Publications by authors named "E Arcaute"

The digital revolution, fuelled by advancements in social media, Big Data, the Internet of Things and Artificial Intelligence, is reshaping our urban landscapes into 'participatory cities'. These cities leverage digital technologies to foster citizen engagement, collaborative decision-making and community-driven urban development, thus unlocking new potentials while confronting emerging threats. Such technologies are empowering individuals and organizations in ways that were unimaginable just a few years ago.

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We present a novel method for analysing socio-spatial segregation in cities by considering constraints imposed by transportation networks. Using a multilayered network approach, we model the interaction probabilities of socio-economic groups with random walks and Lévy flights. This method allows for evaluation of new transport infrastructure's impact on segregation while quantifying each network's contribution to interaction opportunities.

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We argue that theories and methods drawn from complexity science are urgently needed to guide the development and use of digital twins for cities. The theoretical framework from complexity science takes into account both the short-term and the long-term dynamics of cities and their interactions. This is the foundation for a new approach that treats cities not as large machines or logistic systems but as mutually interwoven self-organizing phenomena, which evolve, to an extent, like living systems.

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Cities are characterized by the presence of a dense population with a high potential for interactions between individuals of diverse backgrounds. They appear in parallel to the Neolithic revolution a few millennia ago. The advantages brought in terms of agglomeration for economy, innovation, social and cultural advancements have kept them as a major landmark in recent human history.

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In this paper we revisit the concept of mobility entropy. Over time, the structure of spatial interactions among urban centres tends to become more complex and evolves from centralised models to more scattered origin and destination patterns. Entropy measures can be used to explore this complexity, and to quantify the degree of structural diversity of in- and out-flows at different scales and across the system.

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