Qian Tianjian

Keywords： Urban Streets; Media Check-in Data; Urban Dynamic Sensing; Space Environment Preference; Network Analysis; Urban Computing; Italy; Milan

Abstract：

Streets establish the inner connection of the city and are the carrier of urban life. Different from the built-up buildings carrying relatively independent and single function, the usages of urban street always change with the use of surrounding land and building space; and the application of geo-big data which records individual behavior provides the possibility for dynamic sensing of street use. By collecting media check-in data from Foursquare and Google Popular Times, this paper applies a network influence model to analyze the functional changing patterns of selected streets in Central Milan and finds three types of street usage patterns, which are “inverted U-shaped”, “M-shaped”and “Linear-shaped”. The “inverted U-shaped” has the highest usage intensity, followed by “M-shaped” and “Linear-shaped”. Based on the result of clustering analysis, the relationship between people’s preference and space environment is further discussed in this paper, which shows ways to enhance street attraction in urban street planning and design. These ways include (1) at the land use level, increasing land use diversity and public service proportion; (2) at the traffic level, making use of subway station, reducing bus line interference, controlling road width and increasing road network density; (3) at the spatial perception level, increasing interface density, reducing sky view, increasing H/D ratio and reducing W/D ratio; (4) at the visual perception level, controlling green view and increasing number of urban furniture, landmarks and shops.

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