Chaosheng, I agree with Pierre that if your only goal is to generate a probability map, then IK is faster and more straightforward than simulation and that MG kriging will give the same results, faster, than MG simulation.
However, we have found a couple of practical reasons where it may be advantageous to use simulation for soil contamination studies, so I'll add my two cents worth to this discussion: 1) When trying to explain the concepts of spatial variability and uncertainty, we have found that showing example realizations of what the possible distribution of contaminants could look like provides the groups involved to get a more intuitive understanding of these ideas. People understand the idea of flipping a coin 100 times to get the probability of heads or tails, but have a hard time visualizing in their mind what a "coin flip" looks like in a 2-D soil contamination problem. Showing some example conditional realizations gives them a stronger feel for the nature of the answers geostats is providing to their questions. 2) A number of sites are in the process of designing chemical and/or mechanical treatment systems for the soil that will be removed from the site while the remediation map is being determined. One set of design parameters for these treatment systems is the best and worst case estimates of the total amount of contamination (curies, grams, etc.) contained in the soil at the site. These best/worst case estimates depend on the joint estimate of the contamination at all locations across the site. This is something simulation provides, but kriging doesn't. 3) For soils with radioactive contaminants, there are a number of different sensors (e.g., a gamma detector mounted several meters off the ground) being deployed at field sites that integrate the activity of the contaminant over a larger area/volume. Simulation of the fine scale distribution of the activity can be useful in looking at how these sensors scale up the activity values to the integrated measurement. Also when looking at IK vs MG kriging (or simulation) keep in mind that rarely do the client, stakeholder(s) and regulator(s) have a single action level or threshold that they have all agreed to for application at the site. There are usually multiple thresholds corresponding to different future-land use scenarios and different health risk models. If creating the probabilty maps through IK then each different threshold requires a new set of indicator variograms. If you use MG kriging or simulation, you only need do the variography once-keep in mind that the MG assumption does have other problems with connectivity of extreme values that may or may not be important in your application (this is generally a bigger concern in fluid flow problems than in soil contamination problems). I'll add my thanks to Gregoire for 7 years of superb work! Sean Sean A. McKenna Ph.D. Geohydrology Department Sandia National Laboratories PO Box 5800 MS 0735 Albuquerque, NM 87185-0735 ph: 505 844-2450 -----Original Message----- From: Chaosheng Zhang [mailto:[EMAIL PROTECTED]] Sent: Monday, April 29, 2002 3:57 AM To: Pierre Goovaerts Cc: [EMAIL PROTECTED]; Dave McGrath Subject: Re: AI-GEOSTATS: Risk Assessment with Gaussian Simulation? Pierre, Thanks for the comments. It's my first time to use Gaussian simulation to do something possibly useful, and I have also found the calculation quite slow even though the speed of my computer is not so bad. I'm using Idrisi 32 (with GStat), and the grid is about 500*500. What I worry about is that how useful these realizations are? Obviously they are not "realistic" even though some people say they want to produce a more realistic map, instead of the smoothed Kriging map. Another concern is that the probability map produced based on these realisations may not be so good as the PCLASS (available in Idrisi), as PCLASS may have a better probability background or clearer assumption. In PCLASS, the square root (not sure yet???) of Kriging variances can be used as the RMS (root mean square) or standard deviation of the pixel corresponding to the Kriging map, and the probability > a threshold can be calculated based on the normal assumption. More comments and suggestions will give me more confidence in doing the risk assessment (heavy metal pollution in soils of a mine area). Cheers, Chaosheng ----- Original Message ----- From: "Pierre Goovaerts" <[EMAIL PROTECTED]> To: "Chaosheng Zhang" <[EMAIL PROTECTED]> Cc: <[EMAIL PROTECTED]>; "Dave McGrath" <[EMAIL PROTECTED]> Sent: Saturday, April 27, 2002 4:53 PM Subject: Re: AI-GEOSTATS: Risk Assessment with Gaussian Simulation? > Hello, > > In the past few years stochastic simulation has > been increasingly used to produce probability maps. > To my opinion it's generally a waste of CPU time since > similar information can be retrieved using kriging, > either in a multiGaussian framework or applied to > indicator transforms. > The issue of when using simulation vs kriging > is further discussed in: > Goovaerts, P. 2001. > Geostatistical modelling of uncertainty in soil science. > Geoderma, 103: 3-26. > > I take this opportunity to thank Gregoire > for a remarkable and often challenging job > of keeping this e-mail list alive through the years. > > Pierre > <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><> <><> > > ________ ________ > | \ / | Pierre Goovaerts > |_ \ / _| Assistant professor > __|________\/________|__ Dept of Civil & Environmental Engineering > | | The University of Michigan > | M I C H I G A N | EWRE Building, Room 117 > |________________________| Ann Arbor, Michigan, 48109-2125, U.S.A > _| |_\ /_| |_ > | |\ /| | E-mail: [EMAIL PROTECTED] > |________| \/ |________| Phone: (734) 936-0141 > Fax: (734) 763-2275 > http://www-personal.engin.umich.edu/~goovaert/ > > <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><> <><> > > > On Sat, 27 Apr 2002, Chaosheng Zhang wrote: > > > Dear list, > > > > First, I would like to say thank you to Gregoire for keeping this list alive. > > > > I'm trying to do "risk assessment", and I have some questions about risk assessment with Gaussian Simulation: > > > > (1) How to produce a probability map? > > > > With Gaussian simulation, we can produce many maps/realisations, e.g., 100. Based on the 100 maps, a probability map of higher than a threshold can be produced. I wonder how to produce such a probability map? My understanding is that for each pixel, we just count how many values out of the 100 are >threshold, and the number is regarded as the "probability". Am I right? It seems that this is a time consuming procedure with GIS map algebra. Are there any suggestions for a quick calculation? > > > > (2) Is a probability map better than a Kriging interpolated map for the purpose of risk assessment? > > > > (3) Is "PCLASS" function in IDRISI 32 Release 2 better/easier than the probability map from Gaussian simulation? > > > > >From the online help of IDRISI 32 R2, Section "Kriging and Simulation Notes", it says "If the final goal of simulated surfaces will be to directly reclassify the surfaces by a threshold value, and calculate a probability of occurrence for a process based on that threshold, conditional simulation may be unnecessary. Instead kriging and variance images may be created and then used together with PCLASS." Any comments? > > > > (4) How to carry out "PCLASS"? > > > > Following the above question, I have a problem in doing PCLASS. I cannot input the file name of Kriging variance to the field of "Value error" of the documentation file. It seems that this field only accepts a "value", not an "image file name" or anything in text. Anyone has the experience? > > > > Cheers, > > > > Chaosheng Zhang > > ================================================= > > Dr. Chaosheng Zhang > > Lecturer in GIS > > Department of Geography > > National University of Ireland > > Galway > > IRELAND > > > > Tel: +353-91-524411 ext. 2375 > > Fax: +353-91-525700 > > Email: [EMAIL PROTECTED] > > [EMAIL PROTECTED] > > Web: http://www.nuigalway.ie/geography/zhang.html > > ================================================= > > > > > > -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. 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