Spatial Dynamic Modeling of Tropical Forest Change

  • Author / Creator
    Chen, Jing
  • Traditional Land Use and Cover Change (LUCC) studies have focused on the change in attribute data (e.g., forest area, forest change rates, forest types, etc.) with few cases considering spatial data embedded in the dynamic process. However, LUCC varies with spatial and temporal dimensions in the real world, and these spatial dynamic features are considered to be indispensable in LUCC modeling. With the development of Geographical Information System (GIS) techniques and the increasing accessibility of Remote Sensing images, today we have the opportunity to study spatial dynamic modeling of LUCC and the related issues of spatiotemporal analyses. In this context, the goals of this dissertation are to undertake a retrospective analysis of tropical forest change (both forest loss and gain) in the Guanacaste region, Costa Rica; to explore its spatiotemporal features; to detect geographical factors which potentially act on forest loss/gain in the past 36 years (1979-2015); and then to reproduce and forecast tropical forest change from 1979-2100 in the Guanacaste region. As such, chapter 2 describes the spatiotemporal characteristics of tropical forest change in the Guanacaste region, and explores the spatiotemporal interactions of tropical forest change in two time periods (1979-1997 and 1997-2015) by using historical forest cover data. Chapter 3 aims to detect those geographical factors acting on tropical forest loss/gain from political, natural and biophysical aspects, and assesses the magnitude of each geographical factor affecting forest loss/gain by using geographical detector. Meanwhile, all the assessments and analyses of driving forces in this chapter considered spatial autocorrelations that may exist among each geographical unit of a given factor. Chapter 4 reproduces and simulates tropical forest change of the Guanacaste region in the past 36 years by using a combined model of cellular automata model (CA model) and agent based model (AB model). Pilot model was validated by the historical scenarios of forest change. Afterward, this model was used to forecast future simulations with different assumptions: current trend scenarios, economy-development-driven scenarios, and ecology-protection-driven scenarios. This research contributes to filling important knowledge gaps on contemporary research which is aimed to understand tropical forest dynamic processes.

  • Subjects / Keywords
  • Graduation date
    Spring 2020
  • Type of Item
  • Degree
    Doctor of Philosophy
  • DOI
  • License
    Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.