Mark W. Horner

Spatial Dimensions of Urban Commuting: A Review of Major Issues and Their Implications for Future Geographic Research∗

Abstract Modern urban transportation systems continuously challenge, and are challenged by, the changing nature of 21st-century travel demand. Today, congestion is the norm in cities of the United States, and researchers and practitioners are seeking solutions to these problems. Urban commuting is identified as contributing to the suboptimal performance of transportation systems. This paper offers a review and critique of recent research on urban commuting, emphasizing geographical dimensions of this topic. Three broad areas of research related to urban commuting are discussed. These include (1) urban sustainability, (2) land use, and (3) geographic information systems (GIS). Major themes are examined in an effort to elicit thought on future geographic research. At the conclusion of the paper, summary remarks are provided and avenues for research are outlined.

EXTENSIONS TO THE CONCEPT OF EXCESS COMMUTING

When people commute to work longer or farther than the actual spatial arrangement of homes and workplaces suggest they could be commuting, people are engaging in excess commuting. In the aggregate, excess commuting is the nonoptimal or surplus work travel occurring in cities because people do not minimize their journeys to work. In this paper an alternative view of excess commuting based on a theoretical maximum commute is presented. The calculation of a theoretical maximum commute allows for an analysis of the range between the theoretical minimum and maximum commutes, which marks an improvement over current approaches to the measure of excess commuting. Conceptually, this range is taken to be the commuting capacity of a city. To what extent commuting capacity is consumed in terms of current levels of commuting forms a primary question of the analysis. A model is formulated and applied to 1990 Census data for a sample of US cities. Numerical and visual results suggest variation in the amount of excess commuting and consumed commuting potential for the sample of cities. The results also suggest a relationship between the jobs – housing balance of a city (as captured by its theoretical minimum commute) and its observed commute. Additionally, the maximization calculation is shown to provide insight into the degree of decentralized urban form. A conclusion is provided which relates the findings of this research to larger issues of urban sustainability.

Excess Commuting and the Modifiable Areal Unit Problem

Excess commuting has emerged during the past two decades as an important construct for evaluating the spatial relationships between employment and residential locations. During this time-period, there has been an on-going debate regarding how one should measure excess commuting in urban regions. This paper contributes to the debate by focusing on the spatial issues inherent in excess commuting evaluation. We demonstrate how scale and unit definition (the modifiable areal unit problem) are manifested in the assessment of excess commuting, both in theoretical and empirical terms. To this end, a geographical information systems-based analysis is presented which explores spatial sensitivities in the excess commuting measure. Our results show that aggregation and spatial unit definition may have profound impacts on the estimation of excess commuting. This work provides a formal resolution to much of the recent debate regarding estimates of excess commuting in urban regions.

EMBEDDING ECONOMIES OF SCALE CONCEPTS FOR HUB NETWORK DESIGN.

Abstract We explore the idea of endogenous hub location on a network. In contrast to much of the literature, we propose that hub networks may emerge naturally out of a set of assumptions and conditions borrowed from equilibrium traffic assignment. To this end, we focus on applying a nonlinear cost function that rewards economies of scale on all network links. A model is presented and implemented in a GIS environment using both a 100-node intercity matrix and several synthesized interaction matrices. We compare solutions for different assumptions about network costs, and visualize the results. We find that under discounted conditions, network flow is re-routed to take advantage of the cost savings for amalgamation and that several cities emerge as centers through which large amounts of flow pass. Larger cities such as Los Angeles, New York and Chicago serve gateway functions. We also find that smaller cities such as Oklahoma City, Pittsburgh, Indianapolis, and Knoxville serve major gateway functions because of their locational advantages. Our paper should be of interest to the planner of a surface transportation system, or those interested in nodal concepts such as gateways and transport geography. Results are discussed in light of hub and spoke networks and suggestions are made for future research.

Life Cycle and Environmental Factors in Selecting Residential and Job Locations

Home and workplace location choices are closely related. The determinants of these choices operate differently based on an individuals life cycle, particularly with regard to the presence or absence of children. Individuals with children often place value on greenspace and recreational opportunities, while those without children often prefer smaller residential lots and locations with access to services. Existing studies have found that if residential location desires are satisfied, people are less likely to emphasize the importance of job location irrespective of their life stage. Taking a different approach, this study examines home-workplace decisions from a commuting standpoint. Commute durations and personal characteristics are used to analyse individual behavior. The contributions of this work include the finding that environmental characteristics and amenities may explain the connection between commuting behavior and residential location choices. Existing studies have not connected environmental characteristics and commuting behavior. This study also uses various GIS modeling techniques to explore the effects of previously unanalysed variables on residential location decisions.

