A good understanding of cities is crucial to implement urban planning policies leading to social and economic sustainability and an efficient use of resources. While urban concentration has been associated with both positive and negative effects, echoing debates on compact cities, few studies have documented how density evolves with city size. We fill this gap by investigating how the population density radial structure changes across the urban hierarchy. Our results uncover strong regularities in urban settlements. In terms of density, cities can be seen as exponential cones which evolve homothetically with city population. This rather simple but universal geometric structure of cities provides a new spatial scaling law, which is an important step forward in understanding how cities work and grow. Some deviations can be observed, which mainly oppose dense cities in the developing world and sprawled cities in high-income countries, associated with high energy use per capita. This suggests that urban lifestyle in wealthiest countries has come at the price of negative impacts on environmental outcomes. This research has a broad range of applications as it provides a powerful tool to
Proximity-based cities have attracted much attention in recent years. The 15-minute city, in particular, heralded a new vision for cities where essential services must be easily accessible. Despite its undoubted merit in stimulating discussion on new organisations of cities, the 15-minute city cannot be applicable everywhere, and its very definition raises a few concerns. Here, we tackle the feasibility and practicability of the '15-minute city' model in many cities worldwide. We provide a worldwide quantification of how close cities are to the ideal of the 15-minute city. To this end, we measure the accessibility times to resources and services, and we reveal strong heterogeneity of accessibility within and across cities, with a significant role played by local population densities. We provide an online platform (\href{whatif.sonycsl.it/15mincity}{whatif.sonycsl.it/15mincity}) to access and visualise accessibility scores for virtually all cities worldwide. The heterogeneity of accessibility within cities is one of the sources of inequality. We thus simulate how much a better redistribution of resources and services could heal inequity by keeping the same resources and services or
Cities are some of the most intricate and advanced creations of humanity. Most objects in cities are perfectly synchronised to coordinate activities such as jobs, education, transportation, entertainment, and waste management. Although each city has its own characteristics, some commonalities can be observed across most cities, such as issues related to noise, pollution, segregation, and others. Further, some of these issues might be accentuated in larger or smaller cities. For example, with more people, a city might experience more competition for space, so rents would be higher. The urban scaling theory provides a framework for analysing cities in terms of their size. New data for analysing urban scaling theory allow for an understanding of how urban metrics change with population size, whether they apply across most regions, or whether patterns correspond only to some countries or regions. Yet, reducing a city and all its complexity to a single indicator might simplify urban areas to the extent that their disparities and variations are overlooked. Often, the differences in living conditions across different parts of the same city are greater than the degree of variation observed
The 15-minute city concept, which advocates cities where essential services are accessible within a 15-minute walk or bike ride, has gained significant attention in recent years. However, despite being celebrated for promoting sustainability, large-scale empirical evaluations of the effectiveness of the 15-minute concept in reducing emissions remain limited. To address this gap, we investigate whether cities with better walking accessibility to services, such as 15-minute cities, are associated with lower transportation emissions. Analysing 662 cities worldwide, we find that cities with better walking accessibility to services emit less CO2 per capita for transport. An increase of 10 percentage points in the share of residents living in 15-minute accessible areas is associated with an approximate 5% reduction in transport-related CO2 emissions per capita. Moreover, among cities with similar levels of accessibility, those covering larger areas and exhibiting lower population densities tend to emit more. Our findings highlight the effectiveness of decentralised urban planning, especially the proximity-based 15-minute city, in promoting sustainable mobility. At the same time, our resu
In this paper, we empirically analyze the spatial distribution of Chinese cities using a method based on triangle transition. This method uses a regular triangle mapping from the observed cities and its three neighboring cities to analyze their distribution of mapping positions. We find that obvious center-gathering tendency for the relationship between cities and its nearest three cities, indicating the spatial competition between cities. Moreover, we observed the competitive trends between neighboring cities with similar economic volume, and the remarkable cooperative tendency between neighboring cities with large difference on economy. The threshold of the ratio of the two cities' economic volume on the transition from competition to cooperation is about 1.2. These findings are helpful in the understanding of the cities economic relationship, especially in the study of competition and cooperation between cities.
