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我有大量的栅格（ASCII 文件），我想： 1. 从 Lamberts Equal area 重新投影到 WGS 84 2. 将生成的 WGS 84 栅格裁剪到一定程度 3. 将生成的栅格写入目录

我知道堆叠栅格和重新投影会遇到内存问题。因此，我尝试了一个 for 循环，该循环遍历每个光栅，重新投影作物并将其保存到输出目录。即便如此，我也遇到了内存问题。如果我只是裁剪和掩盖栅格，代码工作得非常快，当我想重新投影时会出现问题。这是我的代码

library(raster)
library(doParallel)
library(rgdal)

#Define how many cores you want to use
UseCores <- detectCores()-1

#Register CoreCluster
cl       <- makeCluster (UseCores)
registerDoParallel (cl)

# Start the clock!
ptm <- proc.time ()

# Reading the shapefile (mask to crop later)
Maskshp  <- readOGR("G:/PhD BOKU/DATA/GIS Data/austria","AUT0")

# Name the output path and creat a directory to store the final results
outpath <- "C:/Users/chakraborty/Desktop/cropdata/"
dir.create(outpath)


# Reading the raster to crop
setwd("C:/Users/chakraborty/Desktop/MPI_rcp85_2080s_Bioclimatic")

files <- list.files(pattern=".tif") 

# add the output directory
outfiles <- paste0(outpath, files)

for(i in 1:length(files)) {
    r <-raster(files[i])
    projection(r)<- CRS("+proj=aea +lat_1=43 +lat_2=62 +lat_0=30 +lon_0=15 +x_0=0 +y_0=0 +ellps=intl 
    +units=m +no_defs")
    newproj <- CRS("+proj=longlat +ellps=WGS84 +towgs84=0,0,0,0,0,0,0 +no_defs")
    rWGS <-  projectRaster(r, crs= newproj,res= 0.008333334)
    rc <- crop(rWGS, Maskshp)
    rc1 <- mask(rc,Maskshp)
    rc1 <- writeRaster(rc1, outfiles[i],format="GTiff")
}

#end cluster
stopCluster (cl)

# Stop the clock
proc.time() -ptm

# Takes 102 seconds to crop and write 20 rasters from Europe to Austrian Extent
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