Dear Isobel Clark
Thank you very for your help
I have used the software on your web site and I have understood more
precisely in which way kriging estimation variance works
Sincerely
Sebastiano Trevisani
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Hello everyone,
Here is a link to Geotrans, a program developed by the US National Imagery
and Mapping Agency to convert locations between different coordinate
systems.
http://earth-info.nima.mil/GandG/geotrans/geotrans.html
It can work in batch mode.
Julian M. Burgos
University of Washington
Sc
On Fri, 24 Oct 2003, Susan King wrote:
> I would like to have algorithms for converting lat/long into different
> projections (albers, utm).
You might check out http://www.remotesensing.org/proj/ which has source
and documentation for PROJ.4, map projection software. I think the source
is in C an
On Fri, 24 Oct 2003, [iso-8859-1] Isobel Clark wrote:
> > - convert your longitude
> > and latitude data into a planar projection first
> Do you have an algorithm that works everywhere in the
> world?
There is no single projection that would be appropriate for everywhere in
the world at once, just
Dear All,
I am trying to fiugre out how many locations I need for a sample of ticks in
the eastern United States. I know that teh rule of thumb is that that no less
than twenty pairs are required per distance class, but is there any other
refrence on sampling for spatial analysis?
Thank you
Ru
I would like to have algorithms for converting lat/long into different
projections (albers, utm).
Susan L. King
Operations Research Analyst
USDA Forest Service
11 Campus Blvd., Suite 200
Newtown Square, PA 19073
Phone: (610) 557-4048
Email: [EMAIL PROTECTED]
FAX: (610) 557-4250
Isobel,
There are published algorithms that will do this - one of the advantages of
the UTM projection is that it can be generated anywhere, with the zoning of
the projection accounting for the necessary differences around the globe.
Good software should be able to deal with UTM zones and hence wo
Sebastiano
Large kriging variances have nothing to do with
negative weights. The two are completely different
phenomena - especially in Universal Kriging.
In Ordinary Kriging the estimation variance can become
as high as two times the total sill of the
semi-variogram. This is a theoretical fact
Hello ai-geostats list-members
Performing an universal kriging on chemical data (log transform of
concentration), in some estimation points I obtained an estimation variance
larger (in some case three times) than the sill of residual variogram. From
what I know this is related to negative weigh
Martin
> - convert your longitude
> and latitude data into a planar projection first
Do you have an algorithm that works everywhere in the
world?
Isobel
http://geoecosse.bizland.com/whatsnew.htm
Want to chat instantly wit
Just to reinforce what Edzer said about projections - convert your longitude
and latitude data into a planar projection first - UTM should be OK though
check your data doesn't cross zones. If you don't do this the stats will not
produce meaningful results as degrees are not a correct spatial measur
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