Multidimensional Scaling (MDS) is certainly an option to be considered.
Its suitability depends, of course, on the specific application.
In my case, which is conceptually similar to Martin's, that option was
discarded.
And I think I can explain why whith this single image:
http://www.geeitema.
ig-geo-
>> boun...@stat.math.ethz.ch] On Behalf Of Martin Renner
>> Sent: Wednesday, January 27, 2010 1:07 AM
>> To: r-sig-geo@stat.math.ethz.ch
>> Subject: [R-sig-Geo] kriging as fish swim, not as crows fly
>>
>> Hi All,
>>
>> I want to kirg fis
Of Martin Renner
> Sent: Wednesday, January 27, 2010 1:07 AM
> To: r-sig-geo@stat.math.ethz.ch
> Subject: [R-sig-Geo] kriging as fish swim, not as crows fly
>
> Hi All,
>
> I want to kirg fish and seabird densities within an estuary which has
> several arms. Since
Ooops, you're right, sorry.
This shows that nobody tried to use it before, haha :)
Now I have uploaded the source files
(http://www.geeitema.org/guenmap/index.jsp?opcion=resultados&idioma=en).
Please let me know if you have any trouble. I have just tested it in
Linux. It compiled and seem to wo
/10, Pilar Tugores Ferra wrote:
From: Pilar Tugores Ferra
Subject: Re: [R-sig-Geo] kriging as fish swim, not as crows fly
To: "Martin Renner"
Cc: r-sig-geo@stat.math.ethz.ch
Date: Wednesday, January 27, 2010, 5:35 PM
Hi, Martin
Two years ago there was a similar discussion on the list:
Hi Facu,
great, this is just what I have been looking for. You say that your
modifications to geoR are open source. On your website I found the geoR.dll
file, but no source code. The .dll is of little use platforms other than
windows. Is there any way I could get the source?
Thank you for the
Hi Martin.
I have succeeded in doing something like that.
Please see http://dx.doi.org/10.1016/j.mcm.2009.05.021.
I used GRASS for the computation of the non-euclidean distances and
modified the geoR library in order to be able to estimate de variograms
and perform kriging prediction with thos
g-geo@stat.math.ethz.ch
Asunto: Re: [R-sig-Geo] kriging as fish swim, not as crows fly
Not kriging as such, but check out the soap-film smoothing in package mgcv:
http://www.maths.bath.ac.uk/~sw283/simon/papers/soap.pdf
FWIW, there are binning methods with MCMC in the package
tripEstimation that have si
Not kriging as such, but check out the soap-film smoothing in package mgcv:
http://www.maths.bath.ac.uk/~sw283/simon/papers/soap.pdf
FWIW, there are binning methods with MCMC in the package
tripEstimation that have similar features, but they are particularly
focussed on individual track estimatio
Hi All,
I want to kirg fish and seabird densities within an estuary which has several
arms. Since neither organisms cross land, the appropriate distances would not
be euclidian but over-water (as fish swim). There are several papers,
describing this problem and how to deal with it (see below),
Tobin Cara wrote:
Hello,
I have recently read an interesting article about integrating Limited Area
Models (LAMs) into kriging with external drift for temperature (Libert� et al.
link below).
www.wmo.int/pages/prog/www/IMOP/.../IOM.../P2(05)_Perini_Italy.doc
This URL is incomplete. Please c
Hello,
I have recently read an interesting article about integrating Limited Area
Models (LAMs) into kriging with external drift for temperature (Libertà et al.
link below).
www.wmo.int/pages/prog/www/IMOP/.../IOM.../P2(05)_Perini_Italy.doc
As I understand, it seems that the authors generated
Hi Greg,
Variogram modelling is slower with large data sets, but 8-10.000
observations should not be a problem, unless you need the results
extremely fast. On my computer (3 years old) it takes about 4 seconds
with 8.000 random observations, using the variogram function in gstat.
Time increas
Hi, I have a very non-specific question about the number of sample points that
can be used
for developing experimental variograms and kriging in R/gstat/etc. Does anyone
have experience
using a very large number of data points in the kriging processes with R? It
has been a few
years since my la
If you are interpolating precipitation you probably should not ignore
the zeros. If you want to log transform your values, perhaps you can
use log(x+1) instead of log(x). Robert
On Tue, Nov 17, 2009 at 10:43 AM, Tobin Cara wrote:
> Hello,
>
> I am taking the log of precipitation values and theref
Hello,
I am taking the log of precipitation values and therefore many are now NA
values. I want to continue to krig my precipitation matrix.
Is there a way to ignore these values with kriging.
