Loading ...
Sorry, an error occurred while loading the content.

Re: [ai-geostats] Uncertainty of Conditional Stochastic Simulated results

Expand Messages
  • Pierre Goovaerts
    Hi Feng, You are in the ideal situation where it would make sense to separate the two populations and do the variography and simulation separately for each
    Message 1 of 2 , Oct 10, 2004
    • 0 Attachment
      Hi Feng,

      You are in the ideal situation where it would make sense
      to separate the two populations and do the variography
      and simulation separately for each stratum, since clearly
      the pattern of variability of soil carbon is expected to be
      different under these two landcovers (I am sure that besides the
      variance, the range and nugget effect must be pretty different)
      and also the average C concentration should vary a lot .
      In most situations it is difficult to consider different populations since:
      1. we might not have enough data within each stratum to compute a
      reliable variogram,
      2. the boundaries of the different strata might be fuzzy,
      3. the multi strata approach creates discontinuities in the map
      that are not physically realistic.
      I don't know your data but I am pretty sure that none of these limitations
      apply.

      Now to answer your question, the use of a single semivariogram implies
      an assumption of stationarity, hence the fact that the
      variance/covariance does not depend on the location within the study area,
      which is clearly not your case. Even wen using a single variogram,
      the variability in your simulated map will be influenced to some
      extent by your data (conditioning observations). Hence, I suspect
      that more variability will appear on woodland anyways.
      By analogy, the same happens when you use an isotropic semivariogram
      in simulation/estimation, while the data display strong anisotropy.
      The simulated/estimated map will display some anisotropy, which is
      always reassuring.

      Cheers,

      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: goovaert@...
      Phone: (734) 668-9900
      Fax: (734) 668-7788
      http://alumni.engin.umich.edu/~goovaert/

      <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>

      On Sun, 10 Oct 2004, Feng Liu wrote:

      > Dear List:
      >
      > I got a question about the uncertainty associated with the Conditional
      > Stochastic Simulated results, the question is:
      >
      > I have soil C data for a sample area, within that area, there are woodland
      > and grassland. The variance of C data in woodland is higher than that in the
      > grassland. Now I want to use Conditional Stochastic Simulation to simulate a
      > bunch of images of soil C on the area. I will use one single variogram model
      > to do the simulation. The questions is: Do the estimated C data more
      > variable under woodland than those under grassland (simulated soil C data in
      > woodland have a larger variance than those in grassland)? or a single
      > variogram model means uniform or random variance of simulated data?
      >
      > Thank you very much
      >
      > Feng Liu
      > Graduate Student
      > Texas A&M University
      >
      >
      >
      >
    Your message has been successfully submitted and would be delivered to recipients shortly.