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

AI-GEOSTATS: Generating an autocorrelated random error field.

Expand Messages
  • mfrehner@geo.unizh.ch
    Hi everybody I m writing a diploma thesis about error propagation in digital terrain models and I want to use monte carlo methods to simulate elevation errors
    Message 1 of 1 , May 24, 2002
    • 0 Attachment
      Hi everybody

      I'm writing a diploma thesis about error propagation in digital terrain
      models and I want to use monte carlo methods to simulate elevation errors
      in the data points and their effect on various gis operations.

      My data are irregularly distributed points (not grid data!) which I
      triangulated using java as programming language. I found lots of
      suggestions in literature how to simulate autocorrelated error fields
      (Heuvelink, Ehlschlaeger, Goodchild, Wechsler,
      Haining/Griffith/Bennet) but as far as I was able to understand them the
      only practicable two (for my task) where:

      1) Generating uncorrelated random field and swapping until a
      predefined
      level of autocorrelation (Moran's I) is reached. (Goodchild, 1980)

      2) Same as 1) but prior to swapping the random numbers have to pass a
      series of statistical tests like a test for
      multivariate-normality. (Haining, Griffith, Bennet, 1983)


      Am I right saying that I need measured errors at some points if i want to
      apply interpolation techniques to simulate an autocorrelated error
      field? (Ehlschlaeger (1994) used a formula depending on the spatial
      autocorrelative effect) I'm asking that, because the only thing I have is
      the RMSE which is 0.4 m. I haven't got the points from which this error
      was empirically derived. But I could randomly set a few start points and
      derive all other points from them.

      So my first question is:
      What technique shall I apply to simulate an autocorrelated random error
      field?


      My second set of questions is:
      How can I determine suitable parameters for the error fields
      autocorrelation? What is the minimum distance of spatial independence? How
      should I determine a suitable distance decay exponent if I haven't got any
      sample error points to estimate a variogram from?


      I hope my questions are not too stupid and thanks for any help!
      Marcel



      --
      * 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.