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The Effects of Seoul’s Greenbelt on Travel Mode Share in Its Inside and Outside: A Spatial Panel Econometric Analysis
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Abstract: This study provides empirical evidence on the links between urban development factors and the use of specific modes of transport in commuting in the Buenos Aires metropolitan area. The case study is of interest because quantitative research on developing countries is scarce and their rapid urban growth and high rates of inequality may generate different results compared to the US or Europe. This relationship was assessed on locality level using regression methods. Spatial econometric techniques were applied to avoid unreliable inferences generated by spatial dependence and to detect the existence of externalities. Furthermore, we include in the model the socio-economic profile of each locality identified using cluster analysis. The findings reveal that
population density affects motorised transport, that diversity is relevant for public transport and nonmotorised trips, and urban design characteristics affect all modes of transport. Spatial dependence is detected for motorised transport, which may imply the existence of externalities, suggesting the need for coordinated decision-making processes on a metropolitan level. Finally, modal split depends on the socio-economic profile of a locality, which may influence the response to public transport policies. To sum up, these results may be useful when it comes to helping policymakers design integrated
public policies on urban and transport planning.
By growing of population, the concept of urban sprawl is increasingly recognized as a serious dilemma among the cities, especially in developing countries. Kabul is one of those cities which are sprawling for two decades and the implication is that residents are suffering from long travel time, pollution and energy consumption. In Kabul city, the number of users for public transport and walk are decreasing day by day and they are shifting to other alternatives. A detailed study to be made in understanding urban sprawl and urban compactness influences on choice mode. This paper is aimed to evaluate the impact of urban sprawl and urban compactness on travel demand for transport modes in 22 districts in Kabul city. Travel demand modeling by using the traditional four-step transportation forecasting model for the year 2017 has been applied to assess the current number of passengers for each transport mode (public transport, walk and private transport) in all 22 districts. Secondly, urban compactness based on metrics with two indicators, mixed-use and density measured to figure out the level of sprawl and compactness in each district. Finally, travel demand for transport modes in both circumstances (compact and sprawl areas) compared in observed districts. The extracted outcome presented an interesting vision of variation amongst districts in Kabul city. This study revealed a profound relationship between urban sprawl and travel demand for all urban transport modes.
Public health risks such as obesity are influenced by numerous personal characteristics, but the local spatial structure such as an area’s built environment can also affect the obesity rate. This study analyzes and discusses how a greenbelt plan as a tool of urban containment policy has an effect on obesity. This study conducted spatial econometric regression models with five factors (13 variables) including transportation, socio-economic, public health, region, and policy factors. The relationship was analyzed between two policy effects of a greenbelt (i.e., a green buffer zone) and obesity. The variables for two policy effects of greenbelt zones are the size of the greenbelt and the inside and outside areas of the greenbelt. The results indicate that the two variables have negative effects on obesity. The results of the analyses in this study have several policy implications. Greenbelts play a role as an urban growth management policy, leading to a reduced obesity rate due to the influence of the transportation mode. In addition, greenbelts can also reduce the obesity rate because they provide recreation spaces for people.
Transit accessibility to jobs (the ease of reaching a place of work by public transport) affects both residential location and commute mode choice, resulting in gradations of residential land-use intensity and transit (public transport) patronage. We propose a scaling model explaining much of the variation in transit use—the number of transit commuters per km2—and residential land-use intensity with transit accessibility. We find that locations with high transit accessibility consistently have more riders and higher residential density; transit systems that provide greater accessibility and with a larger base for patronage have proportionally greater ridership increase per unit of accessibility. All 48 metropolitan statistical areas in our sample have a scaling factor less than 1, so a 1% increase in access to jobs produces a less than 1% increase in transit riders; the largest cities therefore have higher scaling factors than smaller cities, indicating returns to scale. The models, derived from a new database of transit accessibility measured for every minute of the peak period over 11 million US census-blocks, and estimated for 48 major cities across the United States, find that the number of jobs reachable within 45 minutes of the rider’s base most affect transit rider density. The findings support the idea that transit investment should focus on mature, well-developed regions. Cities not only develop their transit networks, but are shaped by them in return. This study teases out the effects of public transportation, finding that there is a scale effect for urban areas to benefit from transit investment.
