[Geowanking] Election Maps / Population Cartogram
creta.kano at gmail.com
Fri Nov 7 12:57:08 PST 2008
To clarify, I meant that if you have a origin/destination data of
travel costs you would have to conflate that data to a polygonal
As an example, I just grabbed the roads file from Geocommons as a
proxy for the travel cost with the very simplistic assumption that
more roads results in lower travel costs.
I agree that weighted graphs would be a better visualization and more
commonly used to display OD types of data.
On Fri, Nov 7, 2008 at 3:29 PM, Christian Willmes
<c.willmes at uni-koeln.de> wrote:
> sophia parafina schrieb:
> very cool! :-)
> But I don't get this:
>> If you want to do travel cost between cities you will need to conflate
>> you values to a polygon layer of administrative boundaries, since the
>> algorithm and scapetoad only works on polygons. So its definitely
>> most doable.
> How can I derive travel cost from roads per area?
> Am I right, that you want to derive cost from the density distribution
> of roads per area?
> If the density between two points is low the cost is high and if the
> density between two points is high the cost is low? So far so good.
> But what if you have for example a highway through a very large area.
> The points along this highway would be accessible far better than the
> points in this area not connected directly to this one highway, but this
> other points would get the same cost values to access them, because they
> are in the same area unit.
> So in the moment I think you cant make good assumptions about travel
> cost from density distributions. Wheighted graphs are the better model
> for that question I think, also for the visualization of it... ;-)
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