Sorting a huge stream of waste accurately within a short period can be done with the support of digitalization, particularly Artificial Intelligence, instead of traditional methods. The overlap of Artificial Intelligence and Circular Economy can flourish many services in the environmental technology domain, in particular smart ewaste recycling, resulting in enabling circular smart cities. We analyse the growing need for automated ewaste recycling as an essential requirement to cope with the fast growing ewaste stream and we shed the light on the impact of Artificial Intelligence in supporting the recycling process through smart classification of devices, where the smartphone is our case study. Our study applies transfer learning as a special technique of Artificial Intelligence by finetuning the output layers of AlexNet as a pretrained model and perform the implementation on a small size dataset that contains 12 classes from 6 smartphone brands. We evaluate the performance of our model by tuning the learning rate, choosing the best optimizer, and augmenting the original dataset to avoid overfitting. We found that the optimizer of Stochastic Gradient Descent with Momentum and 3e-4 a
Diversified economies are critical for cities to sustain their growth and development, but they are also costly because diversification often requires expanding a city's capability base. We analyze how cities manage this trade-off by measuring the coherence of the economic activities they support, defined as the technological distance between randomly sampled productive units in a city. We use this framework to study how the US urban system developed over almost two centuries, from 1850 to today. To do so, we rely on historical census data, covering over 600M individual records to describe the economic activities of cities between 1850 and 1940, and 8 million patent records as well as detailed occupational and industrial profiles of cities for more recent decades. Despite massive shifts in the economic geography of the U.S. over this 170-year period, average coherence in its urban system remains unchanged. Moreover, across different time periods, datasets and relatedness measures, coherence falls with city size at the exact same rate, pointing to constraints to diversification that are governed by a city's size in universal ways.
This study leverages large-scale travel surveys for over 200,000 residents across Boston, Chicago, Hong Kong, London, and Sao Paulo. With rich individual-level data, we make systematic comparisons and reveal patterns in social mixing, which cannot be identified by analyzing high-resolution mobility data alone. Using the same set of data, inferring socioeconomic status from residential neighborhoods yield social mixing levels 16% lower than using self-reported survey data. Besides, individuals over the age of 66 experience greater social mixing than those in late working life (aged 55 to 65), lending data-driven support to the "second youth" hypothesis. Teenagers and women with caregiving responsibilities exhibit lower social mixing levels. Across the five cities, proximity to major transit stations reduces the influence of individual socioeconomic status on social mixing. Finally, we construct detailed spatio-temporal place networks for each city using a graph neural network. Inputs of home-space, activity-space and demographic attributes are embedded and fed into a supervised autoencoder to predict individual exposure vectors. Results show that the structure of individual activity
The "Smart City" (SC) concept has been around for decades with deployment scenarios revealed in major cities of developed countries. However, while SC has enhanced the living conditions of city dwellers in the developed world, the concept is still either missing or poorly deployed in the developing world. This paper presents a review of the SC concept from the perspective of its application to cities in developing nations, the opportunities it avails, and challenges related to its applicability to these cities. Building upon a systematic review of literature, this paper shows that there are neither canonical definitions, models or frameworks of references for the SC concept. This paper also aims to bridge the gap between the "smart city" and "smart village" concepts, with the expectation of providing a holistic approach to solving common issues in cities around the world. Drawing inspiration from other authors, we propose a conceptual model for a SC initiative in Africa and demonstrate the need to prioritize research and capacity development. We also discuss the potential opportunities for such SC implementations in sub-Saharan Africa. As a case study, we consider the city of Lubum
Urban parks are important for public health, but the role of specific spaces, such as playgrounds or lakes, and elements, such as benches or sports equipment, in supporting well-being is not well understood. Based on expert input and a review of the literature, we defined six types of health-related activities: physical, mindfulness, nature appreciation, environmental, social, and cultural. We built a lexicon that links each activity to specific elements and spaces within parks present in OpenStreetMap. Using this data, we scored 23,477 parks across 35 cities worldwide based on their ability to support these activities. We found clear patterns: parks in North America focus more on physical activity, while those in Europe offer more chances to enjoy nature. Parks near city centers support health-promoting activities better than those farther out. Suburban parks in many cities lack the spaces and equipment needed for nature-based, social, and cultural activities. We also found large gaps in park quality between cities. Tokyo and Paris provide more equal access, while Copenhagen and Rio de Janeiro show sharp contrasts. These results can help cities create fairer parks that better supp
This paper focuses on the challenge of interactively modeling street networks. In this work, we extend the simple fractal model, which is particularly useful for describing small cities or individual districts, by constructing random cities based on a tiling structure over which hyperfractals are distributed. This approach enables the connection of multiple hyperfractal districts, providing a more comprehensive urban representation. Furthermore, we demonstrate how this decomposition can be used to segment a city into distinct districts through fractal analysis. Finally, we present tools for the numerical generation of random cities following this model.
