Geographic Network Automata for Representing Complex Evolving Spatial Systems

Abstract

Almost all spatial systems can be modelled as networks. Typically, networks representations of real systems are static, useful for generating descriptive network measures. However, recent interest lies in the representation and analysis of evolving spatial networks that can facilitate the examination of the close coupling between network structure and network dynamics. Therefore, this study proposes a novel spatial modelling framework, Geographic Network Automata (GNA), to represent evolving spatial networks as a function of iteratively applied transition rules. The framework is demonstrated using an adapted and spatially explicit version of Conway's Game of Life. The simulated spatial network structures are quantified using network measures. The presented GNA model framework is general and flexible so that different types of geospatial phenomena can be modelled, providing valuable insights into the link between network structure, dynamics, and evolution.