‘Compact’ or ‘Sprawl’ for sustainable urban form? Measuring the effect on travel behavior in Korea

Abstract

This paper measures and identifies the effects of urban form on travel behavior in Korea. The characteristics of urban form include urban size, density, distribution and clustering. Using cluster analysis, urban form in Korea is categorized into two groups: group 1 (i.e., large-sized, high-density, equally distributed and highly clustered areas) and group 2 (i.e., small-sized, low-density, unequally distributed and highly dispersed areas). The results showed that the large-sized, high-density, unequally distributed and dispersed pattern is a relevant strategy for both groups to minimize vehicle kilometers traveled (VKT) per capita. For group 1, increasing the average travel distance may be an efficient strategy to reduce the number of automobile trips. For group 2, however, decreasing the average travel distance may be a more efficient strategy. Previous recommendations for a so-called compact urban form require more validation before adoption in Korea. Different strategies are required for areas that show different characteristics in order to reduce VKT. It is important that planners and policy decision makers understand the relevant implications of urban form on travel behavior and energy use in order to implement spatial urban developments aimed at sustainability. JEL Classification

Commuting Flows and Labour Market Structure: Modelling Journey to Work Behaviour in an Urban Environment

“…The form of equation 5 implies that high job concentrations can outweigh low values of c and lead to the longer physical commute distances and times, something that has been observed for many high-status, well-paid jobs which are typically concentrated in the CBD (Gordon, Kumar, and Richardson 1989a,b;Lee, Seo, and Webster 2006). Equation 5 also makes it entirely understandable that vehicle kilometres travelled increase in urban environments characterised by high densities and high levels of clustering (Nam, Lim, and Kim 2012).…”

“…Longer commuting distances with lower urban densities have indeed been observed in a number of cities (Cao and Fan 2012;Frost, Linneker, and Spence 1998;Nam, Lim, and Kim 2012;Titheridge and Hall 2006), often with parallel rises in commuting times (Izreali and McCarthy 1985), particularly for commuting from the outer sprawl areas to the centres of cities (Frost, Linneker, and Spence 1998;Sultana and Weber 2007;Titheridge and Hall 2006;Wang 2001;Zimmer 1985). As cities expand or as one moves to the outer, more dispersed parts of cities, urban densities become lower and workplaces, and residences farther apart.…”

“…This would be expected to lead to longer commuting distances and to increased commuting times. Longer commuting distances with lower urban densities have indeed been observed in a number of cities (Cao and Fan 2012;Frost, Linneker, and Spence 1998;Nam, Lim, and Kim 2012;Titheridge and Hall 2006), often with parallel rises in commuting times (Izreali and McCarthy 1985), particularly for commuting from the outer sprawl areas to the centres of cities (Frost, Linneker, and Spence 1998;Sultana and Weber 2007;Titheridge and Hall 2006;Wang 2001;Zimmer 1985). However, exceptions are by no means uncommon, with average commuting distances in some cases becoming shorter rather than longer with increasing urban sprawl (Crane and Chatman 2003;Titheridge and Hall 2006;Zolnik 2011), and average commuting times falling or remaining static (Gordon, Richardson, and Jun 1991;Lee, Seo, and Webster 2006;Zimmer 1985), sometimes even when commuting distances increased (Levinson and Kumar 1994).…”

The Impact of Built Environment Characteristics on Energy Consumption Using Geographically Weighted Regression in Mashhad, Iran

“…They justified this similarity with tendency to make more non-work visit by Individuals who live in more urbanized than those who live in less urbanized areas. Under a compact development, where there are more alternative for travelers to use different transportation modes, the percentage of individuals using automobiles is decreasing, which reduces the energy consumption (Nam, Lim, & Kim, 2012) However, other studies have realized that the effect of density is modest. Crane and Crepeau (1998) argued that density was associated with quality and quantity of public transportation service and the travel behavior was related to cost variables, for example travel price and time.…”

Three Dimensional Spatial Metrics for Compactness Assessment of Urban Forms

“…Two spatial statistics of MI and GOG have been used so far for measuring centrality/compactness [10][11][12] and concentration of high or low values [9]. MI has been recognized as an effective measurement tool of compactness of socio-economic data at the metropolitan scale [10].…”