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), but I have not found an easily accessible implementation. Is anybody aware of a solution in R?
Best,
Martin
@article{Rathbun:1998aa,
Author = {Rathbun, Stephen L.},
Journal = {Environmetrics},
Number = {2},
Pages = {109--129},
Title = {Spatial modelling in irregularly shaped regions: kriging estuaries},
Volume = {9},
Year = {1998}}
@article{Little:1997aa,
Author = {Little, Laurie S. and Edwards, Don and Porter, Dwayne E.},
Journal = {Journal of Experimental Marine Biology and Ecology},
Number = {1},
Pages = {1--11},
Title = {Kriging in estuaries: as the crow flies, or as the fish swims?},
Volume = {213},
Year = {1997}}
Martin Renner
US Geological Survey
Alaska Science Center
kriging as fish swim, not as crows fly
10 messages · Martin Renner, Michael Sumner, Pilar Tugores Ferra +3 more
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 estimation and probably not easily applied. Is location uncertainty a big issue for your data? What are the input locations? Cheers, Mike. On Wed, Jan 27, 2010 at 7:06 PM, Martin Renner
<martin.renner at stonebow.otago.ac.nz> wrote:
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), but I have not found an easily accessible implementation. Is anybody aware of a solution in R?
Best,
Martin
@article{Rathbun:1998aa,
? ? ? ?Author = {Rathbun, Stephen L.},
? ? ? ?Journal = {Environmetrics},
? ? ? ?Number = {2},
? ? ? ?Pages = {109--129},
? ? ? ?Title = {Spatial modelling in irregularly shaped regions: kriging estuaries},
? ? ? ?Volume = {9},
? ? ? ?Year = {1998}}
@article{Little:1997aa,
? ? ? ?Author = {Little, Laurie S. and Edwards, Don and Porter, Dwayne E.},
? ? ? ?Journal = {Journal of Experimental Marine Biology and Ecology},
? ? ? ?Number = {1},
? ? ? ?Pages = {1--11},
? ? ? ?Title = {Kriging in estuaries: as the crow flies, or as the fish swims?},
? ? ? ?Volume = {213},
? ? ? ?Year = {1997}}
Martin Renner
US Geological Survey
Alaska Science Center
_______________________________________________ R-sig-Geo mailing list R-sig-Geo at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-geo
Hi, Martin Two years ago there was a similar discussion on the list: http://markmail.org/message/tw7ulpxbgixieyys If I understand it properly, your problem is you need to compute your variogram using non-euclidian distances. As far as I know, there is no package in R that can do so (correct me if I am wrong). There is a function LCP_Krige that I think you can find on the net. It is not an R function but a mixture of ArcGis 8.x and Matlab. Maybe you can use it or try to adapt it to R... Jensen, OP, MC Christman and TJ Mller. 2006. Landscape-based geostatistics: a case study of the distribution of blue crab in Chesapeake Bay. Envirometrics. 17:605-621. I was interested in applying this sort of analysis but I didn't suceed. I hope you are more lacky! Cheers, Pilar M? Pilar Tugores Ferr? PhD Student Instituto Espa?ol de Oceanograf?a Centro Oceanogr?fico de Baleares Muelle de Poniente s/n 07015 Palma de Mallorca Baleares, Espa?a Telf.: (34) 971 133759 -----Mensaje original----- De: r-sig-geo-bounces at stat.math.ethz.ch [mailto:r-sig-geo-bounces at stat.math.ethz.ch] En nombre de Michael Sumner Enviado el: 27 January 2010 10:29 Para: Martin Renner CC: r-sig-geo at 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 similar features, but they are particularly focussed on individual track estimation and probably not easily applied. Is location uncertainty a big issue for your data? What are the input locations? Cheers, Mike. On Wed, Jan 27, 2010 at 7:06 PM, Martin Renner
<martin.renner at stonebow.otago.ac.nz> wrote:
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), but I have not found an easily accessible implementation. Is anybody aware of a solution in R?
Best,
Martin
@article{Rathbun:1998aa,
? ? ? ?Author = {Rathbun, Stephen L.},
? ? ? ?Journal = {Environmetrics},
? ? ? ?Number = {2},
? ? ? ?Pages = {109--129},
? ? ? ?Title = {Spatial modelling in irregularly shaped regions: kriging estuaries},
? ? ? ?Volume = {9},
? ? ? ?Year = {1998}}
@article{Little:1997aa,
? ? ? ?Author = {Little, Laurie S. and Edwards, Don and Porter, Dwayne E.},
? ? ? ?Journal = {Journal of Experimental Marine Biology and Ecology},
? ? ? ?Number = {1},
? ? ? ?Pages = {1--11},
? ? ? ?Title = {Kriging in estuaries: as the crow flies, or as the fish swims?},
? ? ? ?Volume = {213},
? ? ? ?Year = {1997}}
Martin Renner
US Geological Survey
Alaska Science Center
_______________________________________________ R-sig-Geo mailing list R-sig-Geo at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-geo
_______________________________________________ R-sig-Geo mailing list R-sig-Geo at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-geo
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 those "customized" distances. Both the GRASS script for computing distances and the modified geoR library are open source and available at http://www.geeitema.org/guenmap/index.jsp?opcion=resultados I hope it helps. ?acu.- Martin Renner escribi?:
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), but I have not found an easily accessible implementation. Is anybody aware of a solution in R?