Many metropolitan areas around the world aim to control urban growth with a view to achieving efficiency and containing urban problems. Among many urban growth policy tools, the green belt (GB) policy is known as the most rigid and strongest. However, there has been no study on the consequences when GB restrictions are completely removed. The primary purpose of this study is to analyse the spatial effects of greenbelt removal on land development in Korea’s medium-sized cities between 2000 and 2017. To do so, we used the Landsat thematic mapper (TM) 5 satellite image (2000) and Landsat OLI TIRS 8 satellite image (2017) along with various attribute data to model the spatial effects of greenbelt removal in the cases of three medium-sized cities in Korea. The result of difference-in-difference (DID) analysis confirms that the effects of GB removal on land development vary depending on the local conditions of land development.
Problem, research strategy, and findings: Planners commonly recommend compact development in part as a way of getting people to drive less, with the idea that less driving will lead to more sustainable communities. Planners base their recommendations on a substantial body of research that examines the impact of compact development on driving. Different studies, however, have found different outcomes: Some studies find that compact development causes people to drive less, while other studies do not. I use meta-regression analysis to a) explain why different studies on driving and compact development yield different results, and b) combine different findings from many studies into reliable statistics that can better inform planning practice. I address the following questions: Does compact development make people drive less, and if so, how much less? I find that compact development does make people drive less, because most of the compact development features I study have a statistically significant negative influence on driving. The impact, however, is fairly small: Compact development features do not appear to have much influence on driving. My findings are limited to some extent because they are derived from small sample sizes.
Takeaway for practice: Planners should not rely on compact development as their only strategy for reducing driving unless their goals for reduced driving are very modest and can be achieved at a low cost.
Despite earlier attempts to evaluate the consequences of urban containment policy adoption, the transport implications of these policies have been overlooked. This paper examines the impact that containment policies have on population density and vehicle miles travelled per capita. An empirical analysis is conducted, relying on a fixed-effects model for panel data for the largest 25 metropolitan areas in the US during the 1982 –94 time-period. Because the outcomes are endogenously related, instrumental variable regression is used to test hypotheses about the effect of the presence and age of containment policies on travel. The findings suggest that local containment policies and state-level involvement in enabling or mandating growth management are associated with higher population density and more miles travelled. The results uncover unanticipated relationships of containment policies and travel outcomes, and underscore the importance of a co-ordinated strategy to mitigate some of the potential travel consequences of containment policies.
Job-housing balance has been widely studied as a means to promote sustainable urban planning. Many studies have been conducted to explore how to improve the job-housing balance, but there is inadequate evidence of the effects of metro transit. This paper constructs a difference-in-differences (DID) model to investigate the impacts of the presence of metro transit on the job-housing balance. Considering the distribution of metro stations varies between different regions, a continuous DID model is further built to analyze the impacts of metro service intensity (measured by the number of metro stations). The results show that metro transit is negatively associated with job-housing balance, and such an association increases with each year since the metro operation. We find that the job-housing relationship of the districts where the metro passes and its adjacent areas are both impacted by metro transit. The operation of the metro is not conducive to achieve job-housing balance. This research provides an important reference for making supportive policies to improve the regional job-housing balance and to facilitate sustainable urban development.
The issue of residential location segregation by income class has long been discussed and considered in the field of urban geography as a significant social problem. However, research analysing the effect of local commuting accessibility to residential locations by income class is limited. This study aims to reinterpret the classical theory of job-housing imbalance from a modern perspective using analytical methodology. A utility-based local accessibility index for commuting was estimated and accessibility was calculated considering the travel characteristics of households in each income class. The relationship between local commuting accessibility and the residential location of each income class household was analysed considering the spatial correlation between them. The findings showed that positive spatial correlations existed between local commuting accessibility and residential location of houses of all income classes, implying that all households, regardless of income class, are in areas with good access. However, analyses by controlling for housing and residential characteristics of each region showed that middle- and high-income households were in residential locations where accessibility is higher while low-income households were found in residential locations with lesser accessibility.
