Geographical Modeling

6Model Visualization

6.1. Introduction

Geographers know the essential role of cartography in analyzing, understanding, and describing the spaces they study. For Philippe Pinchemel (1979, pp. 246–247), “only the cartographic representation highlights geographical organizations, structures, and systems. The map and the cartographic language also appear as the expression, as the privileged developer of geography. Geographical thinking can be seen in cartographic representations”. In geographical modeling¹, it is, therefore, not surprising that cartography and data visualization in a broader sense are essential media for the expressiveness of a model. In their latest manual linking agent-based modeling (ABM) and geographic information systems (GIS), Crooks et al. (2019) describe the importance of visualization, applied here to simulation results:

Building effective visualizations of spatial analysis and modeling outcomes, be they derived from GIS or agent-based modeling, is a vital final component of the analysis process. Good-quality maps and visualizations not only explain the outcomes of the analysis, but also aid interpretation by allowing observers to easily draw out insights. (Crooks et al. 2019, p. 117)

Moreover, even when modeling is not geographical, there are many semantic parallels between geographic space and the modeling environment: agents interact in a virtual “world”, a world that refers to a continuous, geographical space, or more often than not, a discretized ...