Looping for importing and interpolating a lot of LIDAR files?

Question

I'm quite new to Grass Gis and I'm trying to make DEM (digital elevation model) for modelling flooding. I have 170 *.xyz files, which need to be scanned for extents (r.in.xyz -s input=...\filename.xyz output=filename fs= ' '), then region needs to be set with previously recieved data (g.region n=... s=... e=... w=... res=2), importing lidar data (r.in.xyz input=...\filename.xyz output=filename fs= ' ') and at last interpolating that data (r.surf.idw input=filename@Siim output=filenameidw).

I did it successfully with one file, but it would be waste of time to do it manually for 170 files. Can anyone recommend me a loop, which I can use?

Answer 1

Here's a snippet of a bash shell script I use:

for f in precip_accum*.txt; do
    precip_rast=`basename ${f} .txt`
    precip_recl=${precip_rast}_recl
    reg=`r.in.xyz -s -g input=${f} output=dummy fs=, |  awk '{print $1" "$2" "$3" "$4}'`
    g.region --quiet $reg
    # Also set resolution to 1/30 degree (about 3 km)
    g.region --quiet res=0.033

    r.in.xyz --quiet --overwrite input=${f} output=${precip_rast} fs=, method=mean
    r.null --quiet $precip_rast setnull=0
    ... more lines with additional processing...
done

I'd like to add that with dense lidar point data you might not need to interpolate at all. This gives a big savings in time. If you have at least one lidar point per raster cell, then just use (as above) method=mean and each raster cell will get the mean height of the lidar points in that cell.

For a python script you would start with something like:

import os
import grass.script as grass
for f in os.listdir(...directory of your filename.xyz...):
    if f.endswith(".xyz"):
        f_out, ext = os.path.splitext(f)
        grass.run_command('r.in.xyz', input=f, output=f_out)

and similarly the rest of the grass modules you need