First some context: I want to run a time-series analysis function that is only available in R for a continental sized multi-band time-series raster, which is stored in disk in GeoTIFF format, that was created translating a VRT file to a GeoTIFF with GDAL using parameter
INTERLEAVE='PIXEL' (That parameter should store all band values for each pixel continuously on the disk an make it easy and fast to read.)
The function only needs the time-series to work, so no spatial dependency. And the file has 380 bands, each of continental size, summing up 420GB on disk space.
The problem: I used the raster package to read the file as a stack, but when I try to get the values for a pixel, R just stucks and appears to be processing, but this operation should be fast. I tried using the
 notation, using the
extract function and none worked. (Even if I try to get only 3 bands from a small RGB file, R seems slow.)
gdallocationinfo it is extremely fast, and with Python and GDAL module it's also incredibly fast.
So shouldn't it be fast in R too? Am I doing something wrong or missing a function designed for that? Doesn't the Raster package use rgdal internally?
But most importantly, is there a way to do it using rgdal then?