Diversity and density of urban functions in station areas

Highlights

• Relation between diversity and density of urban functions in station areas is studied.

• Monte Carlo simulation is performed to validate the use of diversity indices and provide theoretical baselines.

• Urban functions' diversity negatively correlated with the density around large-scale stations in the Tokyo Metropolitan Area.

• The findings encourage urban planners to monitor both diversity and density of urban functions.

Abstract

The diversity and density of urban functions have been known to affect urban vibrancy positively, but the relation between the two has not been empirically examined; if high density is associated with low diversity in an area, its vibrancy may not increase. To obtain a better understanding of the metabolism of cities and directions for urban planning interventions, this paper offers empirical evidence on the association between the diversity and density of urban functions in the Tokyo Metropolitan Area, using a robust density index that was determined via a Monte Carlo simulation. By conducting association analyses, it was found that highly dense station areas tended to display low diversity at multiple scales. Further investigation indicated that this negative correlation was owing to different spatial characteristics of functions and complementary functioning among highly accessible station areas. This paper argues for considering both diversity and density in urban planning to make station areas vibrant and resilient.

Introduction

Urban functions that meet citizens' needs are fundamental to urban vibrancy, which enables sustainable urban development (Hall & Pfeiffer, 2013), because they attract people (Wu, Ye, Ren, & Du, 2018). In this regard, urban planners have implemented two principles in cities: diversity and density. Diversity of functions, or mixed land use, has been recognized as a promoter of activities (Calthorpe, 1994; Jacobs, 1961; Register, 1987), and researchers have investigated its positive effects on urban life (Dovey & Pafka, 2017; Song, Merlin, & Rodriguez, 2013), including transportation ridership (Cervero & Kockelman, 1997; Ewing & Cervero, 2010; Sung & Oh, 2011); public health (Stevenson et al., 2016); and economic growth or vibrancy (Duranton & Puga, 2000; Glaeser, Kallal, Scheinkman, & Shleifer, 1992; Quigley, 1998). Density of functions, in turn, is expected to have a positive impact on an area because it produces a centeredness of the city (Hester, 2010), and, from an economic perspective, stimulates economic efficiency via Marshallian externality (Duranton & Puga, 2004).

Theoretically, the densification of facilities is caused by consumer preference for diversity of products or services (Fujita & Thisse, 1996). If this is empirically true, the eventual clustering of the facilities would be diverse and dense simultaneously, thereby vitalizing the urban area in terms of both aspects. However, little is empirically known about the interaction between these elements—that is, whether they occur independently or concomitantly and, if the latter, whether they are mutually reinforcing or inhibiting. If high density of functions is not associated with high diversity, urban planners must design restrictions to control the degree of density and diversity, and develop strategies for vitalization.

In effect, the presence of the negative externality of high density, such as congestion or pollution, casts doubt on a linear relation between diversity and density of urban functions. Although Talen (2006) focused on the sociodemographic aspect, she found that population density affects income diversity nonlinearly; that is, excessive density results in less diversity. From an economic perspective, a study of individual firms' strategies suggests that the diversity of industrial sectors would decrease as the degree of agglomeration intensifies (Alcácer & Chung, 2014). Conversely, Duranton and Puga (2000) argued that large cities tend to be more diversified than small cities in terms of industry at the city level, thus supporting the simultaneous intensification of diversity and density (e.g., Henderson (1997)). However, no study has empirically investigated the relation between the two in the neighborhood scale.

Furthermore, when examining these links, using a robust diversity index to sample size is crucial; if the index value increases as the number of facilities increases, diversity per se cannot be separately measured from density. Although studies have traditionally used Shannon's entropy (Shannon, 1948) to measure land use (Cervero & Kockelman, 1997; Sung & Oh, 2011) and point-of-interest-based mixed use (Yue et al., 2017), biological and ecological scholars have criticized its sensitivity to sample size (Magurran, 1988; Morishita, 1996). In regard to sensitivity, Simpson's index (Simpson, 1949), which is less frequently used in urban settings (Arribas-Bel, Nijkamp, & Scholten, 2011; Lowry & Lowry, 2014), has been recommended (Mouillot & Lepretre, 1999; Song et al., 2013), but its robustness has been verified in hypothetical populations of biological species and not those of urban functions. Hence, its suitability for urban settings remains unclear.

To fill these gaps in the literature, the present study empirically analyzes the relation between the diversity and density of urban functions by focusing on railway station areas (that are at a walkable distances from stations) in the Tokyo Metropolitan Area, Japan. The authors tested the hypothesis that a higher diversity of urban functions is associated with a higher density of those functions, using two diversity indices; the appropriateness of the indices in urban settings was also examined using a Monte Carlo simulation. The results provide insights into the mechanisms guiding such interplays, and accordingly help develop management systems that benefit urban areas.

This paper makes two contributions. First, it clarified that the diversity and density of urban functions—both being sources of urban vibrancy—do not mutually reinforce at the neighborhood scale. This suggests that urban planners should control the two parameters simultaneously to render an area vibrant; this point has not been claimed in previous studies. Second, it validated two diversity indices to measure urban functions' mixture via a Monte Carlo simulation. This allows future studies to use the indices in the same context.