[R-sig-Geo] regression kriging with non-euclidean distances

[Michael Sumner]

The soap package that accompanies mgcv may be of interest:

http://www.maths.bath.ac.uk/~sw283/simon/software.html

Cheers, Mike.


Alisa Coffin wrote:
> Don & Facundo,
>
> This is something that I'm interested in as well for coastal marine
> applications.
>
> The only solution I've found so far is a cumbersome "barrier" function
> available in the kriging operation of ArcGIS. I would be interested in
> seeing an (better) implementation of the idea in R.
>
> I was able to find a few references on the subject that I pass along to you
> and anyone else that might find it useful:
>
> Krioruchko, K. and A. Gribov. 2002. Geostatistical interpolation and
> simulation in the presence of barriers. X. Sanchez-Vila et al. (eds.), *geoENV
> IV -- Geostatistics for Environmental Applications,* pp. 331-342. Kluwer
> Academic Publishers: the Netherlands.
>
> Curriero, F.C. 1997. The use of non-Euclidean distances in geostatistics,
> PhD thesis.
>
> Little, LS, D Edwards and DE Porter. 1997. Kriging in estuaries: as the crow
> flies or as the fish swims? Journal of experimental marine biology and
> ecology. 213:1-11.
>
> Rathbun, S. 1998. Spatial modeling in irregularly shaped regions: kriging
> estuaries. Envirometrics. 9:109-129.
>
> 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.
>
> Regards,
>
> Alisa Coffin
>
>
> On Thu, Mar 20, 2008 at 2:42 PM, Don MacQueen <macq at llnl.gov> wrote:
>
>   
>> Facundo,
>>
>> I am interested in essentially the same thing,
>> though my application is inside buildings. I am
>> wondering what technique(s), software, etc. you
>> would be using to calculate your distances.
>>
>> I asked about this about a month ago, here on
>> r-sig-geo, and received some helpful replies. The
>> subject line at that time was
>>    [R-sig-Geo] Shortest path around obstacles (OT)
>>
>> -Don
>>
>> At 7:05 PM +0100 3/20/08, Facundo Muñoz wrote:
>>     
>>> Hello All,
>>>
>>> I'm performing  regression kriging (using both gstat and geoR)  in an
>>> urban environment. Thus, i have discontinuities (buildings) in the
>>> prediction space which make distances to be non-euclidean.
>>>
>>> I need to estimate variogram and make predictions using distances
>>> calculated by myself and passed to the algorithms (say, in a distance
>>> matrix), instead of letting them calculate distances based on
>>>       
>> coordinates.
>>     
>>> ¿Has anyone faced this issue before?
>>>
>>> Thanks in advance,
>>>     Facundo Muñoz
>>>
>>> --
>>> Departament d'Estadística i Investigació Operativa Universitat de
>>> València (Estudi General)
>>> Facultat de Matemàtiques, Dr. Moliner 50, 46100 Burjassot, Spain.
>>> (+34) 96 354 3987, fax: (+34) 96 354 3238
>>> e-mail: Facundo.Munoz at uv.es, web: http://www.uv.es/~famarmu/<http://www.uv.es/%7Efamarmu/>
>>>
>>> _______________________________________________
>>> R-sig-Geo mailing list
>>> R-sig-Geo at stat.math.ethz.ch
>>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>>>       
>> --
>> --------------------------------------
>> Don MacQueen
>> Environmental Protection Department
>> Lawrence Livermore National Laboratory
>> Livermore, CA, USA
>> 925-423-1062
>>
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