceived to be part of a chain, and not the final step, this function does not use writeTo, which is reserved for the final step in the chain.

verbose

Numeric, -1 silent (where possible), 0 being very quiet, 1 showing more messaging, 2 being more messaging, etc. Default is 1. Above 3 will output much more information about the internals of Caching, which may help diagnose Caching challenges. Can set globally with an option, e.g., options('reproducible.verbose' = 0) to reduce to minimal

...

For gdalProject, this can be method. For gdalMask can be destinationPath and touches. For all gdal*, this can also be and datatype.

maskToVect

see maskTo argument from maskTo(), but can only be a SpatVector

writeTo

Optional character string of a filename to use writeRaster to save the final object. Default is NULL, which means there is no writeRaster

Details

These three functions are used within postProcessTo, in the sequence: gdalProject, gdalResample and gdalMask, when from and projectTo are SpatRaster and maskTo is a SpatVector, but only if options(reproducible.gdalwarp = TRUE) is set.

This sequence is a slightly different order than the sequence when gdalwarp = FALSE or the arguments do not match the above. This sequence was determined to be faster and more accurate than any other sequence, including running all three steps in one gdalwarp call (which gdalwarp can do). Using one-step gdalwarp resulted in very coarse pixelation when converting from a coarse resolution to fine resolution, which visually was inappropriate in test cases.

See also

gdalResample(), and gdalMask() and the overarching postProcessTo()

Examples

# prepare dummy data -- 3 SpatRasters, 2 SpatVectors
# need 2 SpatRaster
rf <- system.file("ex/elev.tif", package = "terra")
elev1 <- terra::rast(rf)
#'
ras2 <- terra::deepcopy(elev1)
ras2[ras2 > 200 & ras2 < 300] <- NA_integer_
terra::values(elev1) <- rep(1L, terra::ncell(ras2))
#'
# a polygon vector
f <- system.file("ex/lux.shp", package = "terra")
vOrig <- terra::vect(f)
v <- vOrig[1:2, ]
#'
utm <- terra::crs("epsg:23028") # $wkt
vInUTM <- terra::project(vOrig, utm)
vAsRasInLongLat <- terra::rast(vOrig, resolution = 0.008333333)
res100 <- 100
rInUTM <- terra::rast(vInUTM, resolution = res100, vals = 1)
# crop, reproject, mask, crop a raster with a vector in a different projection
#  --> gives message about not enough information
t1 <- postProcessTo(elev1, to = vInUTM)
#> Running `postProcessTo`
#> cropping...
#> projecting...
#> 
#> projectTo is a Vector dataset, which does not define all metadata required.
#>  Using the origin and extent from `ext(from)` in the projection from
#>    `crs(projectTo)`.
#>  If this is not correct, create a template gridded object and pass that to
#>    `projectTo`...
#> 
#> done! took:  0.528 secs
#> masking...
#> done! took:  0.0363 secs
#> cropping...
#> done! took:  0.0404 secs
#> postProcessTo done! took:  0.691 secs
# crop, reproject, mask a raster to a different projection, then mask
t2a <- postProcessTo(elev1, to = vAsRasInLongLat, maskTo = vInUTM)
#> Running `postProcessTo`
#> Try setting options('reproducible.gdalwarp' = TRUE) to use a different, possibly faster, algorithm
#> cropping...
#> projecting...
#> done! took:  0.0279 secs
#> masking...
#> done! took:  0.0108 secs
#> cropping...
#> done! took:  0.0113 secs
#> postProcessTo done! took:  0.104 secs


# using gdal directly --> slightly different mask
opts <- options(reproducible.gdalwarp = TRUE)
t2b <- postProcessTo(elev1, to = vAsRasInLongLat, maskTo = vInUTM)
#> Running `postProcessTo`
#> using sf::gdal_utils('warp') because options("reproducible.gdalwarp" = TRUE) ...
#> running gdalProject ...
#> done! took:  0.023 secs
#> running gdalResample ...
#> done! took:  0.216 secs
#> running gdalMask ...
#> done! took:  0.0405 secs
#> postProcessTo done! took:  0.283 secs
t3b <- postProcessTo(elev1, to = rInUTM, maskTo = vInUTM)
#> Running `postProcessTo`
#> using sf::gdal_utils('warp') because options("reproducible.gdalwarp" = TRUE) ...
#> running gdalProject ...
#> done! took:  0.0459 secs
#> running gdalResample ...
#> done! took:  0.0317 secs
#> running gdalMask ...
#> done! took:  0.109 secs
#> postProcessTo done! took:  0.19 secs
options(opts)