arXiv subjects

Elsa Arcaute

Publications and source records attributed to Elsa Arcaute.

At least 19 recordsLinked to original sources

arXiv2025

How liveable are London's 15-minute neighbourhoods? Exploring liveability profiles and active travel patterns in London

Healthy and liveable neighbourhoods have increasingly been recognised as essential components of sustainable urban development. Yet, ambiguity surrounding their definition and constituent elements presents challenges in understanding and evaluating neighbourhood profiles, highlighting the need for a more detailed and systematic assessment. This research develops a composite Liveability Index for Greater London based on metrics related to the proximity, density, and diversity of POIs, along with population density, and investigates how neighbourhood liveability relates to active travel behaviour. The Index is based on the principles of the 15-minute city paradigm (Moreno et al. 2021) and developed in line with OECD guidelines for composite indicators (European Union and Joint Research Centre 2008). The Index revealed distinct spatial patterns of neighbourhood liveability, with high liveability neighbourhoods predominantly clustered in Inner London. Decomposing the Index provided further insights into the strengths and weaknesses of each neighbourhood. Footfall modelling using ordinary least squares (OLS) and geographically weighted regression (GWR) indicates a generally positive relationship between liveability and footfall, with spatial variation in the strength of this association. This research offers a new perspective on conceptualising and measuring liveability, demonstrating its role as an urban attractor that fosters social interaction and active engagement.

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arXiv2025

Recurrent visitations reveal selectivity beyond the 15-Minute City vision

In the transition towards sustainable and equitable urban living, proximity-centred planning has been adopted in cities worldwide. Exemplified by the 15-Minute City (15mC), this planning paradigm often assumes that local amenity provision translates into local use, yet behavioural evidence on recurrent visitation remains limited. To address this gap, we introduce K-Visitation, a scalable, behaviourally informed framework for comparing recurrent visitation with proximity-based expectations, using 18 months of mobile phone data from 720,000 users in Finland. For each individual, K-Visitation compares recurrent destinations ($K_{freq}$) with nearest options ($K_{dist}$), and evaluates travel time differences between them and their neighbourhood proximity baseline. Across Finnish cities, individuals repeatedly bypassed nearby visited options that already exposed them to required daily amenity categories, incurring measurable travel time costs beyond what local opportunities could support. The sharpest divergence appears in amenity-rich urban cores: where the physical conditions for 15-minute living are strongest, recurrent destinations depart most from nearest options. A density-aware null model and destination-level classifier show that this divergence reflects selective behaviour: non-nearest recurrent destinations are not explained by amenity density alone and are often amenity-rich but functionally specialised. Amenity-specific analysis further reveals a hierarchy in which routine anchors adhere more closely to proximity, while specialised and infrastructural functions depend on wider catchments and connectivity. Our findings show that proximity is a necessary but insufficient condition for local living. The 15mC should therefore secure routine local access while using behavioural evidence to identify where proximity is bypassed and where wider connectivity remains necessary.

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arXiv2025

Multiscalarity in Socio-Spatial Segregation: An Information-Theoretic Framework

We present a novel analytical framework to examine socio-spatial segregation across multiple spatial scales, explicitly leveraging information theory and percolation theory. This framework emphasizes the interplay between regional connectivity and population distribution, which are critical for understanding how spatial inequalities arise and persist in urban regions. Employing the Generalised Jensen-Shannon Divergence (GJSD), this method identifies regions characterized by significant segregation and low connectivity, providing actionable insights for targeted urban interventions. Using Ecuador as a case study, we demonstrate how segregation patterns manifest differently at city, regional, and national scales, underscoring the critical role of multiscalarity in understanding urban inequalities and guiding scale-sensitive policies. This approach not only advances the methodology for studying socio-spatial segregation but also contributes to the broader field by highlighting the importance of considering multiscalar perspectives and connectivity in urban systems.

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arXiv2024

The role of central places in exposure segregation

Here we show that "exposure segregation" - the degree to which individuals of one group are exposed to individuals of another in day-to-day mobility - is dependent on the structure of cities, and the importance of downtowns in particular. Recent work uses aggregated data to claim that the location of amenities can inhibit or facilitate interactions between groups: if a city is residentially segregated, as many American cities are, then amenities between segregated communities should encourage them to mix. We show that the relationship between "bridging" amenities and socio-economic mixing breaks down when we examine the amenities themselves, rather than the urban aggregates. For example, restaurants with locations that suggest low expected mixing do not, much of the time, have low mixing: there is only a weak correlation between bridging and mixing at the level of the restaurant, despite a strong correlation at the level of the supermarket. This is because downtowns - and the bundle of amenities that define them - tend not to be situated in bridge areas but play an important role in drawing diverse groups together.