Best,
Martin
@article{Rathbun:1998aa,
Author = {Rathbun, Stephen L.},
Journal = {Environmetrics},
Number = {2},
Pages = {109--129},
Title = {Spatial modelling in irregularly shaped regions: kriging estuaries},
Volume = {9},
Year = {1998}}
@article{Little:1997aa,
Author = {Little, Laurie S. and Edwards, Don and Porter, Dwayne E.},
Journal = {Journal of Experimental Marine Biology and Ecology},
Number = {1},
Pages = {1--11},
Title = {Kriging in estuaries: as the crow flies, or as the fish swims?},
Volume = {213},
Year = {1997}}
Martin Renner
US Geological Survey
Alaska Science Center
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 help! Best, Martin
On 28 Jan 2010, at 03:42 , Facundo Mu?oz wrote:
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 those "customized" distances. Both the GRASS script for computing distances and the modified geoR library are open source and available at http://www.geeitema.org/guenmap/index.jsp?opcion=resultados I hope it helps. ?acu.- Martin Renner escribi?:
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), but I have not found an easily accessible implementation. Is anybody aware of a solution in R?
Best,
Martin
@article{Rathbun:1998aa,
Author = {Rathbun, Stephen L.},
Journal = {Environmetrics},
Number = {2},
Pages = {109--129},
Title = {Spatial modelling in irregularly shaped regions: kriging estuaries},
Volume = {9},
Year = {1998}}
@article{Little:1997aa,
Author = {Little, Laurie S. and Edwards, Don and Porter, Dwayne E.},
Journal = {Journal of Experimental Marine Biology and Ecology},
Number = {1},
Pages = {1--11},
Title = {Kriging in estuaries: as the crow flies, or as the fish swims?},
Volume = {213},
Year = {1997}}
Martin Renner
US Geological Survey
Alaska Science Center
An embedded and charset-unspecified text was scrubbed... Name: not available URL: <https://stat.ethz.ch/pipermail/r-sig-geo/attachments/20100129/60472567/attachment.pl>
An embedded and charset-unspecified text was scrubbed... Name: not available URL: <https://stat.ethz.ch/pipermail/r-sig-geo/attachments/20100129/c5f83b9f/attachment.pl>
Another approach that might be simpler (or it may oversimplify and not give good results) is to compute the distances between your points as the fish swim, then use multi dimensional scaling (cmdscale function or others) to get a set of points that represent those distances and do the rest of your analysis on the transformed points.
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111
> -----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 Martin Renner
> Sent: Wednesday, January 27, 2010 1:07 AM
> To: r-sig-geo at 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 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), but I have not found an easily accessible implementation.
> Is anybody aware of a solution in R?
>
> Best,
> Martin
>
>
>
> @article{Rathbun:1998aa,
> Author = {Rathbun, Stephen L.},
> Journal = {Environmetrics},
> Number = {2},
> Pages = {109--129},
> Title = {Spatial modelling in irregularly shaped regions: kriging
> estuaries},
> Volume = {9},
> Year = {1998}}
>
> @article{Little:1997aa,
> Author = {Little, Laurie S. and Edwards, Don and Porter, Dwayne
> E.},
> Journal = {Journal of Experimental Marine Biology and Ecology},
> Number = {1},
> Pages = {1--11},
> Title = {Kriging in estuaries: as the crow flies, or as the fish
> swims?},
> Volume = {213},
> Year = {1997}}
>
>
>
>
> Martin Renner
> US Geological Survey
> Alaska Science Center
>
> _______________________________________________
> R-sig-Geo mailing list
> R-sig-Geo at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
Hi Gregory, An ingenious idea! I guess it would work but I'd be a little bit concerned about the alignment of the predicted surface. For now, I'll try Facu's method and see how that goes. Best, Martin
On 29 Jan 2010, at 08:11 , Greg Snow wrote:
Another approach that might be simpler (or it may oversimplify and not give good results) is to compute the distances between your points as the fish swim, then use multi dimensional scaling (cmdscale function or others) to get a set of points that represent those distances and do the rest of your analysis on the transformed points. -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare greg.snow at imail.org 801.408.8111
-----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 Martin Renner
Sent: Wednesday, January 27, 2010 1:07 AM
To: r-sig-geo at 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 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), but I have not found an easily accessible implementation.
Is anybody aware of a solution in R?
Best,
Martin
@article{Rathbun:1998aa,
Author = {Rathbun, Stephen L.},
Journal = {Environmetrics},
Number = {2},
Pages = {109--129},
Title = {Spatial modelling in irregularly shaped regions: kriging
estuaries},
Volume = {9},
Year = {1998}}
@article{Little:1997aa,
Author = {Little, Laurie S. and Edwards, Don and Porter, Dwayne
E.},
Journal = {Journal of Experimental Marine Biology and Ecology},
Number = {1},
Pages = {1--11},
Title = {Kriging in estuaries: as the crow flies, or as the fish
swims?},
Volume = {213},
Year = {1997}}
Martin Renner
US Geological Survey
Alaska Science Center
_______________________________________________ R-sig-Geo mailing list R-sig-Geo at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-geo
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.org/doc/guenmap/docs/distances.gif Here, three types of distances between all pairs from a set of points are compared. The reference distance (red) is the "cost based" distance (or "water distance"), which is the minimum distance measured within the "permisible" region (i.e. "as the fish swims"). In black are represented the corresponding euclidean distances, while in blue, the corresponding MDS distances (in 2D). As you can see, the MDS approach corrects the "bias" in the long terrm. However the variability around the "correct" value holds. So, while it provides the best overall euclidean approximation, it does not account for the behaviour due to the shape of the region. Since the latter was what we was looking for, we discarded this approach. One could try to use MDS with higher dimension. But it does not improve things very much, specially if you have regions with "holes". Distances in such regions don't have an euclidean representation regardless of the dimension. Bests ?acu.- Greg Snow escribi?:
Another approach that might be simpler (or it may oversimplify and not give good results) is to compute the distances between your points as the fish swim, then use multi dimensional scaling (cmdscale function or others) to get a set of points that represent those distances and do the rest of your analysis on the transformed points.