Street Urbanism

We are also sharing the street-scale Walk Score for all these cities below in the format of ShapeFiles. Please unzip the following two files and put them in the same directory and in this way you will be able to open the GIS file. For details please see the Data 44 in the Data Released channel of our website.

We are working on Street Urbanism which is supposed to be a bridge to connect urban studies with planning & design. In addition to the overall introduction online shared, I also attach several recent publications by our group.

Online introduction is available HERE

Streets as traffic carrier and public space of a city, are playing increasingly important role in daily city life. We quantitatively explore the street vibrancy of Chengdu, while referring to the street urbanism proposed by Ying Long and Yao Shen in 2015. We first define the concepts of street, vibrancy and street urbanism, followed by developing the factors for quantitatively evaluating street vibrancy at the street level. These factors range from function density, function diversity, accessibility to metro stations, distance to city center and sub-centers, to street level and width. Linear regression has been adopted for identifying the impact of each factor on the street vibrancy, which is measured by population density derived from mobile phone traces. We specifically analyze the impact factors for public administration and service streets (Type A), commercial streets (Type B) and residential streets (Type C). As one of first studies on evaluating street vibrancy and its impact factors for the whole city, we expect this paper could shed light on the future urban studies.

The significant effect of walking on urban sustainability has attracted worldwide attention. More and more walkability evaluation studies have been conducted in recent years. In this paper, we revised the evaluation method for WalkScore via introducing street greenery and applied the revised method in Chengdu. The application results reveal that streets in residential areas are associated with greater WalkScore, in comparing with those in business areas. In addition, streets being closer to the city center, sub centers, subway stations and shopping centers have greater WalkScore values as well.

Please see the following visualization of the main Chinese cities for a glance at the calculation results.