Comment changer la résolution d'une couche raster dans la R

Voici un exemple de comment faire cela. (lien vers l'original)

  #########################################################################
# SubsampleImageRaster.r
#  
# This function demonstrates resampling of raster images to a new
# spatial resolution using the R raster package.
# 
# Author: Rick Reeves
# Date created: 6-October- 2010
# Date modified:                                                             
# NCEAS
#
#########################################################################
#
SubsampleImageRaster <- function()
{
library(raster)
sOutFile <- ""
resampleFactor <- 4  # For test, subsample incoming image by factor of 10
# Read the mosaic components, stored in a subfolder, into a raster object list.
# Within the same loop, obtain the (geographic) extent of each component.
# Note: these images do not have same spatial extent, so they cant be stored
# in a rasterStack. Instead, use a list of rasterLayers.
setwd("./ForUseCase")
inFiles <- list.files(pattern="*.tif")
nFiles <-  length(inFiles)
inputRaster <- raster()
CoarseResampRaster <- raster()   
FineResampRaster <- raster()   
for (iCtr in 1 : nFiles)
{
message(sprintf("resampling file: %s",inFiles[iCtr]))
inputRaster <- raster(inFiles[iCtr])
# The aggregate() /disaggregate methods resample rasters to COARSER (bigger cells)
# and FINER (smaller cells) resolutions, respectively
CoarseResampRaster <- aggregate(inputRaster,fact=resampleFactor,fun=mean) 
sOutFile <- sprintf("CoarseSubsamp%s",inFiles[iCtr]) 
writeRaster(CoarseResampRaster,filename=sOutFile,format="GTiff",datatype="INT1U",overwrite=TRUE)      
FineResampRaster <- disaggregate(inputRaster,fact=resampleFactor,fun=mean) 
sOutFile <- sprintf("FineSubsamp%s",inFiles[iCtr]) 
writeRaster(FineResampRaster,filename=sOutFile,format="GTiff",datatype="INT1U",overwrite=TRUE)            
}   
message("resample demo")
browser()
# second method: use the resample() method from raster package
# Simple example:
# This code produces a resampled raster, 's',
# with correct resampled values. e.g.; 
# s[] prints a vector of resampled cell values.
r <- raster(nrow=3, ncol=3)
r[] <- 1:ncell(r)
s <- raster(nrow=10, ncol=10)
s <- resample(r, s, method='bilinear')
# Useful example:
# Resample a satellite image, stored in a GeoTiff file
# into a NEW raster with 2x spatial resolution in 
# both dimensions (four times the number of cells)
# Here is the technique: 
#  1) Create a new raster object with the correct 'resampled' number of cells.
#  2) Set the extent (geographic 'bounding box') of the new raster 
#     to the extent of the original raster
#  3) Generate the resampled raster.
resampleFactor <- .5  # reduce the cell size by 50% and double the number of rows and columns.      
inputRaster <- raster("TmB50MosaicImg1.tif")      
inCols <- ncol(inputRaster)
inRows <- nrow(inputRaster)
resampledRaster <- raster(ncol=(inCols / resampleFactor), nrow=(inRows / resampleFactor))
extent(resampledRaster) <- extent(inputRaster)
# The resample method will write the resampled raster image to a NEW disk file..
resampledRaster <- resample(inputRaster,resampledRaster,datatype="INT1U",method='bilinear',filename="testOutResamp.tif",overwrite=TRUE)
# Or, use writeRaster method to create the output file.
writeRaster(resampledRaster,filename="ResampleProduct.tif",format="GTiff",datatype="INT1U",overwrite=TRUE)   
# end
}

J'ai eu récemment une exigence de réduire la résolution d'un ggmap objet. Cela implique l'extraction et la transformation de la ggmap raster (à l'aide de Robin Lovelace est ggmap_rast()), l'agrégation du raster comme expliqué dans ce fil, puis en remplaçant les ggmap haute résolution raster avec la plus faible résolution raster ci-dessous. Espérons que cela est utile:

original_map <- get_map("New York", scale = 1) #download a map at lowest resolution
#ggmap_rast function courtesy of Robin Lovelace
original_map.rast1 <- ggmap_rast(original_map) #extract RasterStack from ggmap object
original_map.rast2 <- aggregate(original_map.rast, 2) #compress raster
rast2_length <- sqrt(length(original_map.rast2)/3)  ## find the number of cells in compressed raster
map <- ggmap::ggmap(original_map) 
# from https://stackoverflow.com/questions/44225063/plot-ggmap-image-over-raster
r <- map$layers[[2]]$geom_params$raster #pull hex raster pixel values from ggmap object
#x <- r[,] #assign values to a variable (probably unnecessary)
xx <- r[1:rast2_length,1:rast2_length] #filler values for raster to be created
rgb_map <- original_map.rast2
for(i in 1:rast2_length){
for(j in 1:rast2_length){
k=i*rast2_length+j
#many rgv values are non-integers; rgb2hex requires integer
red = as.integer(round(rgb_map$layer.1[k],0))
green = as.integer(round(rgb_map$layer.2[k],0))
blue = as.integer(round(rgb_map$layer.3[k],0))
#rgb2hex from ggtern package
xx[i,j] <- rgb2hex(red,green,blue)
#rgb2hex is slow; export, calculate in excel, import is faster, sadly
#xx[i,j] <- as.character(rgb_from_excel$V1[k])
}
}
map$layers[[2]]$geom_params$raster <- xx
map