Toward a spatial-temporal measure of land-use mix

Gehrke, Steven R.; Clifton, Kelly J.

doi:10.5198/jtlu.2015.725

Cited by 19 publications

(30 citation statements)

References 61 publications

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“…The scale at which we measure the built environment matters (Gehrke & Clifton, 2016). The research in non-motorized transportation has brought attention to the faults of using built environment measures taken over larger areas, such as census geographies or transportation analysis zones (TAZs), as they may be obscuring variations or configurations that have implications for travel.…”

Section: Introductionmentioning

confidence: 99%

Improving Trip Generation Methods for Livable Communities

Clifton¹,

Larco²,

Currans³

et al. 2017

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Type of Report and Period Covered Sponsoring Agency Code Supplementary Notes16. Abstract Recent efforts to improve trip generation data available for transportation impact analysis of new development include the collection of multimodal trip generation data, development of models that account for the built environment, and new recommendations for practice. Building on a long line of research on transportation and built environment, many studies have identified important features of the surrounding built environment that most impact trip rates and mode shares, building on a long line of research on transportation and the built environment. Despite these improvements in data and methods, less attention is placed on identifying the conditions of the site itself and the immediate surrounding environment that influence trip generation and mode choice. To fill this gap, this study builds upon previous work (Contextual Influences on Trip Generation (Project Number: OTREC 2011-407), 2012), re-examines the information collected in that study, and includes new site-level observations. The objective of this study is to examine establishment multimodal trip generation more closely from a finer-grained scale and identify site-level attributes of the built environment that help explain multimodal trip generation. From this, we have the additional objective of developing a framework for trip generation analysis that takes findings from this study into consideration. We placed emphasis on those sites in our previous study with a discord between the expected travel patterns, based upon the larger urban context and built environment of the site, and the observed. The research approach will make use of mixed methods. In addition to using archived data from the previous study, site visits provided direct observation of the overall performance of the site, including travel patterns on and around the site as well as specific site configuration, urban design details and traffic operations. The analysis of this combination of data provided a more complete picture of site-level trip generation and our findings highlight the influence of: people living nearby and using the site; the nature of the land use on the site; the development along arterial roadways; site permeability and access; and the local culture around walking and cycling. Finally, this report ends by reflecting on the numerous concerns identified from practice, the research findings from various recent studies, and the need for a sustainable process for evaluating the transportation impacts of new land development. We present a potential framework to advance the methods for how site plans fit into neighborhood and regional planning, using locally defined standards and goals. Here, we de-emphasize the site and its immediate environs as the primary (and only) scale of analysis and lessen the reliance on the problematic methodologies for estimating site-level travel demand. Rather, we argue that transportation impact analysis would benefit by first taking a district, neighbor...

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Section: Introductionmentioning

confidence: 99%

Improving Trip Generation Methods for Livable Communities

Clifton¹,

Larco²,

Currans³

et al. 2017

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show abstract

“…Table 11 details this list of built environment measures from various regional and national datasets utilized in this study to identify a walkable, smart growth neighborhood. Land use mix embodies a subset of land development pattern measures describing both the composition and configuration of land use types in a landscape (Gehrke & Clifton, 2016). Portland Metro's Regional Land Information System provided parcel-level data to calculate composition measures characterizing the percent of land area or patches of each land use type in a landscape and configuration measures explicitly accounting for the spatial arrangement, shape, and dissimilarity of the landscape patches (Li & Reynolds, 1994;Turner, 2005).…”

Section: Built Environment Measurementmentioning

confidence: 99%

“…In contrast, the zoning effect arises from the multitude of ways to configure a spatial boundary or neighborhood at each level of aggregation (Jelinski & Wu, 1996). The following subsections, organized by the operationalization of the built environment with fixed or sliding scales (Guo & Bhat, 2007;Gehrke & Clifton, 2016), provide a review of previous studies of scale variation to recognize its influence on understanding the built environment determinants of travel.…”

Section: Geographic Scale Variation In Transportation-land Use Researchmentioning

confidence: 99%

“…Examples of fixed zonal systems include administrative, statistical, and artificial boundaries (Gehrke & Clifton, 2016). The use of statistical boundaries (e.g., census units) to describe the local built environment is pervasive in travel behavior research because of the ease of obtaining sociodemographic and economic data for the same boundary (Guo & Bhat, 2007) and their objective approximation of the neighborhood unit (Manaugh & Kreider, 2013).…”

Section: Fixed Geographic Scalesmentioning

confidence: 99%

“…However, this connection between land use mix and pedestrian travel remains complicated by the many measures chosen by researchers to objectively illustrate this intangible environmental construct (Manaugh & Kreider, 2013). A division between research and practice resulting in the provision of measures with imperfect theoretical foundations, which likely hinders the implementation of land use mix as a performance metric in practice (Gehrke & Clifton, 2016). This paper critiques current practice and introduces a land use mix measure reflecting the composition and configuration of local land uses.…”

Section: Introductionmentioning

confidence: 98%

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Land Use Mix and Pedestrian Travel Behavior: Advancements in Conceptualization and Measurement

Gehrke¹

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Smart growth policies have often emphasized the importance of land use mix as an intervention beholding of lasting urban planning and public health benefits. Past transportation-land use research has identified potential efficiency gains achieved by mixed-use neighborhoods and the subsequent shortening of trip lengths; whereas, public health research has accredited increased land use mixing as an effective policy for facilitating greater physical activity. However, despite the celebrated transportation, land use, and health benefits of improved land use mixing and the extent of topical attention, no consensus has been reached regarding the conceptualization and measurement of this key smart growth principle or the magnitude of its link to walking.This dissertation, comprised of three empirical studies, explores this topic in detail.In the first study, activity-based transportation and landscape ecology theory contributed to the introduction of a multifaceted land use mix construct reflected by a set of composition and configuration indicators. This activity-related land use mix construct, and not the commonly used entropy index, was a significant built environmental determinant of walk mode choice and home-based walk trip frequency.In the second study, structural equation modeling was used to establish a connection between residing in a smart growth neighborhood and home-based pedestrian travel.This study discovered a multidimensional depiction of the traveler's residential environment that was reflective of local land use mix, employment concentration, and pedestrian-oriented design. The second-order factor, which described a smart growth ii neighborhood, had a strong and positive effect on the household-level decision to walk for transportation-related and discretionary travel when assessed in a multidirectional conceptual framework.In the final study, the influence of geographic scale selection on the connection between the built environment and active and auto-related travel was explored.Informed by this sensitivity analysis, which underlined the existence of scaling and zoning effects, mode choice for both work and nonwork travel as a function of individual, household, transportation, and built environment features at the home location and destination was modeled. These discrete choice analysis results found that measures of land use mix and density at each trip end had the strongest effect on the decision to walk rather drive or ride in a vehicle for nonwork trips. In all, the findings from this dissertation provide policymakers and practitioners greater specificity in the measurement of land use mix and its connection to pedestrian travel behavior.iii Acknowledgments

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Getting From Here to There: Comment on “Does Compact Development Make People Drive Less?”

Clifton

2017

Journal of the American Planning Association

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Toward a spatial-temporal measure of land-use mix

Cited by 19 publications

References 61 publications

Improving Trip Generation Methods for Livable Communities

Improving Trip Generation Methods for Livable Communities

Land Use Mix and Pedestrian Travel Behavior: Advancements in Conceptualization and Measurement

Getting From Here to There: Comment on “Does Compact Development Make People Drive Less?”

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