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

AI-GEOSTATS: Kriging, Constraints

Expand Messages
  • Ursula Manns
    Dear Community, I would like to share some thoughts with you: I studied some datasets concerning plant distribution in arable fields: I found first of all a
    Message 1 of 2 , Oct 13, 2003
    • 0 Attachment
      Dear Community,

      I would like to share some thoughts with you: I studied some datasets
      concerning plant distribution in arable fields:

      I found first of all a large anisotropy.
      Secondly I found very large nugget effects, with a tendecy to have pure
      nugget effect sometimes.
      The distribution of the investigated phenomenon is non-gaussiang nature.
      The occurence of the phenomenon seems to be affected by several soil-
      fetiliser- and weather-related factors and not by the distance of vector
      (h)!

      Am I -from the statistical point of view- allowed to use kriging to
      interpolate these datasets or are their absoulte constraints for kriging
      under these suppositions ? I think I am not allowed to krige !?

      Ursula

      _________________________________________________________________



      --
      * To post a message to the list, send it to ai-geostats@...
      * 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 majordomo@... with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list
      * Support to the list is provided at http://www.ai-geostats.org
    • Isobel Clark
      Ursula I think there are a few things you can try before you abandon all hope of kriging. Certainly if you have nugget effects which are more than (say) 2/3rds
      Message 2 of 2 , Oct 13, 2003
      • 0 Attachment
        Ursula

        I think there are a few things you can try before you
        abandon all hope of kriging. Certainly if you have
        nugget effects which are more than (say) 2/3rds of the
        total sill you will get little or no validity from
        using a distance weighted method such as kriging.

        Possibilities you might like to look at:

        (1) normalise or otherwise transform your data. Highly
        skewed data, for example, will give you spurious
        anisotropies and relatively high nugget effects.

        (2) study the relationship with the external factors.
        Perhaps you could use kriging with external drift.

        Not all patterns have a distance relationship. The
        semi-variogram will tell you whether this assumption
        is correct, but only when calculated properly.
        Calculating a semi-variogram on data which is
        extremely non-Gaussian is counter productive!

        Isobel
        http://geoecosse.bizland.com/whatsnew.htm

        ________________________________________________________________________
        Want to chat instantly with your online friends? Get the FREE Yahoo!
        Messenger http://mail.messenger.yahoo.co.uk

        --
        * To post a message to the list, send it to ai-geostats@...
        * 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 majordomo@... with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list
        * Support to the list is provided at http://www.ai-geostats.org
      Your message has been successfully submitted and would be delivered to recipients shortly.