Hi Samuel, I have dealt with similar problems when analyzing the spatial distribution of dioxin and other heavy metals in river sediments. Core lengths can strongly fluctuate from one sampling point to the next. The empirical approach I used was to weigh each sample proportionally to its length both in the computation of semivariograms (use of weighted semivariogram estimators) and in the kriging procedure (rescaling of kriging weights to account for core length). There was no publication on this approach and reports are confidential. These days I would use a less empirical approach and capitalize on the analogy with the treatment of cancer rates, where the reliability of rates is a function of the population size. You could still use weighted semivariogram estimator, but use a "kriging with measurement error" approach, whereby an error variance term (here inversely proportional to the length of the core) is added to the diagonal elemnts of the kriging matrix.
Here is just a suggestion but I am sure that some mining geostaticians will come up with a more elegant solution.. I also think that Jayme Gomez presented a paper on this issue (and the downscaling or disaggregation problem in general) at the last geostat congress in Banff, but since I only caught the last part of his presentation I might be wrong. Pierre <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><> Dr. Pierre Goovaerts President of PGeostat, LLC Chief Scientist with Biomedware Inc. 710 Ridgemont Lane Ann Arbor, Michigan, 48103-1535, U.S.A. E-mail: [EMAIL PROTECTED] Phone: (734) 668-9900 Fax: (734) 668-7788 http://alumni.engin.umich.edu/~goovaert/ <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><> On Tue, 26 Oct 2004, samuel verstraete wrote: > Hi, > > I have a 3D data set that has been sampled by a private company. They > lacked a complete knowledge of geostatistics so there is no sampling > "strategy" involved. Another thing is that the support of the samples is > strongly fluctuating. Horizontally the sampling support is constant and > can be considered as a point (about 70cm^2 compared to a few hectares) > Vertically the sampling support is not stable and rather "huge" in > comparison with the vertical scale... (sampling can be 0.10 to 1 meter > and maximum depth would be 5 to 6 meter or even less) > > I've read in the literature that there is a possibility to correct for > such a things, through regularization. But none of the literature seems > to discuss the possibility that the samples themself do not always have > the same support, as stated before samples can have a support that is 10 > times bigger than the smallest sample. > > Question is... Is there any other literature that discusses this matter > and even more importantly is there any software out there that can take > this sampling support into consideration when I'm calculating the > variogram or when I start with estimation/simulation of the field. > > > Thanks in advance, > > -- > Samuel Verstraete > Ghent University > Faculty of Bioscience Engineering > Dept. of Soil Management and Soil Care > Coupure Links 653, B-9000 Gent, Belgium > > > >
* By using the ai-geostats mailing list you agree to follow its rules ( see http://www.ai-geostats.org/help_ai-geostats.htm ) * To unsubscribe to ai-geostats, send the following in the subject or in the body (plain text format) of an email message to [EMAIL PROTECTED] Signoff ai-geostats
