Evaluation of Urban Vibrancy and Its Relationship with the Economic Landscape: A Case Study of Beijing

Abstract

As one of the essential indicators for the development of a city, urban vibrancy plays an important role in evaluating the quality of urban areas and guiding urban construction. The development of spatial big data makes it possible to obtain information on user trajectories and the built environment, providing support for the evaluation of urban vibrancy. However, previous studies focused on the number of regional activities when evaluating urban vibrancy and ignored diversity, which was produced by diverse economic landscapes. In this paper, using mobile phone trajectory data, we propose a method for evaluating urban vibrancy from two dimensions: busyness and diversity, based on the improved PageRank algorithm and an index of entropy. Furthermore, in order to explore the relationship between urban vibrancy and the economic landscape, we construct an economic landscape index system based on multi-source data, including points of interest (POIs), roads, building footprints, house prices, the gross domestic product (GDP), and population data. Then, multiple linear regression is utilized to model the relationship between urban vibrancy and the urban economic landscape. The results show that combining busyness and diversity can better characterize urban vibrancy than any single indicator, and the adjusted R-squared (R2) of the regression with economic landscape reaches 0.59.

Do Vibrant Places Promote Active Living? Analyzing Local Vibrancy, Running Activity, and Real Estate Prices in Beijing

“…Previous research proves that local vibrancy is critical for analyzing the real estate market, neighborhood policy making, and investment strategy [ 59 , 60 , 61 ]. Since neighborhood vibrancy correlates with local environmental, demographic, and social characteristics, it provides a proxy for business development, social integration, streetscape quality, or public safety [ 2 , 7 , 8 , 9 ]. Especially for a residential area, vibrancy assessment may guide future economic growth strategies, urban design interventions to promote a more active lifestyle, quality of life improvement, and real estate development.…”

“…Such underlying associations between pedestrian traffic, property values, and local vibrancy provide unique insights for real estate market development and neighborhood regeneration planning [ 5 , 62 ]. Furthermore, varying neighborhood vibrancy reflects different community development levels and disparity in resource allocation or quality of life [ 2 ]. Such local variations reveal the synergetic effects between people, activities, place making, and value creation within a specific physical and social context [ 63 ].…”

“…Its modern era of urban growth expands outwards through a concentric ring road system. Previous studies investigated Beijing’s vibrancy using different data sources such as mobile phone signals, social media check-ins, and GPS trajectories [ 2 , 38 , 70 ]. Jia et al quantified busyness and diversity as two vibrancy measures and found high busyness and diversity between the second to the third ring, high busyness between the second and fourth rings, and low busyness and diversity outside of the fifth ring [ 2 ].…”

“…Urban vibrancy is a critical measure of local liveliness for urban planning, real estate investment, and city management. It reflects many aspects of development including technological innovation [ 1 ], local economy [ 2 ], corporate growth [ 3 ], real estate development [ 4 , 5 ], safety [ 6 , 7 ], public health [ 8 ], and social cohesion [ 9 ]. Like other large cities worldwide, such connotation also applies to Beijing that a vibrant neighborhood usually implies busy traffic, bustling pedestrians, street commerce, diverse activities, and well-designed public space with a sense of place.…”

Effects of Urban Vibrancy on an Urban Eco-Environment: Case Study on Wuhan City

“…Moreover, measurement methods of urban vibrancy are developing based on Jacobs’s six conditions for urban vitality, namely, land use mix, density, block size, building age and accessibility [ 5 ]. Thereafter, extended quantitative measures of the built environment such as urban morphology [ 7 ], urban form or design indicators and some “vibrant” characteristics, including walking [ 8 ], social [ 9 ] and economic [ 10 ] activities, have emerged. In the era of big data, geo-referenced datasets including traditional location-based, social network and human mobility data sets, are applied to quantify vibrancy [ 11 ].…”