Abstract
The analysis and evaluation of urban structure are important while considering sustainable urban policies. It is necessary to develop a method that can easily analyze the social dynamics that are the result of changes over time in urban transportation and land use. Therefore, by describing the relationships between various agents in urban areas as a network, it is possible to analyze them by focusing on their structures. However, since there are few existing studies on social dynamics using network-based methods, it is necessary to examine the validity and effectiveness of these methods. The purpose of this study is to examine the possibility of urban analysis and evaluation focusing on the network shape by describing the urban activities and modeling the dynamics with a multilayer network. In particular, we focus on household composition and individual facility access, examine what kind of interpretation is possible for network indicators, and mention the applicability of complex networks to urban analysis. The model was applied to a two-dimensional grid virtual city, and the household composition and individual facility accessibility were quantified using the centrality index.
Highlights
Urban models using microsimulation have been actively developed as an analytical method for describing temporal changes in land use and transportation, such as Urbansim [3], 2nd generation model of TLUMIP [4], PECAS [5,6], ILUTE [7], ILUMASS [8,9], PUMA [10], and SelfSim [11]
In these urban micro-simulation models, individual and household micro-data were used for the analysis, and probabilistic choice behaviors related to changes in individual
We developed a method that can be useful for the evaluation of different sustainable urban policies by focusing on social dynamics, land use, and transportation networks
Summary
Urban models using microsimulation have been actively developed as an analytical method for describing temporal changes in land use and transportation, such as Urbansim [3], 2nd generation model of TLUMIP [4], PECAS [5,6], ILUTE [7], ILUMASS [8,9], PUMA [10], and SelfSim [11]. In these urban micro-simulation models, individual and household micro-data were used for the analysis, and probabilistic choice behaviors related to changes in individual
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