My attempt with is.nan still gives:
Erreur : dimensions do not match: locations 105 and data 12
Thank
Tobin Cara wrote:
> Hello,
>
> Thank you all for your previous help. I began using R 2 weeks ago, and I am
> getting somewhere finally. I have been able to run universal kriging with a
> Digital Elevation Model trend. Now, does anyone have experience with kriging
> more than one trend variable
Hello,
Thank you all for your previous help. I began using R 2 weeks ago, and I am
getting somewhere finally. I have been able to run universal kriging with a
Digital Elevation Model trend. Now, does anyone have experience with kriging
more than one trend variable?
I assume you have to have th
Dear all,
I have borehole data from which I want to interpolate the basis of a
faulted sandstone formation using kriging. The structural analysis
clearly shows the effect of faults with a directional variogram that is
nonstationary perpendicular to them, but I am a bit at a loss as to how
thes
Maybe something like this:
http://www.ars.usda.gov/sp2UserFiles/ad_hoc/1200SpatialWorkshop/01VinyardOverview.pdf
- Original Message -
From: milton ruser
Date: Tuesday, August 25, 2009 7:50 pm
Subject: Re: [R-sig-Geo] Kriging
> Hi Kabeli,
>
> I never saw Brian Vinyard
Hi Kabeli,
I never saw Brian Vinyard slides 40! :-)
It is accessible on a internet site?
bests
milton
On Tue, Aug 25, 2009 at 6:56 PM, KABELI MEFANE wrote:
> Hi all
>
> Please help and correct me, to predict Z(S0) at (0.5,0.5) given Z(S1) = 3
> at (0,0), Z(S2) = 5 at(0,1), Z(S3) = 6(1,0) and
Hi all
Please help and correct me, to predict Z(S0) at (0.5,0.5) given Z(S1) = 3 at
(0,0), Z(S2) = 5 at(0,1), Z(S3) = 6(1,0) and Z(S4) = 4(1,1). Let
γ (h)=h^2 h<1
= 1 h>=1 using geo.
I did this: coords<-matrix(c(0,0,1,1,0,1,0,1), nrow=4, ncol=2)
> data<-c(3,5,6,4)
> coordata<-dat
On Sunday 21 June 2009, Ebrahim Jahanshiri wrote:
> It has been long that I wanted to suggets this for automatic trend
> detection based on our previous conversations with Edzer and Anne. I
> found two ways that seem to be reasonable and have potential for
> automizing the trend detection ( I got t
It has been long that I wanted to suggets this for automatic trend
detection based on our previous conversations with Edzer and Anne. I
found two ways that seem to be reasonable and have potential for
automizing the trend detection ( I got these from my conversations
with Margaret Oliver and Dick B
Hello all,
I have been using gstat to krige temperature data with elevation as
external drift.
feb01.meantemp.krig<-krige(MEANTEMP~elevation, locations=
feb01.meantemp, newdata=elevation, model=feb01.meantemp.r)
I keep encountering the warning message:
Error: cannot allocate vector of size
Hi Edzer
Thanks for the feed back.
And yes I agree this is a nice design - the type of input define the type
of output, and, besides that, output.control() can have an
option do explicitly specify the required output format.
If we have the converters, is just a matter of call it internally.
clas
Hi Paulo,
you suggest to add conversion functions to geoR later on, but I (as the
average lazy user) would ask the following: if in the following geoR call
kc.s <- krige.conv(s100, loc=gr.s, krige=krige.control(obj=ml.s))
gr.s is of class SpatialPixels[DataFrame] or SpatialGrid[DataFrame],
I've just added to the geoR tutorial page an script with examples
on converting geoR's krige.conv() outputs to
SpatialGridDataFrame and SpatialPixelDataFrame formats defined by the sp
package
The relevant link is:
http://leg.ufpr.br/geoR/tutorials/kc2sp.R
These should be encapsulated on function
On Sun, 14 Dec 2008, Nicolas Meurisse wrote:
Hello,
After kriging with the use of the krige.conv function, I would like to
export my result under the grid format. In order to view it into a GIS.
It was suggested to me to use the writeGDAL function into the rgdal package.
However It looks l
Hello,
After kriging with the use of the krige.conv function, I would like to
export my result under the grid format. In order to view it into a GIS.