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arXiv2024

American cities are defined by isolated rings and pockets characterized by limited socio-economic mixing

Cities generate gains from interaction, but citizens often experience segregation as they move around the urban environment. Using GPS location data, we identify four distinct patterns of experienced segregation across US cities. Most common are affluent or poor neighborhoods where visitors lack diversity and residents have limited exposure to diversity elsewhere. Less frequent are majority-minority areas where residents must travel for diverse encounters, and wealthy urban zones with diverse visitors but where locals sort into homogeneous amenities. By clustering areas with similar mobility signatures, we uncover rings around cities and internal pockets where intergroup interaction is limited. Using a decision tree, we show that demography and location interact to create these zones. Our findings, persistent across time and prevalent across US cities, highlight the importance of considering both who is mixing and where in urban environments. Understanding the mesoscopic patterns that define experienced segregation in America illuminates neighborhood advantage and disadvantage, enabling interventions to foster economic opportunity and urban dynamism.

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arXiv2023

Urban Segregation on multilayered transport networks: a random walk approach

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 L\'evy flights. This method allows for evaluation of new transport infrastructure's impact on segregation while quantifying each network's contribution to interaction opportunities. The proposed random walk segregation index measures the probability of individuals encountering diverse social groups based on their available means of transit via random walks. The index incorporates temporal constraints in urban mobility with a parameter, $\alpha \in [0,1)$, of the probability of the random walk continuing at each time step. By applying this to a toy model and conducting a sensitivity analysis, we explore how the index changes dependent on this temporal constraint. When the parameter equals zero, the measure simplifies to an isolation index. When the parameter approaches one it represents the city's overall socio-economic distribution by mirroring the steady-state of the random walk process. Using Cuenca, Ecuador as a case study, we illustrate the method's applicability in transportation planning as a valuable tool for policymakers, addressing spatial distribution of socio-economic groups and the connectivity of existing transport networks, thus promoting equitable interactions throughout the city.

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arXiv2023

Active-travel modelling: a methodological approach to networks for walking and cycling commuting analysis

Walking and cycling, commonly referred to as active travel, have become integral components of modern transport planning. Recently, there has been growing recognition of the substantial role that active travel can play in making cities more liveable, sustainable and healthy, as opposed to traditional vehicle-centred approaches. This shift in perspective has spurred interest in developing new data sets of varying resolution levels to represent, for instance, walking and cycling street networks. This has also led to the development of tailored computational tools and quantitative methods to model and analyse active travel flows. In response to this surge in active travel-related data and methods, our study develops a methodological framework primarily focused on walking and cycling as modes of commuting. We explore commonly used data sources and tools for constructing and analysing walking and cycling networks, with a particular emphasis on distance as a key factor that influences, describes, and predicts commuting behaviour. Our ultimate aim is to investigate the role of different network distances in predicting active commuting flows. To achieve this, we analyse the flows in the constructed networks by looking at the detour index of shortest paths. We then use the Greater London Area as a case study, and construct a spatial interaction model to investigate the observed commuting patterns through the different networks. Our results highlight the differences between chosen data sets, the uneven spatial distribution of their performance throughout the city and its consequent effect on the spatial interaction model and prediction of walking and cycling commuting flows.

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arXiv2023

Revealing the spatial extent of patent citations in the UK: How far does knowledge really spillover?

Access to external knowledge sources through localized knowledge spillovers is an important determinant of the innovative capabilities of firms. However, the geographical extent of knowledge spillovers is not well understood. In this article we use patent citations in the UK as a proxy of knowledge flows and analyze the spatial extent of knowledge spillovers relative to the distribution of existing knowledge creation. We find that local, regional and country specific institutional factors play an important role in influencing the probability of knowledge spillovers and that most knowledge spillovers are exhausted within an extended commuting boundary. It is also shown that these effects have increased over time and that the spatial extent of knowledge spillovers varies by industry.

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arXiv2023

Spaces of innovation and venture formation: the case of biotech in the United Kingdom

Patents serve as valuable indicators of innovation and provide insights into the spaces of innovation and venture formation within geographic regions. In this study, we utilise patent data to examine the dynamics of innovation and venture formation in the biotech sector across the United Kingdom (UK). By analysing patents, we identify key regions that drive biotech innovation in the UK. Our findings highlight the crucial role of biotech incubators in facilitating knowledge exchange between scientific research and industry. However, we observe that the incubators themselves do not significantly contribute to the diversity of innovations which might be due to the underlying effect of geographic proximity on the influences and impact of the patents. These insights contribute to our understanding of the historical development and future prospects of the biotech sector in the UK, emphasising the importance of promoting innovation diversity and fostering inclusive enterprise for achieving equitable economic growth.

