Hi
Thank you for the references and the software.
I'm going to your web site.
I know your book quite well (I started my Ph.D. using your book).
Sebastiano
At 14.46 02/02/2010, Pierre Goovaerts wrote:
Hello,
Factorial kriging is not very sophisticated,
it's just a slight variant of kriging
that requires the modification of just a few lines of codes.
Anyways, I just posted a program to perform factorial kriging analysis
in the download section of my website. I hope your grid is not too big,
The program filter.exe (FORTRAN source code
filter.f) is a modified version of the Gslib
program kt3d.f that allows performing a kriging
analysis. Based on the number of nested
structures of the variogram model specified in
the parameter file filter.par, the program will
estimate the values of the noise and
noise-filtered signal (1 structure), or the
values of the noise, local and regional
components (2 structures). Following Goovaerts
(1997, page 167), the regional component
includes both the long-range component and the
trend component in order to attenuate the impact
of the search window on the estimation of these long-range spatial components.
The zipped folder includes the executable, the
source code, as well as a sample parameter file for the Jura dataset.
In another paper concerned with noise-filtering of imagery, I run the
program for a single pixel to get the kernel weights and then apply
the same kernel everywhere (since the data geometry does not change except
at the edges of the image).
<http://home.comcast.net/%7Epgoovaerts/RSE-2005.pdf>Goovaerts,
P., Jacquez, G.M., and W.A. Marcus. 2005.
Geostatistical and local cluster analysis of
high resolution hyperspectral imagery for
detection of anomalies. Remote Sensing of the
Environment<http://home.comcast.net/%7Epgoovaerts/RSE-2005.pdf>, 95, 351-367.
Cheers,
Pierre
On Tue, Feb 2, 2010 at 3:39 AM, seba
<<mailto:[email protected]>[email protected]> wrote:
Hi Pierre
I think that for my task factorial kriging is a little bit
too much sophisticated (nevertheless, is there any open source or
free implementation of it ??? I remember that it
is implemented in Isatis.....).
I have an exhaustive and regularly spaced data set (i.e. a grid) and I need
to calculate locally the spatial variability of the residual surface or better
I would like to calculate the spatial
variability of the high frequency component.
Here I'm lucky because I know exactly what I
want to see and what I need to filter out.
In theory, using (overlapping) moving window
averages (but here it seems better to use some more complex kernel)
one should be able to filter out the short range
variability (characterized by an
eventual variogram range within the window size???).
Seeing the problem from another perspective, in the case of a perfect
sine wave behavior, I should be able to filter out spatial
variability components with wave lengths up to the window size.
But maybe there is something flawed in my
reasoning....so feedback is appreciated!
Bye
Sebastiano
At 16.27 01/02/2010, you wrote:
well Factorial Kriging Analysis allows you to tailor the filtering weights
to the spatial patterns in your data. You can use the same filter size but
different kriging weights depending on whether you want to estimate
the local or regional scales of variability.
Pierre
2010/2/1 seba
<<mailto:[email protected]> [email protected]>
Hi José
Thank you for the interesting references. I'm going to give a look!
Bye
Sebastiano
At 15.46 01/02/2010, José M. Blanco Moreno wrote:
Hello again,
I am not a mathematician, so I never worried
too much on the theoretical reasons. You may
be able to find some discussion on this
subject in Eubank, R.L. 1999. Nonparametric
Regression and Spline Smoothing, 2a ed. M. Dekker, New York.
You may be also interested on searching
information in and related to (perhaps citing)
this work: Altman, N. 1990. Kernel smoothing
of data with correlated errors. Journal of the
American Statistical Association, 85: 749-759.
En/na seba ha escrit:
Hi José
Thank you for your reply.
Effectively I'm trying to figure out the
theoretical reasons for their use.
Bye
Sebas
--
Pierre Goovaerts
Chief Scientist at BioMedware Inc.
3526 W Liberty, Suite 100
Ann Arbor, MI 48103
Voice: (734) 913-1098 (ext. 202)
Fax: (734) 913-2201
Courtesy Associate Professor, University of Florida
Associate Editor, Mathematical Geosciences
Geostatistician, Computer Sciences Corporation
President, PGeostat LLC
710 Ridgemont Lane
Ann Arbor, MI 48103
Voice: (734) 668-9900
Fax: (734) 668-7788
<http://goovaerts.pierre.googlepages.com/>http://goovaerts.pierre.googlepages.com/
--
Pierre Goovaerts
Chief Scientist at BioMedware Inc.
3526 W Liberty, Suite 100
Ann Arbor, MI 48103
Voice: (734) 913-1098 (ext. 202)
Fax: (734) 913-2201
Courtesy Associate Professor, University of Florida
Associate Editor, Mathematical Geosciences
Geostatistician, Computer Sciences Corporation
President, PGeostat LLC
710 Ridgemont Lane
Ann Arbor, MI 48103
Voice: (734) 668-9900
Fax: (734) 668-7788
<http://goovaerts.pierre.googlepages.com/>http://goovaerts.pierre.googlepages.com/
