I'm trying to generalize the 90m SRTM DEM for use in cartography, e.g.
for a hillshading in a 1:700.000 map. Emphasis is on a good-looking
map, not on a hydrologic correct model. For this scale, there is too
much detail in the SRTM DEM, so I tried different filtering
approaches: r.neigbors, r.resample.rst and other methods like
resolution-bumping, but the output looks to soft: all the main ridges,
which should give a quite crisp image have disappeared. I would like
to keep the main structures (like high peaks and long ridges) and drop
the small structures like short ridges, small gullys and channels. I
know, automated generalizing of elevation models is one of the biggest
topics in modern cartography, but maybe someone has a good hint
You may find the CleanTOPO2 data set what you need.
David
On 6/20/06, Hamish <hamish_nospam@yahoo.com> wrote:
Lars:
> I'm trying to generalize the 90m SRTM DEM for use in cartography, e.g.
> for a hillshading in a 1:700.000 map. Emphasis is on a good-looking
> map, not on a hydrologic correct model. For this scale, there is too
> much detail in the SRTM DEM, so I tried different filtering
> approaches: r.neigbors, r.resample.rst and other methods like
> resolution-bumping, but the output looks to soft: all the main ridges,
> which should give a quite crisp image have disappeared. I would like
> to keep the main structures (like high peaks and long ridges) and drop
> the small structures like short ridges, small gullys and channels. I
> know, automated generalizing of elevation models is one of the biggest
> topics in modern cartography, but maybe someone has a good hint
