A four-dimensional agent-based model: A case study of forest-fire smoke propagation

Abstract

Dynamic geospatial complex systems are inherently four-dimensional (4D) processes and there is a need for spatio-temporal models that are capable of realistic representation for improved understanding and analysis. Such systems include changes of geological structures, dune formation, landslides, pollutant propagation, forest fires, and urban densification. However, these phenomena are frequently analyzed and represented with modeling approaches that consider only two spatial dimensions and time. Consequently, the main objectives of this study are to design and develop a modeling framework for 4D agent-based modeling, and to implement the approach to the 4D case study for forest-fire smoke propagation. The study area is central and southern British Columbia and the western parts of Alberta, Canada for forest fires that occurred in the summer season of 2017. The simulation results produced realistic spatial patterns of the smoke propagation dynamics.