It was suggested to me to use the writeGDAL function into the rgdal
package. However It looks like I have a problem of supported formats
(data
ías
I.E.O. - Centro Oceanográfico de Baleares
Muelle de Poniente s/n
07015 Palma de Mallorca (España)
Tel.: (34) 971 401561
-Mensaje original-
De: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] En nombre de Ashton Shortridge
Enviado el: 27 August 2008 22:22
Para: r-sig-geo@stat.math.ethz.ch
As
Hi Sarah,
This looks interesting and relevant:
http://www.leg.ufpr.br/mbgbook/
On Tuesday 26 August 2008, Edzer Pebesma wrote:
> Diggle & Ribeiro
--
Ashton Shortridge
Associate Professor [EMAIL PROTECTED]
Dept of Geography http://www.msu.edu/~ashton
2
Dave,
Transformation to a continuous distribution when the data follow a
discrete distribution is always messy, and the back-transform may get worse.
While you're at the library, try to pick up Diggle & Ribeiro's
Model-based geostatistics; they describe a model-based approach that
extends gl
Thanks Edzer,
I've requested Cressie's book from our library (just waiting on it).
My main concern was the many 0 counts. I also was not enthusiastic about
odd transformations which then require appropriate back-transforms (I
imagine the back transform of the kriging variance gets messy)
I've
Hi Dave,
Dave Depew wrote:
Hi all,
A question for the more experienced geostats users
I have a data set containing 2-3 variables relating to submerged plant
characteristics inferred from acoustic survey.
The distribution of the % cover variable is bounded (0-100) and highly
left skewed (m
Hi all,
A question for the more experienced geostats users
I have a data set containing 2-3 variables relating to submerged plant
characteristics inferred from acoustic survey.
The distribution of the % cover variable is bounded (0-100) and highly
left skewed (many 0's). The transect spacin
copy of your lecture notes?
Thanks,
Jin
-Original Message-
From: Hengl, T. [mailto:[EMAIL PROTECTED]
Sent: Monday, 7 July 2008 6:23
To: Li Jin
Cc: r-sig-geo@stat.math.ethz.ch
Subject: RE: [R-sig-Geo] kriging [SEC=UNCLASSIFIED]
Jin,
Do not get me wrong. I support your effort
ECTED]
Sent: Mon 7/7/2008 4:10 AM
To: Hengl, T.
Cc: r-sig-geo@stat.math.ethz.ch
Subject: RE: [R-sig-Geo] kriging [SEC=UNCLASSIFIED]
Dear Tom,
Many thanks for your comments and the relevant information. It seems that we
need to clarify what is RK. The definition of RK is, however, not quite
everyone interested in RK or the like.
Best regards,
Jin
-Original Message-
From: Hengl, T. [mailto:[EMAIL PROTECTED]
Sent: Friday, 4 July 2008 5:55
To: Li Jin
Cc: r-sig-geo@stat.math.ethz.ch
Subject: RE: [R-sig-Geo] kriging [SEC=UNCLASSIFIED]
Dear Jin,
I really think that this list
It is under review.
-Original Message-
From: Edzer Pebesma [mailto:[EMAIL PROTECTED]
Sent: Friday, 4 July 2008 6:56
To: Hengl, T.
Cc: Li Jin; r-sig-geo@stat.math.ethz.ch
Subject: Re: [R-sig-Geo] kriging [SEC=UNCLASSIFIED]
Hengl, T. wrote:
> Anybody interested in these topics sho
mailto:[EMAIL PROTECTED]
Sent: Fri 7/4/2008 11:19 AM
To: Frede Aakmann Tøgersen
Cc: Hengl, T.; r-sig-geo@stat.math.ethz.ch; Dave Depew; [EMAIL PROTECTED]
Subject: Re: SV: [R-sig-Geo] kriging
I completely agree with you that this seems the more coherent
statistical modelling approach to these kin
If you are not the intended recipient,
> please notify Faculty of Agricultural Sciences immediately and delete this
> email.
>
>
>
>
>
> Fra: [EMAIL PROTECTED] på vegne af Edzer Pebesma
> Sendt: to 03-07-2008 13:33
> Til: Hengl, T.
ricultural Sciences immediately and delete this email.
Fra: [EMAIL PROTECTED] på vegne af Edzer Pebesma
Sendt: to 03-07-2008 13:33
Til: Hengl, T.
Cc: r-sig-geo@stat.math.ethz.ch; Dave Depew
Emne: Re: [R-sig-Geo] kriging
Hengl, T. wrote:
I agree with Paulo - gstat can wo
Hengl, T. wrote:
Anybody interested in these topics should take a look at sections 2.8 "Final notes about
regression-kriging" and "2.2 Local versus localized models" in my lecture notes (I
like to refer to it because it is an open-access material).
I noticed. But is it peer-reviewed?
