Brent,
You describe a useful approach. The pixel resolution approach can
also be valuable for judging maximum vector resolution. There isn't
much to rendering more than 1-2 nodes per pixel of resulting map /
screen / print image. Minimum resolution is much harder to judge,
since the irregularity of a feature may be so variable even within a
dataset. Could be just aesthetic, or otherwise application-specific.
For example, at what scale does the topology become incorrect (holes
not shown correctly, etc.)? At what scale does the vector
representation misrepresent feature length or area significantly? A
tough problem, I think.
Cheers,
Josh
On May 8, 2007, at 10:43 AM, Brent Fraser wrote:
Ari,
Usually the creator of the vector data would select a
map scale (e.g. 1:50,000) that the vectors would be
rendered, then ensure the positional accuracy and the
resolution/point-density of the vectors would be suitable
for that scale. Of course the end user of the data may
choose to use it at a different scale, but it may appear too
generalized (jaggy, lack points, etc) at a larger scale
(e.g. 1:10,000), or have too many points (or features) at
smaller scale (1:1,000,000).
For raster image data (sorry, I don't have one for
vectors), my rule-of-thumb for relating resolution to scale
is: take the pixel size (resolution) in meters, multiply by
4000 and that will give a reasonable scale to view the
image. So for Quickbird satellite image data with a
resolution of 0.6 meters, a good scale would be 1:2,400 (0.6
x 4000=2400). Any larger scale than that and you'll start
to see pixel edges.
For vectors, perhaps a roughness value (using fractal
math?) could be computed and used with the coordinate values
to come up with appropriate scale. It would likely depend
on the objects the vectors represented (streams are rougher
than roads, etc). Just a thought...
Brent Fraser
GeoAnalytic Inc.
Calgary, Alberta
----- Original Message -----
From: "Ari Jolma" <[EMAIL PROTECTED]>
To: <[email protected]>
Sent: Tuesday, May 08, 2007 3:35 AM
Subject: [Geowanking] Scale of vector data
I'm a bit ignorant on this issue. I've thought that it's a
bit
meaningless to talk about the scale of vector data but
clearly one can
have more accurate and less accurate polygons for example.
Are there commonly accepted methods for computing the
scale of an
arbitrary geospatial dataset?
Just asking,
Ari
--
Prof. Ari Jolma
Geoinformaatio- ja paikannustekniikka / Geoinformation and
positioning
Teknillinen Korkeakoulu / Helsinki University of
Technology
tel: +358 9 451 3886 address: POBox 1200, 02015 TKK,
Finland
Email: ari.jolma at tkk.fi URL: http://www.tkk.fi/~jolma
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