Open Access Journal

ISSN: 2183-7635

Article | Open Access | Ahead of Print | Last Modified: 18 December 2025

From City‐Builder to Geogame: A Geodesign Process for Participatory Urban Planning

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Abstract:  City‐building games (CBGs) have a long history of focusing on societal simulation and urban management gameplay, including The Sumerian Game (1964), Micropolis, later named SimCity (1989), and Utopia: Creation of a Nation (1991). In this article, we present the outcomes of a pilot study through which we have developed an innovative process that transfers CBGs’ gameplay actions into real‐world planning systems. To evaluate the interplay between CBG simulation and the real world, we delivered workshops to 140 young people and adults to design their local community in South Lancaster, UK, using Cities: Skylines I and II. A novel approach using GIS and machine learning tools was developed to analyse young people’s planning decisions and needs in the area, focusing on the act of “play” within the game. These analytical tools, which involved the semantic classification of game imagery, yielded insights into land‐use decisions. Through game updates released during the study of Cities: Skylines II, we explored new analytical potential and established a process to extract gameplay results that provide additional urban block and street‐level tools for analysis, from CBG to geogame. The limitations of these approaches include the “black box” nature of the game and its planning model, such as zoning and focus on car‐based infrastructure. However, Cities: Skylines has a large player community and strong potential to turn into a geogame in support of real‐world planning and consultation, engaging communities. This article contributes to the literature with a novel and replicable process and case study. When geogames are applied to real‐world problems, the result is a demonstration of the ability of simulations to inform real‐world decisions.

Keywords:  city‐building games; geodesign; geogames; participatory planning; urban analytics

Published:   Ahead of Print

DOI: https://doi.org/10.17645/up.10560



© Paul Cureton, Paul Coulton, Lisha He, Yuxuan Zhao. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0), which permits any use, distribution, and reproduction of the work without further permission provided the original author(s) and source are credited.

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