<div>Dear All,</div><div><br></div>Thanks for all the help on this matter. Sorry for the late reply (fieldwork and vacation got in the way...)! <div><br></div><div>I ended up solving the problem by (1) filling the ocean nulls, (2) splitting the region into subregions, and (3) running it on a more powerful machine.</div>
<div><br></div><div>Best,</div><div>Nick<br><br><div class="gmail_quote">On Fri, Dec 2, 2011 at 11:39 PM, pkscwc <span dir="ltr"><<a href="mailto:pkscwc@gmail.com">pkscwc@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
Dear Nick,<br>
<br>
I am working on SRTM rasters of resolution 1km, 500m, 250m and recently 90m<br>
using GRASS for long and had countered the problem being faced by you.<br>
<br>
My workaround is given below and as a by-product you may get a very nice<br>
coastline vector/raster also.<br>
<br>
1. I have converted all the nulls with r.mapcalc to -160 using the formula<br>
C=if(A, if(isnull(B),-160,B))<br>
Where,<br>
A: region of interest<br>
B: original srtm raster with nulls for sea and holes<br>
C: Output map in which nulls have been converted to -160.<br>
<br>
(Why -160, because in my map, as from my human memory, the lowest value was<br>
-70. I just chose a value lower than this value. We will need it later on to<br>
convert back them as holes for r.fillnulls to work upon.)<br>
<br>
A sample from the history file of the raster is produced below:<br>
<br>
Sun Aug 1 17:49:10 2010<br>
test5<br>
PERMANENT<br>
pks<br>
raster<br>
<br>
<br>
generated by r.mapcalc<br>
if(test_nL_region@PERMANENT, if(isnull(ib2@PERMANENT), -160, ib2@PERMANENT))<br>
<br>
<br>
A: test_nL_region<br>
<br>
This raster map is a region of my interest out the big srtm raster converted<br>
from a vector. Grass has a command , which converts the current region to a<br>
vector file.<br>
Again, the sample from the history file of the raster is produced below:<br>
<br>
ed Jul 28 10:09:42 2010<br>
test_nL_region<br>
PERMANENT<br>
pks<br>
raster<br>
Vector Map: nL_region@PERMANENT in mapset PERMANENT<br>
Original scale from vector map: 1:1<br>
generated by v.to.rast<br>
v.to.rast input="nL_region@PERMANENT" output="test_nL_region" use="c\<br>
at" type="point,line,area" layer=1 value=1 rows=4096<br>
<br>
nL_region:<br>
Again, the sample from the history file of the vector is produced below:<br>
COMMAND: v.in.region output="nL_region" type="area" cat=1<br>
GISDBASE: /home/pks/renamed_grassdata<br>
LOCATION: newLocation MAPSET: PERMANENT USER: pks DATE: Wed Jul 28 09:53:43<br>
2010<br>
<br>
So, now we have -160s all around , i.e. the sea and holes on land.<br>
<br>
Now use the r.reclass.area feature to differentiate sea from holes on land.<br>
A sample from my recent work is given below:<br>
<br>
Tue Nov 8 13:55:47 2011<br>
bi_reclassed3_area.recl<br>
work2<br>
rdcgis1<br>
reclass<br>
Reclassified map based on:<br>
Map [bi_reclassed3.clump.bi_reclassed3_area] in mapset [work2]<br>
generated by r.reclass<br>
<br>
I am using GRASS7 and in the history given above , all the parameters are<br>
not available.<br>
In my case , I used 1 billion hectare as "greater than area" parameter to<br>
bring out the sea , land , and holes in land in different categories.<br>
<br>
Thereafter, use mask and pick up the landmass with holes in land , which you<br>
want to fill.<br>
Just remember to convert back the -160 to null again.<br>
<br>
I felt that r.fillnulls works best when the nulls have values around them.<br>
<br>
By the way, CGIAR provides holes-filled-SRTM-raster.You may like to read<br>
their literature for understanding the algorithms used to fill the nulls.<br>
It's good and useful.<br>
<br>
Try this link for downloading clean rasters of your area of interest:<br>
<br>
<a href="http://srtm.csi.cgiar.org/SELECTION/inputCoord.asp" target="_blank">http://srtm.csi.cgiar.org/SELECTION/inputCoord.asp</a><br>
<br>
Hope, it helps.<br>
<br>
Some of my observations are listed below:<br>
1. If the system lacks RAM, then increase patience.<br>
2. If the system lacks hard-disk space, don't go for GIS.<br>
3. Learn python.<br>
<span class="HOEnZb"><font color="#888888"><br>
--<br>
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