Hi Bulent,
No problem, but please always copy the list, so that:
- others can offer an alternative solution (as I said, I'm highly
biased towards R)
- our discussion can be searchable by everybody for further reference
I have spent a good portion of today working on this project and I got as
far as reorganizing the data. It seems that any step after this is beyond my
knowledge of GRASS, such as generating an interpolation grid (quoting you):
# Generate an interpolation grid (the same for each raster to be generated)
resolution <- 5 # your resolution
This just sets the resolution of the grid I want to generate to 5m.
grid <- expand.grid(x = seq(min(df$UTM_E), max(df$UTM_E), by =
resolution), y = seq(min(df$UTM_N), max(df$UTM_N), by = resolution))
grid <- points2grid(grid)
This is a quick and dirty way to generate a grid (raster) on which
interpolate your points. If you got a polygon (shapefile) of your
study area, you'd better use it to generate an interpolation grid. See
?spsample for that.
I understand that I should define the geographic extents –hence creating an
interpolation grid– of the data I will interpolate from this weather
station. However, I am not sure if the statements below are the commands
that I should type in the Terminal of Grass (they seem to be R commands):
[ grid <- expand.grid(x = seq(min(df$UTM_E), max(df$UTM_E), by =
resolution), y = seq(min(df$UTM_N), max(df$UTM_N), by = resolution))
grid <- points2grid(grid) ]
and
[ make_map <- function(data, grid) ]
This is R code, indeed. What you need to do is to open a R session
from within GRASS. Just type R on your GRASS command line. Then you'll
be in a R session that is in GRASS 
Make sure you check out the
spgrass6 package to interface your R session with your GRASS session.
HTH,
Pierre
--
Scientist
Landcare Research, New Zealand