English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Urban form can be reflected by many city elements, such as streets. A street network serves as the backbone of a city and reflects a city’s physical structure. A street network’s topological measures and statistical distributions have been widely investigated in recent years, but previous studies have seldom characterized the heavy-tailed distribution of street connectivities from a fractal perspective. The long-tail distribution of street connectivities can be fractal under the new, third definition: a set or pattern is fractal if the scaling of far more small things than large ones recurs at least twice. The number of recurred scaling patterns of far more less-connected streets than well-connected ones greatly helps in measuring the scaling hierarchy of a street network. Moreover, it enables us to examine the potential fractality of urban street networks at the national scale. In this connection, the present study aims to contribute to urban morphology in China through the investigation of the ubiquity of fractal cities from the lens of street networks. To do this, we generate hundreds of thousands of natural streets from about 4.5 million street segments over 298 Chinese cities and adopted power-law detection as well as three fractal metrics that emerged from the third definition of fractal. The results show that almost all cities bear a fractal structure in terms of street connectivities. Furthermore, our multiple regression analysis suggests that the fractality of street networks is positively correlated with urban socioeconomic status and negatively correlated with energy consumption. Therefore, the fractal metrics can be a useful supplement to traditional street-network configuration measures such as street lengths.

Understanding Chinese Urban Form: The Universal Fractal Pattern of Street Networks over 298 Cities