Effects of Point Pattern Shape on Home-Range Estimates

Abstract Home-range estimators are commonly tested with simulated animal locational data in the laboratory before the estimators are used in practice. Although kernel density estimation (KDE) has performed well as a home-range estimator for simulated data, several recent studies have reported its poor performance when used with data collected in the field. This difference may be because KDE and other home-range estimators are generally tested with simulated point locations that follow known statistical distributions, such as bivariate normal mixtures, which may not represent well the space-use patterns of all wildlife species. We used simulated animal locational data of 5 point pattern shapes that represent a range of wildlife utilization distributions to test 4 methods of home-range estimation: 1) KDE with reference bandwidths, 2) KDE with least-squares cross-validation, 3) KDE with plug-in bandwidths, and 4) minimum convex polygon (MCP). For the point patterns we simulated, MCP tended to produce more accurate area estimates than KDE methods. However, MCP estimates were markedly unstable, with bias varying widely with both sample size and point pattern shape. The KDE methods performed best for concave distributions, which are similar to bivariate normal mixtures, but still overestimated home ranges by about 40–50% even in the best cases. For convex, linear, perforated, and disjoint point patterns, KDE methods overestimated home-range sizes by 50–300%, depending on sample size and method of bandwidth selection. These results indicate that KDE does not produce home-range estimates that are as accurate as the literature suggests, and we recommend exploring other techniques of home-range estimation.

Optimizing hurricane disaster relief goods distribution: model development and application with respect to planning strategies.

Over the last few years, hurricane emergencies have been among the most pervasive major disruptions in the United States, particularly in the south-east region of the country. A key aspect of managing hurricane disasters involves logistical planning to facilitate the distribution and transportation of relief goods to populations in need. This study shows how a variant of the capacitated warehouse location model can be used to manage the flow of goods shipments to people in need. In this application, the model is used with protocols set forth in Floridas Comprehensive Emergency Plan and tested in a smaller city in north Florida. Scenarios explore the effects of alternate goods distribution strategies on the provision of disaster relief. Results show that measures describing peoples accessibility to relief goods are affected by the distribution infrastructure used to provide relief, as well as assumptions made regarding the population(s) assumed to be in need of aid.

Exploring Metropolitan Accessibility and Urban Structure

Location-based assessments of accessibility gauge the attraction of a place relative to other places. These approaches have been used extensively in models of commuting and urban structure. Even though locational accessibility measures are integral to such efforts, they may also be used to explore aspects of urban spatial structure. As such, this paper presents a GIS-based analysis of locational accessibility for a sample of U.S. metropolitan areas. Indices of accessibility based on spatial interaction models are developed for intraurban residential and employment locations. Results show that residential accessibility patterns are similar across cities, taking a concentric pattern where the central urban area is most attractive. However, employment accessibility varies more from city to city; moreover, the areas of highest employment accessibility tend to be decentralized within their respective regions. Overall, location-based accessibility indices are useful for exploring urban form, particularly with respect to issues of urban sprawl. Directions for future research are identified, including linking comparative urban accessibility measures to ongoing work on commuting, the jobs-housing balance, and urban structure.

Using urban commuting data to calculate a spatiotemporal accessibility measure for food environment studies

Improving spatial access to healthy foods in urban regions is recognized as an important component of reducing the prevalence of chronic illness and achieving better health outcomes. Previously, researchers exploring this domain have calculated accessibility measures derived from the travel cost from home locations to nearby food stores. This approach disregards additional opportunities that present themselves as residents move throughout the city. A time-geographic accessibility measure is utilized to explore how single-occupancy automobile commuting affords access to supermarkets. Results show residents in some TAZs have more access when accounting for their commuting behavior than when measuring access from their home. This finding suggests more nuanced calculations of accessibility are necessary to fully understand which urban populations have greater access to healthy food.

A Multi-objective Approach to Improving Regional Jobs-Housing Balance

H ORNER M. W. and M URRAY A. T. (2003) A multi-objective approach to improving regional jobs-housing balance, Reg. Studies 37 , 135-146. Congestion is one of the most significant problems facing urban regions. It is well recognized that congestion is largely a by-product of the work commute, suggesting spatial imbalances in the locations of jobs relative to the location of housing. While jobs-housing imbalances persist in most urban areas, research indicates that associated commuting (and congestion) tends to be more than it need be. Addressing these issues, we extend the classic transportation problem to deal with regional jobs-housing imbalances. Application results are presented using journey-to- work data for the Atlanta metropolitan region. Several scenarios are evaluated, demonstrating the inherent flexibility of this modelling approach in addressing the long-term management of congestion. Our results show that policies affecting the distribution of workers are more likely to decrease commuting, as opposed to policies aimed at altering the distribution of jobs. The model may be used as a strategic tool to guide land use decisions aimed at addressing jobs-housing balance, which may ultimately ameliorate the effects of congestion, emissions and related externalities.