xsmle is a new user-written command for spatial analysis. We consider the quasi–maximum likelihood estimation of a wide set of both fixed- and random-effects spatial models for balanced panel data. xsmle allows users to handle unbalanced panels using its full compatibility with the mi suite of commands, use spatial weight matrices in the form of both Stata matrices and spmat objects, compute direct, indirect, and total marginal effects and related standard errors for linear (in variables) specifications, and exploit a wide range of postestimation features, including the panel-data case predictors of Kelejian and Prucha (2007, Regional Science and Urban Economics 37: 363–374). Moreover, xsmle allows the use of margins to compute total marginal effects in the presence of nonlinear specifications obtained using factor variables. In this article, we describe the command and all of its functionalities using simulated and real data.
Co-locating jobs and housing is natural to cost-saving individuals but is potentially congestive at a local level. As for quasi-rational locators, whose rationality is limited in finding the best location especially in the short run, their houses and jobs tend to agglomerate, yielding congestion especially in growing localities. In the long run, when more information and time to adapt to such an externality become available, however, jobs-housing (J-H) balance may be improved after short-run imbalance. Graphically, the J-H balance to be expressible in the J-H ratio (X) and commuting efficiency (Y) tend to be linearly traded off at a regional level in the long run, but this trade-off can be U-shaped at a local level especially in the short run. This study discusses long-run stabilisation after short-run dynamic adaptation (periods) to such a U-shaped ‘trade-off’ in and outside the greenbelt of Seoul. Its spatial transitions between 2000, 2005, and 2010 were analysed regarding the quasi-rational commuters' local amelioration of the trade-off. It is shown that commuting time decreased and J-H balance overall improved in the long run. This trend is more apparent in the new towns built between 1989 and 1995 than the nine new towns built after the mid 2000s. Mean commuting time decreased sharply in such most job-rich or formerly housing-rich areas as ones with J-H ratios >2.08 or <1.18. This suggests a quasi-rational-commuter-led transition to improved balance in the long run, despite the greenbelt's commuting-delaying effect. Considering this J-H range, this transition needs to be managed more scientifically, minimising the greenbelt's negative effect with any positive effect untainted.
Conventional thinking suggests that pedestrian-friendly, mixed-land-use developments will contribute to an overall reduction in travel by providing an alternative to automobile travel. However, these elements may serve to increase travel demand by reducing the overall cost of travel-a phenomenon generally known as 'induced' travel. To date, most studies of induced travel have focused on aggregate travel patterns, without examining how development patterns may influence people's trip-making decisions. To fill a void in the empirical research, we examine the potential for induced trip making at mixed-use developments by analyzing data obtained from a survey of travelers at a typical mixed-use site in suburban Dallas, Texas, USA. Our analysis found that during both the morning and afternoon study periods, at least some percentage of internal trips at the case-study site were induced, and not 'captured' from the external street network as is typically assumed. Induced trips by land-use pair and travel mode are also reported. Even with the induced trips, a reduction in regional vehicle-miles traveled can still be realized at mixed-use developments sites due to the propensity for those trips to be made on foot. Induced travel also has implications for the development of traffic-impact studies for proposed mixed-use sites, which generally assume that all internal trips are replacing external trips. Planners, policy makers, politicians, and other stakeholders exploring mixed-use developments as a land-use solution to urban traffic congestion and air-quality issues are encouraged to consider the implications of induced travel in the mixed-use environment.
