News
Current projects
ERC Starting Grant SEGUE: modelling urban economic segregation in cities of the Netherlands. This project combines systematic literature reviews, longitudinal analysis of empirical microdata and generative agent-based modelling to address the evolution and causal relationships between economic segregation and economic inequality in cities.
Rbanism: empowering urbanism researchers, students, educators and practitioners to use open-source software and related open-science practices effectively and with confidence. This community project raises awareness, stimulates engagement and builds capacity by demonstrating the benefits of reproducibility, automation and scalability for urbanism research, education and practice.
Recent publications
June 2025 (Cottineau-Mugadza, 2025): In this chapter, I present an overview of patterns and regularities in city size distributions. Starting from a short history of early findings, I go on to present Zipf’s contribution, the plethora of empirical material which can be interpreted as a confirmation of the law and some models generating such a regular distribution. The deviations from the law and recent propositions to advance the study of urbanisation “beyond Zipf’s law” are also presented.
May 2025 (San Millán et al., 2025): In this paper, we compute income inequality and residential segregation annually in all urban areas of the Netherlands from 2011 to 2022 and show they have remained stable or decreased in most cities. We analyse how income is distributed by percentile of the income distribution, how each percentile is segregated and at which geographical scale segregation occurs in different cities. Urban areas vary strongly: more unequal urban areas tend to be more segregated, but the same segregation levels can coexist with diverse inequality metrics.
March 2025 (Cottineau-Mugadza et al., 2025): In this chapter, we reflect on the specificity of peer-review for data papers, with the experience gathered from Cybergeo, a scientific open access journal publishing geography articles, where a section dedicated to data papers was created in 2017.
February 2025 (Roxburgh et al., 2025): In this piece, we propose a list of features that would greatly enhance population synthesis methods from the perspective of agent-based modelling. These include, but are not limited to: the attributes of agents, their location in space, the ways they make decisions and their behavioural dynamics. In the real-world, these aspects of everyday human life can be deeply interconnected, with these associations being highly consequential in shaping outcomes. Initialising synthetic populations in ways that fail to respect these covariances can therefore compromise model efficacy, potentially leading to biased and inaccurate simulation outcomes.