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arXiv2023

Modelling the multi-scalar effect of commuting on exposure to diversity

Urban systems are primarily relational. The uneven intensities and distribution of flows between systems of cities results in hierarchically organised complex networks of urban exchange. Distinct urban spatial structures reflect the diversity of functional and social patterns which vary or remain constant across multiple scales. In this work, we examine the impact of commuting on the potential accessibility to spatial and social diversity, and the scalar relations that may exist. We first define relational scales by conducting a process of percolation on the commuting network, as a hierarchical clustering algorithm. This gives rise to a nested structure of urban clusters based on flow connectivity. For each cluster at each scale, we compute measures of commuting structural and social diversity by examining the spatial distribution of origin-destination pairs, and the distribution of workers' skills and occupations. To do this, we make use of global entropy measures allowing us to quantitatively analyse the reachable diversity across scales. Applying this methodology to Chile, we observe that the hierarchical accessibility to the wider system of cities and the patterns of spatial interaction, significantly influence the degree of exposure to diversity within urban systems. This framework examines connectivity-based diversity at multiple scales, and allows for the classification of cities and systems of cities according to the spatial and social dimensions of commuting dispersion. Such insights could contribute to the planning of infrastructural projects connecting the urban system at different scales, while also guiding a strategic relocation and redistribution of economic activities at regional levels.

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arXiv2023

The scalar mismatch of regional governance: a comparative analysis of hierarchical structures

Self-organisation in territories leads to the emergence of patterns in urban systems that shape the interactions between cities, resulting in a hierarchical organisation. Governance follows as well a hierarchical structure, breaking the territory into smaller units for its management. The possible mismatch between these two organisations may lead to a range of problems, ranging from inefficiencies to insufficient and uneven distribution of resources. This paper seeks to develop a methodology to explore and quantify the correspondence between the hierarchical organisation given by the structure of governance and that given by the structure of the urban systems being governed, where Chile is used as case study. The urban hierarchical structure is defined according to the connectivity of the system given by the road network. This is extracted through a clustering algorithm defined as a percolation process on the street network, giving rise to urban clusters at different scales. These are then compared to the spatial scales of the administrative system. This is achieved by computing cophenetic distance on the dendrograms, by looking at the different clustering membership using Jaccard similarity, and by analysing the topological diversity defined as the structural entropy. The results show that the urban sub-national structures present high heterogeneity, while the administrative system is highly homogeneous, replicating the same structure of organisation across the national territory. Such contrasting organisational structures present administrative challenges that can give rise to poor decision-making processes and mismanagement, impairing the efficient functioning of systems. Our results can help address these challenges, informing how to rebalance such mismatches through planning and political strategies that consider the complex interdependencies of territories across scales.

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arXiv2021

Some recent advances in urban system science: models and data

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. There are many different aspects to study in urban systems from a scientific point of view, just to name a few one can concentrate in demography and population evolution, mobility, economic output, land use and urban planning, home accessibility and real estate market, energy and water consumption, waste processing, health, education, integration of minorities, etc. In the last decade, the introduction of communication and information technologies have enormously facilitated the collection of datasets on these and other questions, making possible a more quantitative approach to city science. All these topics have been addressed in many works in the literature, and we do not intend to offer here a systematic review. Instead, we will only provide a brief taste of some of these above-mentioned aspects, which could serve as an introduction to a subsequent special number. Such a non-systematic view will lead us to leave outside many relevant papers, and for this we apologise.

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arXiv2021

Uncovering structural diversity in commuting networks. Global and local entropy

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. We use toy models of commuting networks to examine global and local measures, allowing the comparison to occur between different parts of the system. We show that entropy at the link and node level give different insights on the characteristics of the systems, enabling us to identify employment hubs and interdependencies between and within different parts of the system. We discuss how these can be used to inform planning and policy decisions oriented towards decentralisation and resilience.