Problem: Localities and states are turning to land planning and urban design for help in reducing automobile use and related social and environmental costs. The effects of such strategies on travel demand have not been generalized in recent years from the multitude of available studies.Purpose: We conducted a meta-analysis of the built environment-travel literature existing at the end of 2009 in order to draw generalizable conclusions for practice. We aimed to quantify effect sizes, update earlier work, include additional outcome measures, and address the methodological issue of self-selection.Methods: We computed elasticities for individual studies and pooled them to produce weighted averages.Results and conclusions: Travel variables are generally inelastic with respect to change in measures of the built environment. Of the environmental variables considered here, none has a weighted average travel elasticity of absolute magnitude greater than 0.39, and most are much less. Still, the combined effect of several such variables on travel could be quite large. Consistent with prior work, we find that vehicle miles traveled (VMT) is most strongly related to measures of accessibility to destinations and secondarily to street network design variables. Walking is most strongly related to measures of land use diversity, intersection density, and the number of destinations within walking distance. Bus and train use are equally related to proximity to transit and street network design variables, with land use diversity a secondary factor. Surprisingly, we find population and job densities to be only weakly associated with travel behavior once these other variables are controlled.Takeaway for practice: The elasticities we derived in this meta-analysis may be used to adjust outputs of travel or activity models that are otherwise insensitive to variation in the built environment, or be used in sketch planning applications ranging from climate action plans to health impact assessments. However, because sample sizes are small, and very few studies control for residential preferences and attitudes, we cannot say that planners should generalize broadly from our results. While these elasticities are as accurate as currently possible, they should be understood to contain unknown error and have unknown confidence intervals. They provide a base, and as more built-environment/travel studies appear in the planning literature, these elasticities should be updated and refined.Research support: U.S. Environmental Protection Agency.
This article analyzes and discusses U.S. metropolitan suburbanization in three cities with different growth management policies. The study areas are Portland, Minneapolis-St. Paul, and Cleveland Metropolitan Statistical Areas (MSAs). Portland has the Metro, an elected metropolitan government, and an Urban Growth Boundary (UGB). Minneapolis-St. Paul has a tax-sharing policy and the Metropolitan Council (MC) to enhance regional assets and manage urban growth efficiently. In comparison, Cleveland has no distinguishable policy to counteract suburbanization. This study analyzes metropolitan suburbanization in terms of “a trade-off of opportunity cost” of commuting time and jobs-housing balance in the two cities with polices and in the city without policies. The regression and GIS results support the rationale for planning interventions and policy efforts rather than a policy principle of laissezfaire. Planning interventions and growth management polices are considered to help offset the more slowly increasing opportunity cost of commuting time by faster-increasing employment opportunities, towards a higher balanced jobs-housing ratio through efficient land use.
TRB’s Transit Cooperative Research Program (TCRP) Report 95: Chapter 15 – Land Use and Site Design provides information on the relationships between land use/site design and travel behavior. Information in the report is drawn primarily from research studies that have attempted to measure and explain the effects. This report is part of TCRP’s Traveler Response to Transportation System Changes Handbook series. The overarching objective of the Traveler Response to Transportation System Changes Handbook is to equip members of the transportation profession with a comprehensive, readily accessible, interpretive documentation of results and experience obtained across the United States and elsewhere from (1) different types of transportation system changes and policy actions and (2) alternative land use and site development design approaches. This is the second of 19 chapters expected to be published in this series.
This article uses a specific and long-established planning policy, Seoul's greenbelt, to explore the concept of counterfactual planning. Suppose the greenbelt had never existed. How would the spatial structure of the metropolitan region have been different? Under both monocentric and polycentric assumptions, both population and employment (in terms of densities and numbers) would have been much lower in the core city and the periphery. The effects would have been more dramatic in the core city, suggesting that the greenbelt contributed significantly to densification and congestion. Still, its consequences for leapfrog development were far from negligible. In addition, because the greenbelt policy was reinforced by a strong government strategy to build very large new towns beyond the greenbelt, a significant jobs-housing imbalance resulted because people decentralized much faster than jobs. Whether these effects are offset by the recreational and other environmental benefits of the greenbelt is unclear.
This research estimates commuting costs associated with Seoul’s Greenbelt. It uses a density gradient framework for workers and residents and assumes that the Greenbelt results in a major discontinuity in these gradients that would be eliminated if the Greenbelt did not exist. This means abolition of the Greenbelt would result in both more workers and residents within the Greenbelt and fewer outside (both centrally and peripherally). The commuter distance savings from this reallocation form the basis for measuring the commuting costs. The average savings is 5 percent (a reduction from 7.14 km to 6.79 km); Greenbelt workers and residents would achieve substantial savings that are not fully offset by modest increases for those in the non-Greenbelt zones. Total commuting costs associated with the current Greenbelt are 12.01 per commuter), or 72.02 per commuter) including the value of travel time.