The concept of `proximity-based cities' has gained attention as a new urban organizational model. Most prominently, the 15-minute city contends that cities can function more effectively, equitably and sustainably if essential, everyday services and key amenities are within a 15-minute walk or cycle. However, focusing solely on travel time risks overlooking disparities in service quality, as the proximity paradigm tends to emphasize the mere presence of an element in a location rather than bringing up more complex questions of identity, diversity, quality, value or relationships. Transitioning to value-based cities by considering more than just proximity can enhance local identity, resilience and urban democracy. Fostering bottom-up initiatives can create a culture of local care and value, while predominantly top-down governing strategies can lead to large inequalities. Balancing these approaches can maximize resilience, health and sustainability. This equilibrium has the potential to accompany sustainable growth, by encouraging the creation of innovative urban solutions and reducing inequalities.
Characterizing the structure of cities constitutes an important task since the identification of similar cities can promote sharing of respective experiences. In the present work, we consider 20 European cities from 5 respective countries and with comparable populations, each of which characterized in terms of four topological as well as one geometrical feature. These cities are then mapped into respective networks by considering their pairwise similarity as gauged by the coincidence methodology, which consists of combining the Jaccard and interiority indices. The methodology incorporates a parameter alpha that can control the relative contribution of features with the same or opposite signs to the overall similarity. Interestingly, the maximum modularity cities network is obtained for a non-standard parameter configuration, showing that it could not be obtained were not for the adoption of the parameter alpha. The network with maximum modularity presents four communities that can be directly related to four of the five considered countries, corroborating not only the effectiveness of the adopted features and similarity methodology, but also indicating a surprising tendency of the
The science of cities seeks to understand and explain regularities observed in the world's major urban systems. Modelling the population evolution of cities is at the core of this science and of all urban studies. Quantitatively, the most fundamental problem is to understand the hierarchical organization of cities and the statistical occurrence of megacities, first thought to be described by a universal law due to Zipf, but whose validity has been challenged by recent empirical studies. A theoretical model must also be able to explain the relatively frequent rises and falls of cities and civilizations, and despite many attempts these fundamental questions have not been satisfactorily answered yet. Here we fill this gap by introducing a new kind of stochastic equation for modelling population growth in cities, which we construct from an empirical analysis of recent datasets (for Canada, France, UK and USA) that reveals how rare but large interurban migratory shocks dominate city growth. This equation predicts a complex shape for the city distribution and shows that Zipf's law does not hold in general due to finite-time effects, implying a more complex organization of cities. It also
Stochastic equations constitute a major ingredient in many branches of science, from physics to biology and engineering. Not surprisingly, they appear in many quantitative studies of complex systems. In particular, this type of equation is useful for understanding the dynamics of urban population. Empirically, the population of cities follows a seemingly universal law - called Zipf's law - which was discovered about a century ago and states that when sorted in decreasing order, the population of a city varies as the inverse of its rank. Recent data however showed that this law is only approximate and in some cases not even verified. In addition, the ranks of cities follow a turbulent dynamics: some cities rise while other fall and disappear. Both these aspects - Zipf's law (and deviations around it), and the turbulent dynamics of ranks - need to be explained by the same theoretical framework and it is natural to look for the equation that governs the evolution of urban populations. We will review here the main theoretical attempts based on stochastic equations to describe these empirical facts. We start with the simple Gibrat model that introduces random growth rates, and we will t
