[R-sig-Geo] how to do a principle component analysis with geo-referenced points
koen.hufkens at ua.ac.be
Mon Nov 13 10:15:27 CET 2006
>From fields to objects: A review of geographic boundary analysis
Integrating Edge Detection and Dynamic Modeling in Quantitative Analyses of Ecological Boundaries
Measuring the abruptness of patchy ecotones - A simulation-based comparison of landscape pattern statistics
Edge effects in fragmented landscapes: a generic model for
delineating area of edge influences (D-AEI)
I've got a lot more in my endnote database, I can send you the file if you want to because this copy pasting isn't exactly efficient.
Koen Hufkens, Phds
Department of Biology
Research Group of Plant and Vegetation Ecology
University of Antwerp
B-2610 Wilrijk, Belgium
Koen.Hufkens at ua.ac.be
> -----Original Message-----
> From: r-sig-geo-bounces at stat.math.ethz.ch
> [mailto:r-sig-geo-bounces at stat.math.ethz.ch] On Behalf Of
> Nicholas Lewin-Koh
> Sent: zondag 12 november 2006 4:23
> To: Carlos A. Bastos M.Guerra
> Cc: r-sig-geo at stat.math.ethz.ch
> Subject: Re: [R-sig-Geo] how to do a principle component
> analysis with geo-referenced points
> Hi Carlos,
> I think that there are tools in the sp package for dealing with grids.
> If I am understanding you correctly and you want to do
> "zoning" of your region than you probably are not looking to
> do pca, but some sort of clustering.
> Marie Jose Fortin had some nice papers on a technique called
> wombling, for finding regions of abrupt ecological change.
> There are some other techniques for spatial partitioning, but
> I am not sure if they are implemented in R. It has been a
> long time since I worked on ecological problems.
> For more information on the spatial tools in R a good place
> to start is http://cran.r-project.org/src/contrib/Views/Spatial.html
> the CRAN task view for spatial statistics, and
> has some more pointers.
> Hope this helps,
> On Sat, 11 Nov 2006 20:24:59 -0000, "Carlos A. Bastos M.Guerra"
> <carlosguerra at esa.ipvc.pt> said:
> > Dear Nicholas,
> > First of all thanks for the references, I think they will
> help me with
> > my current problem. :) The thing is that I am used to work
> with AcrGIS
> > to do the spatial analysis, but the statistical methods in
> ArcGIS are
> > a bit "dummy", namely in spatial PCA. I am used to work with R with
> > the ade4 package :) but when I heard that I could do
> spatial analysis
> > with R I ad to try it...but its more difficult that it seams (at
> > first)...
> > What I did was: (in ArcGIS) convert the centroids of a grid into a
> > point shape file, than I have integrated all the information into
> > different columns. I converted the dbf file into a txt an then I
> > imported the file into R ... and my problems began... :)
> > My objective is to do a PCA and extract the different
> groups of points
> > in order to make an ecological zoning.
> > I am still starting with R and "the Geo tools" can you
> point me some
> > reading material that I can use?
> > Best regards,
> > Carlos
> > -----Mensagem original-----
> > De: Nicholas Lewin-Koh [mailto:nikko at hailmail.net]
> > Enviada: sábado, 11 de Novembro de 2006 19:06
> > Para: r-sig-geo at stat.math.ethz.ch
> > Cc: Carlos GUERRA
> > Assunto: [R-sig-Geo] RE: how to do a principle component
> analysis with
> > geo-referenced points
> > Hi Carlos,
> > There are a couple of ways to do this, but you have to be a little
> > more specific about what your goals/intentions are. I
> assume you have
> > points p(x1,y1), ...., p(xn,yn), where p is a vector of
> > If the goal is interpolation than you have to model the spatial
> > covariance of the orthognal factors, and you should look at
> > waekernagel's book.
> > if your goal is to extract principal components and account for the
> > variance induced by a spatial process, a quick and dirty
> approach is
> > to include polynomials of the xy coordinates in the data
> and do pca on
> > the augmented matrix. Take a look at
> > Borcard, D., P. Legendre & P. Drapeau. 1992. Partialling out the
> > spatial component of ecological variation. Ecology 73: 1045-1055
> > Méot, A., P. Legendre & D. Borcard. 1998. Partialling out
> the spatial
> > component of ecological variation: questions and
> propositions in the
> > linear modeling framework. Environmental and Ecological Statistics 5
> > (1): 1-27.
> > Another approach is spatial factor analysis
> > Christensen, WF, and Amemiya, Y (2001). "Generalized
> > analysis method for multivariate geo-referenced data," Mathematical
> > Geology, 33, 801-824.
> > Christensen, WF, and Amemiya, Y (2002). "Latent variable
> analysis of
> > multivariate spatial data," Journal of the American Statistical
> > Association, 97, 302-317
> > If your question is there R code to do this, I think the
> ade4 package
> > can to the spatial variance partitioning, but for factor
> analysis, you
> > are on your own.
> > Nicholas
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