--
E
r-sig-geo@stat.math.ethz.ch; [EMAIL PROTECTED]
Subject: RE: [R-sig-Geo] kriging [SEC=UNCLASSIFIED]
Hi All,
I have recently reviewed the spatial interpolation methods for environmental
scientists. Regression kriging (RK) is one of over 40 methods reviewed. Here
attached is what I described in the draft of
If you are not the intended recipient, please notify Faculty of
Agricultural Sciences immediately and delete this email.
Fra: [EMAIL PROTECTED] på vegne af Edzer Pebesma
Sendt: to 03-07-2008 13:33
Til: Hengl, T.
Cc: r-sig-geo@stat.math.ethz.ch; Dave Depew
Emne: Re: [
ariables. EUR 22904 EN Scientific and Technical Research
series, Office for Official Publications of the European Communities,
Luxemburg, 143 pp.
http://bookshop.europa.eu/uri?target=EUB:NOTICE:LBNA22904:EN:HTML
-Original Message-
From: [EMAIL PROTECTED] on behalf of Dave Depew
Sent: Mon 6/16/20
series, Office for Official Publications of the European Communities,
> Luxemburg, 143 pp.
> http://bookshop.europa.eu/uri?target=EUB:NOTICE:LBNA22904:EN:HTML
>
>
> -Original Message-
> From: [EMAIL PROTECTED] on behalf of Dave Depew
> Sent: Mon 6/16/2008 10:54 P
Thank you for all the incredibly valuable and helpful replies.
Summarizing the responses, it seems that kriging on river networks as well
as the group in Tokyo that is developing SANET are the closest exiting
projects on this topic.
Markus
[[alternative HTML version deleted]]
__
Hello.
Following papaer may be helpful.
OKABE, A., SATOH, T. and SUGIHARA, K. "A KERNEL DENSITY
ESTIMATION METHOD FOR NETWORKS,
ITS COMPUTATIONAL METHOD, AND A GIS-BASED TOOL",
Discussion Paper, No. 80, Center for Spatial Information
Science, Univ. of Tokyo,
http://www.csis.u-tokyo.ac.jp/dp/8
I don't know about road networks, but I know of at least four groups
that have worked on kriging over river networks, and one or two that
worked on coastal data using water distance instead of Euclidian
distance. Googling "kriging river network" gave quite a few hits.
--
Edzer
Markus Loecher w
Dear geo experts,
has anyone looked into kriging of spatial processes that do not live in a 2D
continuum but instead are constrained to a network/graph (e.g. a street
grid) ?
Clearly, distances need to be redefined but more than that, the covariance
matrix is a very different animal.
Thanks!
Mark
hi Tom,
That was my impression from reading some introductory texts... I'll have
to see how the mgcv package fits the polynomial function to the
data...it isn't clear to me at first glance how it is accomplished.
Many thanks for your advice.
Dave
Tomislav Hengl wrote:
Dear Dave,
I separate
Dear Dave,
I separate fitting of the deterministic (trend) and residual part of the
universal kriging model all
the time. Adding OK of residuals to the trend is fine, as long as the
regression model is estimated
using GLS (but many do it even if they use only OLS; the difference is often
minor
Thanks Tom,
I've been able to fit a polynomial function to the data quite well. The
residuals are behaving (i.e normal distribution and no skewness of
variance). I'm assuming this means that I could krige the residuals
(Ordinary K?) and then add the trend back to the predicted residual
grid? I
=EUB:NOTICE:LBNA22904:EN:HTML
-Original Message-
From: [EMAIL PROTECTED] on behalf of Dave Depew
Sent: Mon 6/16/2008 10:54 PM
To: Paulo Justiniano Ribeiro Jr
Cc: r-sig-geo@stat.math.ethz.ch
Subject: Re: [R-sig-Geo] kriging
Ok,
What about higher order polynomials? I have fitted one using a gam to
Ok,
What about higher order polynomials? I have fitted one using a gam to
the data which which helps to normalize the residuals, and reduce the
variance of the residuals.
Is it simply a matter of plugging in the function into the gstat command
line? Or is it simpler to krig the residuals and th
Dave,
what is necessary for UK is a relation expressed by a linear model, not
necessaraly a linear relation between the variables.
e.g. you could have a second degree polinomial and still work within the
scope of universal kriging.
On Mon, 16 Jun 2008, Dave Depew wrote:
> Hi all,
> I have a dat
Hi all,
I have a data set that I would like to krige to interpolate between
transects. There is a non-linear trend between two of the variables...my
impression from reading the gstat help file is that there must be a
linear relationship between the data to use universal kriging?
