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GEOSTATS: Re: cellular automata and geostatistics

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  • Sytze.deBruin@STAFF.GIRS.WAU.NL
    Hello, Here s a summary of the responses I received: Phaedon Kyriakidis pointed out that a cellular automata model can be regarded as a space-time Markov Chain
    Message 1 of 1 , Feb 14, 2000
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      Hello,

      Here's a summary of the responses I received:

      Phaedon Kyriakidis pointed out that a cellular automata model can be regarded
      as a space-time Markov Chain model.

      Olivier Jaquet gave me the following reference to a lattice gas model he
      developed for stochastic simulation of conduit networks that can be applied in
      hydrogeological modeling of karst aquifers:
      Jaquet O. (1997) Stochastic model of karstic conduit networks using lattice
      gas simulations, Geostatistics Wollongong '96, Volume 2, pp.1124-1133.

      Justin Quirouette directed me to to:
      http://aix1.uottawa.ca/academic/arts/geographie/lpcweb/sections1/software/frms
      oft.htm which contains free software and reports on spatial statistics and
      cellular automata (separately).

      Claudio Monteiro sent me a paper about a model in which a fuzzy inference
      engine and a cellular automata engine are combined:
      Miranda V., Monteiro C., "Fuzzy Inference in Spatial Load Forecasting",
      Proceedings of PES Winter Meeting 2000, Singapore, January 2000.

      There appeared to be more list members who are interested in the subject.

      Thanks,

      Sytze de Bruin
      Centre for Geo-Information
      Wageningen University
      P.O. Box 339
      6700 AH Wageningen
      The Netherlands
      Tel: +31 317 474636
      Fax: +31 317 474567

      << original message >>
      A simple cellular automaton is defined by a cell in a lattice, a discrete
      state space, a neighbourhood template and a local transition function. Cells
      can change their state in discrete time-steps. The transition rules can be
      deterministic or stochastic. Usually all cells change their state
      simultaneously (unlike SIS). Usually, state transitions only depend on the
      previous state of the cells and their neighbourhoods and possibly some local
      or global constraints.
      Does anybody have suggestions (literature, software, comments) for
      geostatistical approaches to modelling with cellular automata. I am
      particularly interested in the possibility of using cross-variograms derived
      from historical data.

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