The distributions of street lengths and nodes follow inverse-power distribution laws. That means that the smaller the network components, the more numerous they have to be. In addition, street networks show geometrical self-similarities over a range of scales. Based on these features many authors claim that street networks are fractal in nature. What we show here is that both the scaling laws and self-similarity emerge from the underlying dynamics, together with the purpose of optimizing flows of people and goods in time, as predicted by the Constructal Law. The results seem to corroborate the prediction that cities’ fractal dimension approaches 2 as they develop and become more complex
International audienceIn this work we study a Poisson patterns of fixed and mobile nodes distributed...
Urban population density always follows the exponential distribution and can be described with Clark...
The basic rules of central place networks are abstracted and formulated as three geometric series sc...
In this paper cities are viewed as lively systems with internal flow structure of people, energy and...
Traffic networks have been proved to be fractal systems. However, previous studies mainly focused on...
City-size distributions follow an approximate power law in various countries despite high volatility...
In this paper, we study topological patterns of urban street networks using a largest sample (the la...
Scaling laws have been observed in many natural and engineered systems. Their existence can give use...
Easy and intuitive navigability is of central importance in cities. The actual scale-free networking...
In this paper, we argue for the case that cities are self-organised complex systems by presenting ev...
This paper proposes a novel concept of flow to measure the efficiency of urban street networks (a ki...
This paper aims to measure the efficiency of urban street networks (a kind of complex networks) from...
This paper aims to measure the efficiency of urban street networks (a kind of complex networks) from...
Zipf's law is one the most conspicuous empirical facts for cities, however, there is no convinc...
The application of fractal geometry to the modelling of some aspects of urban technical networks has...
International audienceIn this work we study a Poisson patterns of fixed and mobile nodes distributed...
Urban population density always follows the exponential distribution and can be described with Clark...
The basic rules of central place networks are abstracted and formulated as three geometric series sc...
In this paper cities are viewed as lively systems with internal flow structure of people, energy and...
Traffic networks have been proved to be fractal systems. However, previous studies mainly focused on...
City-size distributions follow an approximate power law in various countries despite high volatility...
In this paper, we study topological patterns of urban street networks using a largest sample (the la...
Scaling laws have been observed in many natural and engineered systems. Their existence can give use...
Easy and intuitive navigability is of central importance in cities. The actual scale-free networking...
In this paper, we argue for the case that cities are self-organised complex systems by presenting ev...
This paper proposes a novel concept of flow to measure the efficiency of urban street networks (a ki...
This paper aims to measure the efficiency of urban street networks (a kind of complex networks) from...
This paper aims to measure the efficiency of urban street networks (a kind of complex networks) from...
Zipf's law is one the most conspicuous empirical facts for cities, however, there is no convinc...
The application of fractal geometry to the modelling of some aspects of urban technical networks has...
International audienceIn this work we study a Poisson patterns of fixed and mobile nodes distributed...
Urban population density always follows the exponential distribution and can be described with Clark...
The basic rules of central place networks are abstracted and formulated as three geometric series sc...