I am aware that there are similar questions and problems around but mine is very specific.
I'm working with the WorldClim and Chelsa Climate data sets in 30 arc-second resolution. In the process I want to put the specific datasets into a ncdf4 file. In the process the data must be converted into a vector to be casted into a matrix. This matrix is then reverst and in the end transponed. The output data is than casted into a array to be later put into the ncdf-file.
My example code looks like this.
library(raster)
library(ncdf4)
# Download of one of the raster files (here 110 Mb .tif-Raster from the Chelsa server)
temp.raster <- raster("https://envidatrepo.wsl.ch/uploads/chelsa/chelsa_V1/bioclim/integer/CHELSA_bio10_08.tif")
#determining the cellsize
cellsize <- (temp.raster@[email protected]@extent@xmin)/temp.raster@ncols
# Set Longitudes
lon <- as.array(seq(temp.raster@extent@xmin+cellsize/2,
temp.raster@extent@xmax-cellsize/2,
(temp.raster@[email protected]@extent@xmin)/temp.raster@ncols))
nlon <- length(lon)
# Set Latitudes
lat <- as.array(seq(temp.raster@extent@ymin+cellsize/2,
temp.raster@extent@ymax-cellsize/2,
(temp.raster@[email protected]@extent@xmin)/temp.raster@ncols))
nlat <- length(lat)
temp.raster.data <- t(apply(matrix(data = as.numeric(values(temp.raster)),
nrow = nlat,
ncol = nlon,
byrow = TRUE),
2,
rev))
temp.raster.data <- array(temp.raster.data, dim=c(nlon,nlat,1))
The error occurs at the values()-function in the process of extracting the values out of the raster file.
Setting a higher memory limit as suggested in other questions did not work, and adding more RAM is not an option.
Has someone a suggestion of a workaround or even simpler solution to this problem?
My sessionInfo() is
R version 4.0.2 (2020-06-22)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18363)
With 12 GB of RAM (memory.limit() --> 11984)
Thank you for your time!
A simpler way would be to use writeRaster
f <- "https://envidatrepo.wsl.ch/uploads/chelsa/chelsa_V1/bioclim/integer/CHELSA_bio10_08.tif"
bf <- basename(f)
download.file(f, bf, mode="wb")
library(raster)
r <- raster(bf)
ncfile <- gsub(".tif", ".nc", bf)
x <- writeRaster(r, ncfile)
Also you are reinventing the wheel a lot; consider the below.
#determining the cellsize
cellsize <- res(r)
# Lon/lat
lon <- xFromCol(r, 1:ncol(r))
lat <- yFromRow(r, 1:nrow(r))