Towards development of spherical geographic automata modelling approaches for global land-use/land-cover change

Approaches of geographic automata grounded in the theories of complex spatial systems and geographic information science (GISc) have been utilized in many geospatial applications to analyze and simulate spatio-temporal processes including land-use/land-cover (LULC) change. Given the increasing interactions in human-environment systems and their significant impact on global sustainability issues, there is a need for new modelling methodologies for characterizing LULC change processes at the global level. However, current geosimulation modelling approaches are based on conventional geospatial data and two-dimensional planar representations which omit effects of the curvature of the Earth's surface. Such models when applied to LULC change can result in spatial and computational errors emanating from distortions. Therefore, the primary objective of this dissertation is to develop a suite of novel spherical geographic automata modelling approaches for simulating complex spatial systems at the global level and considering the curved surface of the Earth. The dissertation integrates spherical geodesic grids, geosimulation modelling approaches, theories of GISc, and complex systems to leverage the capabilities of these fields for better representation of different land systems at the global level. The proposed methodology is implemented to simulate LULC change as a complex spatial dynamic system operating on a sphere. Results from the models' implementations indicate the methodology offers a realistic and consistent framework for representing, simulating, analysing, and visualizing LULC change, particularly urbanization and deforestation, on a spherical surface. Moreover, the presentation of modelling results in the context of LULC change processes contribute to the enhancement of decision-making processes at the global level by providing tools that can be utilized for forecasting, scenario testing and policy formulation. This dissertation contributes new methodological frameworks to the fields of geographic information science, specifically geographic automata modelling, and land use science.