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arXiv2021

A Road Segment Prioritization Approach for Cycling Infrastructure

Understanding the motivators and deterrents to cycling is essential for creating infrastructure that gets more people to adopt cycling as a mode of transport. This paper demonstrates a new approach to support the prioritization of cycling infrastructure and cycling network design, accounting for cyclist preferences and the growing emphasis on 'filtered permeability' and 'Low Traffic Neighborhood' interventions internationally. The approach combines distance decay, route calculation, and network analysis methods to examine where future cycling demand is most likely to arise, how such demand could be accommodated within existing street networks, and how to ensure a fair distribution of investment. Although each of these methods has been applied to cycling infrastructure prioritization in previous research, this is the first time that they have been combined, creating an integrated road segment prioritization approach. The approach, which can be applied to other cities, as shown in the Appendix, is demonstrated in a case study of Manchester, resulting in cycling networks that balance directness against the need for safe and stress-free routes under different investment scenarios. A key benefit of the approach from a policy perspective is its ability to support egalitarian and cost-effective strategic cycle network planning.

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arXiv2020

Modeling growth of urban firm networks

The emergence of interconnected urban networks is a crucial feature of globalisation processes. Understanding the drivers behind the growth of such networks - in particular urban firm networks -, is essential for the economic resilience of urban systems. We introduce in this paper a generative network model for firm networks at the urban area level including several complementary processes: the economic size of urban areas at origin and destination, industrial sector proximity between firms, the strength of links from the past, as well as the geographical and socio-cultural distance. An empirical network analysis on European firm ownership data confirms the relevance of each of these factors. We then simulate network growth for synthetic systems of cities, unveiling stylized facts such as a transition from a local to a global regime or a maximal integration achieved at an intermediate interaction range. We calibrate the model on the European network, outperforming statistical models and showing a strong role of path-dependency. Potential applications of the model include the study of mitigation policies to deal with exogenous shocks such as economic crisis or potential lockdowns of countries, which we illustrate with an application on stylized scenarios.

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arXiv2020

Multilayer modeling of adoption dynamics in energy demand management

Due to the emergence of new technologies, the whole electricity system is undergoing transformations on a scale and pace never observed before. The decentralization of energy resources and the smart grid have forced utility services to rethink their relationships with customers. Demand response (DR) seeks to adjust the demand for power instead of adjusting the supply. However, DR business models rely on customer participation and can only be effective when large numbers of customers in close geographic vicinity, e.g., connected to the same transformer, opt in. Here, we introduce a model for the dynamics of service adoption on a two-layer multiplex network: the layer of social interactions among customers and the power-grid layer connecting the households. While the adoption process - based on peer-to-peer communication - runs on the social layer, the time-dependent recovery rate of the nodes depends on the states of their neighbors on the power-grid layer, making an infected node surrounded by infectious ones less keen to recover. Numerical simulations of the model on synthetic and real-world networks show that a strong local influence of the customers' actions leads to a discontinuous transition where either none or all the nodes in the network are infected, depending on the infection rate and social pressure to adopt. We find that clusters of early adopters act as points of high local pressure, helping maintaining adopters, and facilitating the eventual adoption of all nodes. This suggests direct marketing strategies on how to efficiently establish and maintain new technologies such as DR schemes.

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arXiv2019

Evidence for localization and urbanization economies in urban scaling

We study the scaling of (i) numbers of workers and aggregate incomes by occupational categories against city size, and (ii) total incomes against numbers of workers in different occupations, across the functional metropolitan areas of Australia and the US. The number of workers and aggregate incomes in specific high income knowledge economy related occupations and industries show increasing returns to scale by city size, showing that localization economies within particular industries account for superlinear effects. However, when total urban area incomes and/or Gross Domestic Products are regressed using a generalised Cobb-Douglas function against the number of workers in different occupations as labour inputs, constant returns to scale in productivity against city size are observed. This implies that the urbanization economies at the whole city level show linear scaling or constant returns to scale. Furthermore, industrial and occupational organisations, not population size, largely explain the observed productivity variable. The results show that some very specific industries and occupations contribute to the observed overall superlinearity. The findings suggest that it is not just size but also that it is the diversity of specific intra-city organization of economic and social activity and physical infrastructure that should be used to understand urban scaling behaviors.

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arXiv2019

Truncated lognormal distributions and scaling in the size of naturally defined population clusters

Using population data of high spatial resolution for a region in the south of Europe, we define cities by aggregating individuals to form connected clusters. The resulting cluster-population distributions show a smooth decreasing behavior covering six orders of magnitude. We perform a detailed study of the distributions, using state-of-the-art statistical tools. By means of scaling analysis we rule out the existence of a power-law regime in the low-population range. The logarithmic-coefficient-of-variation test allows us to establish that the power-law tail for high population, characteristic of Zipf's law, has a rather limited range of applicability. Instead, lognormal fits describe the population distributions in a range covering from a few dozens individuals to more than one million (which corresponds to the population of the largest cluster).

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