Cellular Automata

Application of cellular automata to the study of geographical phenomena dates to the late 1960s and development of land use change models by Chapin and Weiss. While famous today for the invocation of Tobler’s first law, a short paper on urban growth modeling by Waldo Tobler in 1970 is among the earliest examples of geographers’ use of cellular automata. This work, while pioneering, was largely ignored by geographers for several decades, until interest was revived by Helen Couclelis in the mid 1980s, presaging a flurry of activity in the early 1990s and the emergence of automata modeling as a popular avenue of research inquiry thereafter.

The use of cellular automata in geographic research is illustrative of a broader paradigm shift in the social and life sciences, away from modeling using aggregated views of space and time and toward treatment of phenomena and systems as collectives of massive amounts of individual, independent, and heterogeneous entities – each represented at their own atomic spatial and temporal scale – connected and interacting dynamically in a complex adaptive fashion. In geography, this work draws inspiration from related research in sociology, economics, ecology, political science, physics, biology, chemistry, mathematics, and computer science. However, work by geographers is starting to have a reciprocal influence in these fields, infusing spatial thinking (and GI science in particular) into the social and physical sciences.

Cellular Automata: A Primer

The Advantages of Cellular Automata Modeling in the Geographic Sciences

Human Geography Applications

Geographic Applications in Other Sciences

The Future for Cellular Automata in Geographic Research