Ulli,
Yes, I have used this data for Haiti and Europe.
1. uncompress the .bil file into your cell directory
2. create an ascii header file for it (or run r.support & edit header)
Here's my header for eur_30_dem1:
proj: 3
zone: 0
north: 85N
south: 35N
east: 22:30E
west: 25W
cols: 5700
rows: 6000
e-w resol: 0:00:30
n-s resol: 0:00:30
format: 1
compressed: 0
3. next I ran r.mapcalc to get real negative numbers instead of unsigned
ints:
r.mapcalc eur_30_dem1a="if(eur_30_dem1>32768,eur_30_dem1-65536,eur_30_dem1)"
(This creates a smaller file due to automatic compression.)
4. Then run r.support to create a color file. You will probably have to
edit the color file because they use the value -9999 for no data so
you may want to assign a specific color to that, then use the remaining
range for a color ramp. For Haiti, I just made all -9999 data zero since
there was no "real" zero data. r.stats can help you find the real
minimum.
Here's my colr file for eur_30_dem1a:
% -9999 4536
-9999:55:55:255
-30:150:230:150 0:10:230:10
0:10:230:10 492:10:160:10
492:10:160:10 962:50:130:10
962:50:130:10 1514:120:100:30
1514:120:100:30 2067:120:130:40
2067:120:130:40 2481:170:160:50
2481:170:160:50 2757:235:235:100
2757:235:235:100 4536:255:255:200
5. Now you can get rid of the file eur_30_dem1:
g.remove eur_30_dem1
g.rename eur_30_dem1a,eur_30_dem1
- Bill