[GRASSLIST:3461] More Africa maps

Michael Ash mash at econs.umass.edu
Fri May 21 05:47:59 EDT 2004


I download Digital Chart of the World (VMAP0) data on a
country-by-country basis in .e00 (ESRI export) format from
http://www.maproom.psu.edu/dcw/ . I believe that the data in
.e00 format are an ESRI product made available for free in a
slightly inconvenient format.

I then use the attached grass script to import and organize
the data, e.g., to assign the correct dig_cats files, etc.
Let me know if I can help with the script.

Best,

Michael



g.gisenv set=MAPSET=ndiku
for i in /home/ndiku/dcw/[a-z]*
do
 echo $i
 country=${i#'/home/ndiku/dcw/'}
 echo $country
 for j in $i/*.e00
 do
    m.in.e00 -is input=$j
    coverage=${j#/home/ndiku/dcw/$country/}
    coverage=${coverage%.e00}
    echo $j
    echo $country $coverage
    g.rename -o vect=$coverage,${country}_$coverage
    g.rename -o sites=$coverage,${country}_$coverage
    if [ -e /home/ndiku/grass/SSA/ndiku/dig_cats/${coverage} ]
     then
      for k in /home/ndiku/grass/SSA/ndiku/dig_cats/${coverage}*
       do
        label=${k#/home/ndiku/grass/SSA/ndiku/dig_cats/$coverage}
        echo $k
        echo $label
        mv $k /home/ndiku/grass/SSA/ndiku/dig_cats/${country}_$coverage$label
       done
     fi
 done
 if [ -e /home/ndiku/grass/SSA/ndiku/site_lists/${country}_aepoint ]
  then
    s.to.vect -p input=${country}_aepoint output=${country}_aepoint
    cp /home/ndiku/grass/SSA/ndiku/dig/${country}_aepoint /home/ndiku/grass/SSA/ndiku/dig/${country}_aepoint.aeptname
    cp /home/ndiku/grass/SSA/ndiku/dig_att/${country}_aepoint /home/ndiku/grass/SSA/ndiku/dig_att/${country}_aepoint.aeptname
    cp /home/ndiku/grass/SSA/ndiku/dig_plus/${country}_aepoint /home/ndiku/grass/SSA/ndiku/dig_plus/${country}_aepoint.aeptname
  fi
 if [ -e /home/ndiku/grass/SSA/ndiku/site_lists/${country}_pppoint ]
  then
    s.to.vect -p input=${country}_pppoint output=${country}_pppoint
    cp /home/ndiku/grass/SSA/ndiku/dig/${country}_pppoint /home/ndiku/grass/SSA/ndiku/dig/${country}_pppoint.ppptname
    cp /home/ndiku/grass/SSA/ndiku/dig_att/${country}_pppoint /home/ndiku/grass/SSA/ndiku/dig_att/${country}_pppoint.ppptname
    cp /home/ndiku/grass/SSA/ndiku/dig_plus/${country}_pppoint /home/ndiku/grass/SSA/ndiku/dig_plus/${country}_pppoint.ppptname
  fi
done


> for some time now there are African 90m (3 arcsec) elevation SRTM
> data available at http://edcftp.cr.usgs.gov/pub/data/srtm/ for
> free. there is also Markus Neteler' s script for loading them into
> Grass available somewhere on the net, Google it (though honestly I
> haven't tried it yet :))

>> Hi all, First of all - I am an *extreme* newbie with anything
>> related to GIS, but I am very keen on learning a lot about this
>> subject, mainly for personal reasons.

>> I am now in the process of looking for the right software to start
>> of with, and since I am a Linux user, it seems all people end up
>> recommending GRASS, so - here I am :)

>> I am still in the installation phase of GRASS, but I thought it
>> might be a good idea at this stage to ask about obtaining data from
>> external sources. At this stage I am particularly interested in data
>> from the following sites:

>>  1) http://www.georigin.com/ - Contain datasets related to African countries
>>  2) http://edc.usgs.gov/products/elevation/gtopo30.html and
>> http://lpdaac.usgs.gov/gtopo30/gtopo30.asp (essentially the same ORG) -
>> GTOP30 data sets related to Southern Africa

>> It seems from what I have read that I would be able to use the
>> GTOP30 data, although if there are any people that has some input
>> here, I will greatly apprciate it !

>> The problem really is with the first site (georigin.com). I can
>> download the data I'm interested in in one of the following formats:
>> Asset, Planet or MapInfo. As you can see from this site, one of the
>> links they obtained there data from refers eventually to a site in
>> the usgs.gov domain - which make me belief the data might actually
>> be in GTOP30 format or something similar.

>> Has anyone worked with this data yet? Any tips/pointers?




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