[R-sig-Geo] Downsample (aggregate) raster by a non-integer factor, using a Gaussian filter

[Nikolaos Tziokas]

I have a fine resolution raster (100m pixel size) and I want to downsample
it (aggregate) to 460m pixel size. The downsampling should be done using a
Gaussian filter (local function). The scale factor is 4.6, so non-integer.
The sigma (std) parameter of the Gaussian filter should be expressed in
cells (pixels) (also the Gaussian filter in this manner).

To put it differently I am trying to simulate coarse data as though they
were measured with a coarse point spread function (PSF). The PSF is assumed
to be a Gaussian filter.

So, in theory, for each coarse pixel I need to go to its center and
calculate the weights (from the PSF/Gaussian filter) needed for each fine
pixel surround it. To do this I need to apply a transfer function (TF;
e.g., Gaussian filter) to the fine data, but with a very large width.

The function aggregate from the terra package does not allow the fact
argument to be non-integer, so I thought to create a template raster (a
raster with no pixel values) from a coarse resolution raster at 460m
spatial scale that I have.

All in all, I need to create a custom function which downsamples a raster
using a Gaussian filter (units in pixels).

So far I created the template raster:

library(terra)

fr = rast("path/tirs.tif") # raster to be upscaled
cr = rast("path/ntl.tif")

# create an empty raster with the same dim, extent and crs as the coarse
res raster
(er <- rast(ext(cr), resolution=res(cr)))
crs(er) <- crs(cr)

The raster layers I am using:

fr = rast(ncols=216, nrows=417, nlyrs=1, xmin=582700, xmax=604300,
ymin=1005700, ymax=1047400, names=c('B10_median'), crs='EPSG:7767')

cr = rast(ncols=48, nrows=91, nlyrs=1, xmin=582360, xmax=604440,
ymin=1005560, ymax=1047420, names=c('avg_rad'), crs='EPSG:7767')
Any recommendations on how I can proceed?

-- 
Tziokas Nikolaos
Cartographer

Tel:(+44)07561120302
LinkedIn <http://linkedin.com/in/nikolaos-tziokas-896081130>

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