Agent-based modelling of urban expansion and land cover change: a prototype for the analysis of commuting patterns in Geneva, Switzerland
Résumé
Agent-based modelling has been used in many studies of urban expansion, land use and land cover change patterns. While representing a powerful tool for depicting and formulating predictions about the evolution of interconnected complex systems, this method also poses a series of challenges to the researcher community, most notably in terms of model calibration and validation, and output data visualisation. Based on these findings, we present an agent-based model developed in GAMA, coupled with a data exploration platform coded in python, for analysing commuting patterns in the canton of Geneva, Switzerland. Output datasets generated from a set of simple evolution rules for the agents, are distributed in open access together with the code for the associated data visualisation platform. This prototype is early work in developing a series of agent-based models for simulating urban expansion and land cover change dynamics, together with their own data exploration platforms for calibration, validation and output data analysis purposes.
Domaines
Intelligence artificielle [cs.AI]
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FRCCS2023_ExtendedAbstractSubmission_Chambers_Cruz_DiMarzo.pdf (1004.86 Ko)
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