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GEOSTATS: Summary: Kriging with Barriers

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  • Steve Friedman
    What a great group of folks, thank you all for the suggestions. In essense the solution is to do either 1 or 2 things. 1. Use an indicator kriging methodology
    Message 1 of 1 , Apr 23, 1999
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      What a great group of folks, thank you all for the suggestions.

      In essense the solution is to do either 1 or 2 things.

      1. Use an indicator kriging methodology coding the surface
      area for 1 = terrestrial sites, and 0 = aquatic sites. Krige the
      trees across the entire surface using the indicator surface to
      weight the solution. Only terrestrial sites should be returned

      2. Krige the entire surface without an indicator surface, then use
      a clipping coverage to remove the aquatic sites, leaving only the
      terrestrial portion of the region.

      Thanks again
      Steve F.
      ..................................................................................................

      postings from the kind folks who shed some light on my little corner
      of the world.

      from Ulrich Leopold

      there is a possibility in SURFER 6.0 (low cost software for MS-DOS
      and WINDOWS platform). You can perform interpolations in SURFER or
      another geostatistical software. You can create a base map with all
      your digital boundaries. This map can be used to blank your
      interpolated result grid inside or outside those boundaries. You have
      to define it.

      If you use another geostatistical software (better decision), you
      need an ascii column grid as output with the interpolated results.
      X Y Z
      1 2 3
      1 3 3
      : : :
      . . .
      If you just have Z but not the coordinates you need to add
      them to the grid points and have to convert it to an SURFER
      ascii-grid. Both can be done by 3PLOT (freeware; ai-geostat software
      page). Then you can blank this SURFER grid with your base map in
      SURFER and map it.

      >from Tiina.
      One thing you could try, is masking out of areas with lakes if you use
      any GIS tool. I only have experience with Arc/Info.
      Arc/Info kriging routines are not good. You could make the interpolated
      surface first with some other software. Then import the datafile in
      Arc/Info ( or other GIS-tool ) and create a cover of it, also creating a

      cover for lakes. (Have you got access to a digitized map over lakes? Yoy

      can import it in Arc/Info and make a cover.)
      After that , it is simple map algebra;
      Forestcover = Allcover - Lakecover.
      Something like that should be possible to do with other tools as well.
      Good luck!
      Tiina.

      > from eric j. lorup

      is landcover of same class everywhere and do the trees spread through
      some
      mechanism that easily allows for modelling of autocorrelation? Otherwise

      there would be other factors (such as soil type, areas not suitable for
      tree
      growing, ...) determining the distribution of the trees across your
      landscape. So this will decide upon choice of Kriging method.

      Re the lakes I don't have enough experience. All that came to my mind
      was
      the Kriging implementation in Arc/Info which, if I remember it right.
      allows
      for including of breakelines or borders or anything like this. But
      Arc/Info
      is by no means a real geostatistical tool :-)

      There's other software out there, check the software list maintained by
      Gregoire Dubois at:

      http://curie.ei.jrc.it/software/index.htm

      Kind regards
      eric j. lorup

      Steve Few
      I discussed this problem with my wife (from Minnesota) this weekend. As
      I
      drive through Mn going to Milacs or Bay Lake in during the summer, I
      wondered how in the world you would handle those patches of trees
      between lakes.

      I keep going back to the problem (ignoring scale) of breaking your State

      into different pieces. The lack of continuity in the "h" vectors, the
      distances (gap caused by lake milacs) are substantial. Even the small
      lakes
      such as Bay Lake nearby can wipe out the continuity necessary to
      estimate a
      reasonable semivariogram.

      Breaking the Mn into pieces around big lakes, then make the big lakes
      the
      "center" of a region is one idea. Ignore the water, and do your
      neighborhood thing as distance from center of the big lakes. On small
      lakes, I would ignor the smallest ones, and do ??? Got me.

      I guess you're paving the way. I haven't done any real difficult
      spatial
      modeling (just spatial stat class), so, sorry I can't help any further.

      Steve Few
      Statistician, NC DENR (Air Quality)

      > Vera
      I would suggest to try indikator kriging on the variable
      presence-absence of lake and use it as a weighting function
      for the kriged estimates of the tree density.

      See Pawlowsky, Olea and Davis (1993), "Boundary assessment
      under uncertainty", Mathematical Geology, 25(2), p. 125-143,
      for details

      > John Kern
      I have dealt with this problem in many situations with other GIS folks.
      I
      am a statistician and often I will develop a spatial model and GIS
      people
      will display in ARC-Info or ARC/view etc. The problem you are
      encountering
      is really not a big issue as youcan go ahead and make predictions of the

      numbers or density of trees where there are lakes followed by clipping
      and
      or intersecting the forest coverage with the lakes coverage where you
      are
      interested in not lakes. Making the prediction of tree density on one
      pixel should have no influence on the predicted tree density on other
      pixels, so you can either use a complicated kriging algorithm which
      looks
      at the 2000 lakes to decide whether or not to make a prediction, or
      youcan
      use a simple kriging algorithm to develop the tree coverage everywhere,
      followed by using the power of the GIS to just eliminate unneeded
      predictions in the lakes. I hope this helps.

      > Gary Smith

      I tend to brute force this sort of thing by having a separate indicator
      data
      file that assigns all grid nodes to categories (in your case each node
      might
      have a 1 for lakes and a 2 for vegetated landscape). Then I write a
      short
      piece of code that loads both the kriging results and the indicator
      data
      file and then have the computer assign the kriged value to the node if
      the
      indicator at a node is for vegetated landscape, and to return some other

      sort of value if the indicator is for lakes such that when plotted, the
      lakes will show up in a different color than the vegetated landscape
      kriged
      values. Because your kriging, and not using some sort of sequential
      simulation, the fact that the estimator gives you a tree density number
      where there can't be any trees does not effect the outcome where there
      are
      trees. So, simply ignorring the kriging results where you know there is

      water shouldn't effect the validity of your assumptions.

      You may get a wiser answer from someone more into geostats than I, but
      this
      might be worth considering

      > Stephen Smith
      I am surprised that you didn't get any responses (even statements that
      there
      is no one way of doing it). People here have run up against these
      problems
      when kriging snow crab, surfclams, etc around shoals, islands etc. The
      only
      method that I have used is to define a polygon which defines the surface
      to
      be kriged and then kriged over the points in that polygon only (using
      poly.grid). The polygon excludes the areas where the animal can not
      exist.
      This ignores potential interface effects (e.g., beach, surf line).





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