No Arabic abstract
We show that the definition of the city boundaries can have a dramatic influence on the scaling behavior of the night-time light (NTL) as a function of population (POP) in the US. Precisely, our results show that the arbitrary geopolitical definition based on the Metropolitan/Consolidated Metropolitan Statistical Areas (MSA/CMSA) leads to a sublinear power-law growth of NTL with POP. On the other hand, when cities are defined according to a more natural agglomeration criteria, namely, the City Clustering Algorithm (CCA), an isometric relation emerges between NTL and population. This discrepancy is compatible with results from previous works showing that the scaling behaviors of various urban indicators with population can be substantially different for distinct definitions of city boundaries. Moreover, considering the CCA definition as more adequate than the MSA/CMSA one because the former does not violate the expected extensivity between land population and area of their generated clusters, we conclude that, without loss of generality, the CCA measures of light pollution and population could be interchangeably utilized in future studies.
The spatial structure of modern cities exhibits highly diverse patterns and keeps evolving under numerous constraints. Two key dimensions have recently achieved prominence in characterizing this diversity: heterogeneity and spreading. However, modern settlements do not fill the entire heterogeneity--spreading space. Yet, the dynamic mechanisms leading to emergence of the observed layouts are unclear. Here, we assess the heterogeneity and spreading of population density in 25 Australian and 175 US cities. We observe that larger cities tend to form a cluster with a low degree of spreading and a high degree of heterogeneity, and relate this observation to the dynamic properties of intra-urban migration in these cities. In doing so, we introduce a model consistent with the relocation data which predicts such highly compact and heterogeneous structure for the majority of cities, in concordance with the actual layout data. In addition, we analyze the stability of the long-term dynamics of urban configurations with respect to changes in the mobility characteristics, such as social disposition and relocation impedance near their equilibrium states. As a result, we report three qualitatively distinct feasible phases of urban structures: uniform, monocentric, and polycentric. These phases are shown to be separated by either smooth or sharp transitions, observed in the space of suitably chosen configurational parameters. Finally, this analysis reveals that the set of all possible equilibrium configurations (configurational attractors) form a narrow region in the heterogeneity--spreading space, thus explaining the emergence of clustering patterns.
The relationship between nature contact and mental well-being has received increasing attention in recent years. While a body of evidence has accumulated demonstrating a positive relationship between time in nature and mental well-being, there have been few studies comparing this relationship in different locations over long periods of time. In this study, we estimate a happiness benefit, the difference in expressed happiness between in- and out-of-park tweets, for the 25 largest cities in the US by population. People write happier words during park visits when compared with non-park user tweets collected around the same time. While the words people write are happier in parks on average and in most cities, we find considerable variation across cities. Tweets are happier in parks at all times of the day, week, and year, not just during the weekend or summer vacation. Across all cities, we find that the happiness benefit is highest in parks larger than 100 acres. Overall, our study suggests the happiness benefit associated with park visitation is on par with US holidays such as Thanksgiving and New Years Day.
Bus transportation is considered as one of the most convenient and cheapest modes of public transportation in Indian cities. Due to their cost-effectiveness and wide reachability, they help a significant portion of the human population in cities to reach their destinations every day. Although from a transportation point of view they have numerous advantages over other modes of public transportation, they also pose a serious threat of contagious diseases spreading throughout the city. The presence of numerous local spatial constraints makes the process and extent of epidemic spreading extremely difficult to predict. Also, majority of the studies have focused on the contagion processes on scale-free network topologies whereas, spatially-constrained real-world networks such as, bus networks exhibit a wide-spectrum of network topology. Therefore, we aim in this study to understand this complex dynamical process of epidemic outbreak and information diffusion on the bus networks for six different Indian cities using SI and SIR models. This will allow us to identify epidemic thresholds for these networks which will help us in controlling outbreaks by developing node-based immunization techniques.
Rapid urbanization with poor city planning has resulted in severe air pollution in low- and middle-income countries urban areas. Given the adverse impacts of air pollution, many responses have been taken, including migration to another city. The current study explores the psychological process and demographic predictors of migration intention among urban people in Hanoi, Vietnam - one of the most polluted capital cities in the world. The Bayesian Mindsponge Framework (BMF) was used to construct the model and perform Bayesian analysis on a stratified random sampling dataset of 475 urban people. We found that the migration intention was negatively associated with the individuals satisfaction with air quality. The association was moderated by the perceived availability of a better alternative (or nearby city with better air quality). However, the high migration cost due to geographical distance made the moderation effect of the perceived availability of a better alternative negligible. Moreover, it was also found that male and young people were more likely to migrate, but the brain drain hypothesis was not validated. The results hint that without air pollution mitigation measures, the dislocation of economic forces might occur and hinder sustainable urban development. Therefore, collaborative actions among levels of government, with the semi-conducting principle at heart, are recommended to reduce air pollution.
Numerous urban indicators scale with population in a power law across cities, but whether the cross-sectional scaling law is applicable to the temporal growth of individual cities is unclear. Here we first find two paradoxical scaling relationships that urban built-up area sub-linearly scales with population across cities, but super-linearly scales with population over time in most individual cities because urban land expands faster than population grows. Different cities have diverse temporal scaling exponents and one city even has opposite temporal scaling regimes during two periods, strongly supporting the absence of single temporal scaling and further illustrating the failure of cross-sectional urban scaling in predicting temporal growth of cities. We propose a conceptual model that can clarify the essential difference and also connections between the cross-sectional scaling law and temporal trajectories of cities. Our model shows that cities have an extra growth of built-up area over time besides the supposed growth predicted by the cross-sectional scaling law. Disparities of extra growth among different-sized cities change the cross-sectional scaling exponent. Further analyses of GDP and other indicators confirm the contradiction between cross-sectional and temporal scaling relationships and the validity of the conceptual model. Our findings may open a new avenue towards the science of cities.