Modeling Complex Forest Ecology in a Parallel Computing Infrastructure Metadata

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  • Main Title Modeling Complex Forest Ecology in a Parallel Computing Infrastructure


  • Author: Mayes, John
    Creator Type: Personal


  • Chair: Mikler, Armin R.
    Contributor Type: Personal
    Contributor Info: Major Professor
  • Committee Member: Boukerche, Azzedine
    Contributor Type: Personal
  • Committee Member: Tarau, Paul
    Contributor Type: Personal
  • Committee Member: Jacob, Roy T.
    Contributor Type: Personal


  • Name: University of North Texas
    Place of Publication: Denton, Texas


  • Creation: 2003-08
  • Digitized: 2003-08-28


  • English


  • Content Description: Effective stewardship of forest ecosystems make it imperative to measure, monitor, and predict the dynamic changes of forest ecology. Measuring and monitoring provides us a picture of a forest's current state and the necessary data to formulate models for prediction. However, societal and natural events alter the course of a forest's development. A simulation environment that takes into account these events will facilitate forest management. In this thesis, we describe an efficient parallel implementation of a land cover use model, Mosaic, and discuss the development efforts to incorporate spatial interaction and succession dynamics into the model. To evaluate the performance of our implementation, an extensive set of simulation experiments was carried out using a dataset representing the H.J. Andrews Forest in the Oregon Cascades. Results indicate that a significant reduction in the simulation execution time of our parallel model can be achieved as compared to uni-processor simulations.


  • Library of Congress Subject Headings: Forest ecology -- Computer simulation.
  • Keyword: Simulation
  • Keyword: parallel simulation
  • Keyword: forest simulation
  • Keyword: semi-Markov


  • Name: UNT Theses and Dissertations
    Code: UNTETD


  • Name: UNT Libraries
    Code: UNT


  • Rights Access: public
  • Rights License: copyright
  • Rights Holder: Mayes, John
  • Rights Statement: Copyright is held by the author, unless otherwise noted. All rights reserved.

Resource Type

  • Thesis or Dissertation


  • Text


  • OCLC: 53362789
  • Archival Resource Key: ark:/67531/metadc4305


  • Degree Name: Master of Science
  • Degree Level: Master's
  • Degree Discipline: Computer Science
  • Academic Department: Department of Computer Science
  • Degree Grantor: University of North Texas