The balance between jobs and housing has received considerable attention in the recent debates over sustainable urban development. The excess commuting technique, which measures the difference between the average observed commute and the average minimum commute, has been suggested as one means to identify the numerical imbalance between workplaces and residential locations. This paper extends the conventional approach through the development of an extended excess commuting technique, which can measure both the quantitative and qualitative imbalance. The empirical results show that commuters in the Seoul Metropolitan Area (SMA) have tried to reduce both qualitative and quantitative imbalance based on time rather than distance over the past 10 years (1990-2000). The results show how the spatial processes of decentralisation have been countered by the economic processes of faster travel, and how the net result is a saving in the journey to work travel time.
The study aims to estimate commuting costs of the “leap-frog” new town development in the Seoul Metropolitan Area. In order to measure the commuting costs of the “leap-frog” new town development, we assume a contiguous new town construction to Seoul, allowing new town development within Seoul's Greenbelt.Total VMT savings from the contiguous new town development to Seoul are 744 million km/year. Average commuting distance would be shortened by 1.5% for every worker of the SMA if 196 thousand workers (2.7% of total jobs) and 420 thousand residents (5.7% of total commuters) in new towns have been relocated into hypothetical new towns. Total commuting costs associated with the leapfrog new town development are 5.82 per commuter), or 34.88 per commuter) including value of travel time.The biggest benefit goes to the workers who live or work in the new towns with the “contiguous new town development” scenario. The average work trip distances of residents and workers of new towns would have substantially decreased by 27% and 17%, if the five new towns had been developed contiguously to Seoul. VKT savings for the residents and workers of the new towns are 1141 million km/year and 256 million km/year, respectively. New town residents would gain commuting cost savings of 927/year including the value of travel time by the relocation of new towns towards Seoul.
A study of six companies in Greater Oslo indicates that both the modal split and the energy use for journeys to work are to a high extent influenced by the geographical location of the workplace. Employees of workplaces in peripheral, low-density parts of the urban area are far more frequent car drivers and use considerably more energy for journeys to work than employees of workplaces located in central, high-density areas. A study of long-term consequences of workplace relocations within the urban area shows that the immediate increase in average commuting distance of a workplace moving to the urban fringe, has not been reversed by subsequent turnover and residential changes among the employees.
Urban containment policies attempt to manage the location, character, and timing of growth to support a variety of goals such as compact development, preservation of greenspace, and efficient use of infrastructure. Despite prior research evaluating the effects of urban containment policies on land use, housing, and transportation outcomes, the public health implications of these policies remain unexplored. This ecologic study examines relationships among urban containment policies, state adoption of growth-management legislation, and population levels of leisure and transportation-related physical activity in 63 large metropolitan statistical areas from 1990 to 2002.
Multiple data sources were combined, including surveys of urban containment policies, the Behavioral Risk Factor Surveillance System, the U.S. Census of Population, the National Resources Inventory, and the Texas Transportation Institute Urban Mobility Study. Mixed models were used to examine whether urban containment policies and state adoption of growth-management legislation were associated with population levels of leisure-time physical activity (LTPA) and walking/bicycling to work over time.
Strong urban containment policies were associated with higher population levels of LTPA and walking/bicycling to work during the study period. Additionally, residents of states with legislation mandating urban growth boundaries reported significantly more minutes of LTPA/week compared to residents of states without such policies. Weak urban containment policies showed inconsistent relationships with physical activity.
This study provides preliminary evidence that strong urban containment policies are associated with higher population levels of LTPA and active commuting. Future research should examine potential synergies among state, metropolitan, and local policy processes that may strengthen these relationships.
This paper evaluates household travel surveys for the Washington metropolitan region conducted in 1968 and 1988, and shows that commuting times remain stable or decline over the twenty year period despite an increase in average travel distance, after controlling for trip purpose and mode of travel. The average automobile work-to-home time of 32.5 minutes in both 1968 and 1988 is, moreover, very consistent with a 1957 survey showing an average time of 33.5 minutes in metropolitan Washington. Average trip speeds increased by more than 20 percent, countering the effect of increased travel distance. This change was observed during a period of rapid suburban growth in the region. With the changing distributional composition of trip origins and destinations, overall travel times have remained relatively constant. The hypothesis that jobs and housing mutually co-locate to optimize travel times is lent further support by these data. .
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