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Hello,<br>
<br>
another idea, unfortunately no solution, would be to ask at the
r-sig-geo Mailinglist[1] - a list on the statistic-package R, which
can be used directly in QGIS via the ManageR-Plugin...if you know a
little bit of statistics and R... but could also be a little bit of
overdoing if you have never worked with R before...<br>
<br>
Maybe an idea...<br>
Albin<br>
<br>
[1]<br>
<pre wrap=""><a class="moz-txt-link-abbreviated" href="mailto:R-sig-Geo@r-project.org">R-sig-Geo@r-project.org</a>
<a class="moz-txt-link-freetext" href="https://stat.ethz.ch/mailman/listinfo/r-sig-geo">https://stat.ethz.ch/mailman/listinfo/r-sig-geo</a>
</pre>
<br>
Am 25.01.2011 12:52, schrieb Anita Graser:
<blockquote
cite="mid:AANLkTinrEN5nBQpPwng4roUefSGNUsD1pxRdm8sJm_W_@mail.gmail.com"
type="cite">
<div>Hi Nikos,<br>
</div>
<div><br>
</div>
<div>I think this would be a perfect question for <a
moz-do-not-send="true" href="http://gis.stackexchange.com">gis.stackexchange.com</a></div>
<div><br>
</div>
<div>A manual approach (135 stations is not that much) would be to
decide on a maximum distance between stations (depends on your
analysis requirements I guess) and then buffer the station
points accordingly. You can then manually remove points with
redundant/overlapping geographic coverage. </div>
<div><br>
</div>
<div>But I'm sure there are better solutions :)</div>
<div><br>
</div>
<div>Best wishes,</div>
<div>Anita</div>
<br>
<div class="gmail_quote">On Tue, Jan 25, 2011 at 12:09 PM, nikos <span
dir="ltr"><<a moz-do-not-send="true"
href="mailto:vesnikos@gmail.com">vesnikos@gmail.com</a>></span>
wrote:<br>
<blockquote class="gmail_quote" style="margin: 0pt 0pt 0pt
0.8ex; border-left: 1px solid rgb(204, 204, 204);
padding-left: 1ex;">Hello List,<br>
<br>
<br>
I have an interesting problem, and I'd really appreciate if
you could<br>
give a couple insightful tips on how you'd solve the
following:<br>
<br>
I want to order some meteo (rain mm/month for PSDI) data from
my<br>
corresponding national agency, but in their infinitive wisdom
they<br>
choose to place their weather stations in a pattern that
follows<br>
anything but a canonical distribution.<br>
<br>
I know this because they sent me a shp file with all their 136
stations<br>
which are available to the general public - for a fee of
couse.<br>
<br>
Now my problems arise on how I choose which possible
combination of my<br>
dataset of stations correspond to a canonical distribution of
the<br>
mainland - keeping the set of the stations to a minimum as
with each<br>
station the cost goes up?<br>
I want to be as much efficient one can be using GIS technology
;)<br>
<br>
<br>
My initial thinking is to find a subdataset which have their
voronoi<br>
polygons created with the same area. But im not so sure if
thats the<br>
correct approach<br>
<br>
Any tips on how to solve this problem is greatly appreciated!<br>
<br>
<br>
<br>
<br>
Ves Nikos<br>
<br>
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</blockquote>
</div>
<br>
<pre wrap="">
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</blockquote>
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