How can I create an R loop with the code provided below?

Please, I need help in creating a loop that would do the computation shown in the codes below on a hdflist containing 483 files in R. I have added a link that contains two .hdf files and the shapefiles for trial. The code seems to work just fine for a single .hdf file but I'm still struggling with looping. Thank you

download files from here https://beardatashare.bham.ac.uk/getlink/fi2gNzWbuv5H8Gp7Qg2aemdM/

# import .hdf file into R using get_subdatasets to access the subsets in the file`
sub <- get_subdatasets("MOD13Q1.A2020353.h18v08.006.2021003223721.hdf")

# convert red and NIR subsets and save them as raster`
gdalwarp(sub[4], 'red_c.tif')
gdalwarp(sub[5], 'NIR_c.tif')

# import red and NIR raster back into R`
# scale the rater while at it`

r_r=raster('red_c.tif') * 0.0001 
r_N=raster('NIR_c.tif') * 0.0001 

# calculate sigma using (0.5*(NIR+red))`
sigma <- (0.5*(r_N+r_r))

# calculate knr using exp((-(NIR-red)^2)/(2*sigma^2))`
knr <- exp((-(r_N-r_r)^2)/(2*sigma^2))

# calculate kndvi using (1 - knr) / (1 + knr)`
kndvi <- (1 - knr) / (1 + knr)

# import shapefile into R`
shp=readOGR(".", "National_Parks")
options(stringsAsFactors = FALSE)

#change crs of shapefile to crs of one of the rasters`
shp2 <- spTransform(shp, crs(kndvi))

# use extent to crop/clip raster`
## set extent`
e <- extent(910000,980000, 530000, 650000)

## clip using crop function`

crop_kndvi <- crop(kndvi, e)

# mask raster using the shapefile`
kndvi_mask <- mask(crop_kndvi, shp2)

And then save kndvi_mask as raster for 483 files

Here is how you can do that with terra. terra is the replacement for raster; it is much faster and more versatile. For example, with terra you can skip the gdalwarp step.

You can write one big for-loop, but I prefer to use functions and then call these in a loop or lapply.

Also, instead of your raster-algebra approach, it could be more efficient to wrap the kndvi computation into its own function and use it with lapp. I think that is a better approach as the code is clearer and it allows you to re-use the kndvi function.

library(terra)
parks <- vect("National_Parks.shp")
parks <- project(parks, "+proj=sinu +lon_0=0 +x_0=0 +y_0=0 +R=6371007.181 +units=m")
e <- ext(910000,980000, 530000, 650000)

kndvi function to be used by lapp

kndvi <- function(red, NIR) {
    red <- red * 0.0001 
    NIR <- NIR * 0.0001 
    sigma <- (0.5 * (NIR + red))
    knr <- exp((-(NIR-red)^2)/(2*sigma^2))
    (1 - knr) / (1 + knr)
}

Main function. Note that I use crop before the other functions; that saves a lot of unnecessary processing.

fun <- function(f) {
    outf <- gsub(".hdf$", "_processed.tif", f) 
    # if file.exists(outf) return(rast(outf))
    r <- rast(f)[[4:5]]
    # or r <- sds(f)[4:5]
    r <- crop(r, e)
    kn <- lapp(r, kndvi)
    name <- substr(basename(f), 9, 16)
    mask(kn, parks, filename=outf, overwrite=TRUE, names=name)
}

Get the filenames and use the function with a loop or with lapply as shown by Elia.

ff <- list.files(pattern="hdf$", full=TRUE)

x <- list()
for (i in 1:length(ff)) {
    print(ff[i]); flush.console()
    x[[i]] <- fun(ff[i])
}
z <- rast(x)
z

#class       : SpatRaster 
#dimensions  : 518, 302, 2  (nrow, ncol, nlyr)
#resolution  : 231.6564, 231.6564  (x, y)
#extent      : 909946.2, 979906.4, 530029.7, 650027.7  (xmin, xmax, ymin, ymax)
#coord. ref. : +proj=sinu +lon_0=0 +x_0=0 +y_0=0 +R=6371007.181 +units=m +no_defs 
#sources     : MOD13Q1.A2020337.h18v08.006.2020358165204_processed.tif  
#              MOD13Q1.A2020353.h18v08.006.2021003223721_processed.tif  
#names       :     A2020337,     A2020353 
#min values  : 0.0007564131, 0.0028829363 
#max values  :    0.7608207,    0.7303495

This takes about 1 second per file on my computer.

Or as a for-loop that you asked for:

ff <- list.files(pattern="hdf$", full=TRUE)
for (f in ff) {
    print(f); flush.console()
    outf <- gsub(".hdf$", "_processed.tif", f) 
    r <- rast(f)[[4:5]]
    r <- crop(r, e)
    kn <- lapp(r, kndvi)
    name <- substr(basename(f), 9, 16)
    mask(kn, parks, filename=outf, overwrite=TRUE, names=name)
}

outf <- list.files(pattern="_processed.tif$", full=TRUE)
x <- rast(outf)