A lack of financial access, which is often an issue in many central-city U.S. neighborhoods, can be linked to higher interest rates as well as negative health and psychological outcomes. A number of analyses of "banking deserts" have also found these areas to be poorer and less White than other parts of the city. While previous research has examined specific cities, or has classified areas by population densities, no study to date has examined a large set of individual cities. This study looks at 319 U.S. cities with populations greater than 100,000 and isolates areas with fewer than 0.318 banks per square mile based on distances from block-group centroids. The relative shares of these "deserts" appears to be independent of city population across the sample, and there is little relationship between these shares and socioeconomic variables such as the poverty rate or the percentage of Black residents. One plausible explanation is that only a subset of many cities' poorest, least White block groups can be classified as banking deserts; nearby block groups with similar socioeconomic characteristics are therefore non-deserts. Outside of the Northeast, non-desert areas tend to be poorer
Smart cities are a growing trend in many cities in Argentina. In particular, the so-called intermediate cities present a context and requirements different from those of large cities with respect to smart cities. One aspect of relevance is to encourage the development of applications (generally for mobile devices) that enable citizens to take advantage of data and services normally associated with the city, for example, in the urban mobility domain. In this work, a platform is proposed for intermediate cities that provide "high level" services and that allow the construction of software applications that consume those services. Our platform-centric strategy focused aims to integrate systems and heterogeneous data sources, and provide "intelligent" services to different applications. Examples of these services include: construction of user profiles, recommending local events, and collaborative sensing based on data mining techniques, among others. In this work, the design of this platform (currently in progress) is described, and experiences of applications for urban mobility are discussed, which are being migrated in the form of reusable services provided by the platform
We investigated the socioeconomic scaling behavior of all cities with more than 50,000 inhabitants in the Netherlands and found significant superlinear scaling of gross urban product with population size. Of these cities, 22 major cities have urban agglomerations and urban areas defined by the Netherlands Central Bureau of Statistics. For these major cities we investigated the superlinear scaling for three separate modalities: the cities defined as municipalities, their urban agglomerations and their urban areas. We find superlinearity with power-law exponents of around 1.15. But remarkably, both types of agglomerations underperform if we compare for the same size of population an agglomeration with a city as a municipality. In other words, an urban system as one formal municipality performs better as compared to an urban agglomeration with the same population size. This effect is larger for the second type of agglomerations, the urban areas. We think this finding has important implications for urban policy, in particular municipal reorganizations. A residual analysis suggests that cities with a municipal reorganization recently and in the past decades have a higher probability to
Do cities have just one or several centers? Studies performing radial or monocentric analyses of cities are usually criticised by researchers stating that cities are actually polycentric, and this has been well known for a long time. Reversely, when cities are studied independently of any center, other researchers will wonder how the variables of interest evolve with the distance to the center, because this distance is known to be a major determinant at the intra-urban scale. Both monocentric and polycentric formalisms have been introduced centuries (respectively, decades) ago for the study of urban areas, and used both on the empirical and the theoretical side in different disciplines (economics, geography, complex systems, physics...). The present work performs a synthesis of both viewpoints on cities, regarding their use in the literature, and explores with data on European urban areas how some cities considered to be the most polycentric in Europe compare to more standard cities when studied through a combination of radial analysis and scaling laws.
Smart cities have been a very active research area in the past 20 years, while continuously adapting to new technological advancements and keeping up with the times regarding sustainability and climate change. In this context, there have been numerous proposals to expand the scope of smart cities, focusing on resilience and sustainability, among other aspects, resulting in terms like smart sustainable cities. At the same time, there is an ongoing discussion regarding the degree in which smart cities put people at their centre. In this work, we argue toward expanding the current smart city definition by integrating the circular economy as one of its central pillars and adopting the term smart (and) circular city. We discuss the ways a smart and circular city encompasses both sustainability and smartness in an integral manner, while also being well-positioned to foster novel business activity and models and helping to place citizens at the heart of the smart city. In this sense, we also argue that previous research in smart cities and technologies, such as those related to Industry 4.0, can serve as a cornerstone to implement circular economy activities within cities, at a scale that