Second, would a
On Mon, 5 May 2008, Edzer Pebesma wrote:
Dave Depew wrote:
Thanks,
This worked.
I'm still confused why the if else statement didn't work...
If one wanted to do conditional arithmetic would a for statement bee
needed?
e.g.
meuse.grid[["class"]] = for(i in 1:length(meuse.grid[["dist"]])
Dave Depew wrote:
Thanks,
This worked.
I'm still confused why the if else statement didn't work...
If one wanted to do conditional arithmetic would a for statement bee
needed?
e.g.
meuse.grid[["class"]] = for(i in 1:length(meuse.grid[["dist"]])){
if (meuse.grid[["dist"]]<0.5)
{meuse.grid[["
Thanks,
This worked.
I'm still confused why the if else statement didn't work...
If one wanted to do conditional arithmetic would a for statement bee needed?
e.g.
meuse.grid[["class"]] = for(i in 1:length(meuse.grid[["dist"]])){
if (meuse.grid[["dist"]]<0.5)
{meuse.grid[["class"]]=10*meuse.gri
Dave Depew wrote:
Hi all,
I've got a question regarding kriging outputs. I have an interpolated
dataset which due to the nugget effect contains some negative values
as the predictions. I would like to truncate these @ "0", rather than
having them as a negative prediction.
I've tried something
Hi all,
I've got a question regarding kriging outputs. I have an interpolated
dataset which due to the nugget effect contains some negative values as
the predictions. I would like to truncate these @ "0", rather than
having them as a negative prediction.
I've tried something similar with the m
Rogers,
It worked great, the function writeAsciiGrid() from maptools. My goal
was to export it as Arc ASCII file.
Thanks,
Jose
On Sun, Mar 2, 2008 at 3:51 PM, Roger Bivand <[EMAIL PROTECTED]> wrote:
> On Fri, 29 Feb 2008, Jose Funes wrote:
>
> > Dear members,
> >
> > I have tried to export a
Hi all...
Is there a package that can match two sets of spatial points? I have an
old set of files that were digitized into a local coordinate system, and
a newer set of files that have been gps'd. The IDs between the two
don't match, there may be more points in the gps'd data, and of course,
the
On Fri, 29 Feb 2008, Jose Funes wrote:
> Dear members,
>
> I have tried to export a kriging map to arcgis as asciigrid or image.
> I have used the functions write.asciigrid and writeRast6sp(grass), in
> both cases any success; In the former when exporting it, I got the
> following message " Asciig
Dear members,
I have tried to export a kriging map to arcgis as asciigrid or image.
I have used the functions write.asciigrid and writeRast6sp(grass), in
both cases any success; In the former when exporting it, I got the
following message " Asciigrid does not support grids with non-square
cells".
tical analysis, properly conducted, is a delicate dissection of
uncertainties, a surgery of suppositions. ~M.J.Moroney
> -Oorspronkelijk bericht-
> Van: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] Namens Robert Helber
> Verzonden: donderdag 26 juli 2007 22:25
> Aan: R geo
I am attempting to krige a very large 2D region using the geoR package
(http://cran.ssds.ucdavis.edu/). The geoR kriging works well for
regions that have stationary data. My big region has areas where the
trend and possibly the variogram changes. Because of this I am trying
to split up the b
On Sat, 20 Jan 2007, epifanio wrote:
> Hi,
> i've tryed to delete the "\" backslash,
> now i've a different error, at the same line :
>
> > grd <- GridTopology(cellcentre.offset=c(G$west+(G$ewres/2), G$south
> +(G$nsres/2)), cellsize=c(G$ewres, G$nsres), cells.dim=c(G$cols, G
> $rows));
> Err
Hi,
i've tryed to delete the "\" backslash,
now i've a different error, at the same line :
> grd <- GridTopology(cellcentre.offset=c(G$west+(G$ewres/2), G$south
+(G$nsres/2)), cellsize=c(G$ewres, G$nsres), cells.dim=c(G$cols, G
$rows));
Errore in validObject(.Object) : invalid class "GridTopol
On Fri, 19 Jan 2007, epifanio wrote:
> hi i've some problem to do a tutorial on the kriging
> interpolation
> i found instruction on how to interpolate the srtm data to
> increase the resolution :
>
> http://grass.itc.it/newsletter/GRASS_OSGeo_News_vol4.pdf
>
>
hi i've some problem to do a tutorial on the kriging
interpolation
i found instruction on how to interpolate the srtm data to
increase the resolution :
http://grass.itc.it/newsletter/GRASS_OSGeo_News_vol4.pdf
at page 20 ... at the line :
grd <- Grid
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