Effects of the Urban Compactness and Residential Density on Zonal Trip Generation

Abstract

In terms of population density, Seoul is actually one of most densely populated cities in the world. According to data from 1999 and 2000, Seoul was denser than Tokyo, New York, or London, with 16,364 persons per square per kilometers. In previous research and literature, it is expected that city’s high level of compactness would produce fewer inter-zonal trips. Nevertheless, transportation still causes some problems in Seoul and it was also reported that in 2005 South Korea had USD 8 billion in congestion costs, which was around 4% of the GDP. The Korea Transport Database 2010 also shows that people in Seoul make work trips almost 6 days a week; furthermore, one out of three persons use car for commuting every day. The main purpose of this paper, then, is to identify the veracity of the concept that high urban compactness can reduce transportation problem. In order to answer this question this paper determines the degree of urban compactness in each sub-district in Seoul by using a more comprehensive measurement, and analyzes the effect of this urban compactness on trip generation.

In this paper’s urban compactness measurement, 424 sub-districts are categorized according to their relative proportions of residence, manufacture, and trade and service to Seoul in general. These relative proportions for every sub-district are mapped in a hexagonal diagram. In order to make sure that every urban compactness level results in a distinct level of trip generations, the Analysis of Variance is used. Finally, the 424 sub-districts are classified into 3 groups: relatively more compact areas which have relatively more balance land use, manufacture-intense areas, and trade service-intense areas.

After obtaining the level of urban compactness of each sub-district, multiple linear regression analysis models are developed in order to examine effects of urban compactness on productions of inter-zonal trips. In the model, the response variables are the work trip rates (trip per person per day) by overall mode, by car, and by public transit; the explanatory variables are dummy variables which represent levels of urban compactness, the Residential/Nonresidential Ratio which represent the residential density, and socio-economic variables. These variables are analyzed to determine whether any of them should be altered to reduce the travel demand.

Insights obtained from the multiple linear regression analysis are: increasing residential density and urban compactness may result in reducing the demand for work trips out of the sub-district. Furthermore, people who live in high-compact areas are also more encouraged to use public transport than in less compact areas.