Browsing by Author "Nasri, Arefeh"

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    Analysis of the effect of multi-level urban form on bikeshare demand: Evidence from seven large metropolitan areas in the United States
    (Journal of Transport and Land Use, 2020) Nasri, Arefeh; Younes, Hannah; Zhang, Lei
    Bikeshare programs in their current form have been in place for several years in many cities across the United States. Encouraging people to use bikeshare for their daily routine travel has numerous social, economic, environmental, and health benefits. Therefore, it is important to understand factors influencing bikeshare use in different urban areas to improve the system and encourage more use. This paper investigates how the built environment at both local and regional scales influences bikeshare use in seven large metropolitan areas in the U.S. The study areas include Boston, Chicago, Philadelphia, Minneapolis, San Francisco, San Jose, and Washington, D.C., and the data consists of about 12 million bike trips from approximately 2,000 stations over a one-year period. In addition to linear regression models built for each individual city for comparison purposes, a multi-level mixed effect regression model is built to predict the number of trips originated from each station with respect to the local and regional built environment pattern. The results are consistent with previous research on the effect of land use at the local level on bikeshare demand and show that residential density, regional diversity, pedestrian-oriented road network density, and job accessibility via transit all have a significant positive effect on bikeshare demand. At the regional level, results suggest that the overall level of mixed-use development and overall bike-friendliness in the region (i.e., exclusive bike routes, right-of-way, and bike facilities) and higher congestion level in the region are significant factors influencing bikeshare activities and demand. Models developed in this study could be applied to other communities that are seeking to improve and/or expand their bikeshare systems, as well as cities planning to launch new bikeshare programs.
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    How built environment affects travel behavior: A comparative analysis of the connections between land use and vehicle miles traveled in US cities
    (Journal of Transport and Land Use, 2012) Zhang, Lei; Hong, Jinhyun; Nasri, Arefeh; Shen, Qing
    Mixed findings have been reported in previous research regarding the impact of built environment on travel behavior—i.e., statistically and practically significant effects found in a number of empirical studies and insignificant correlations shown in many other studies. It is not clear why the estimated impact is stronger or weaker in certain urban areas and how effective a proposed land use change/policy will be in changing certain travel behavior. This knowledge gap has made it difficult for decision makers to evaluate land use plans and policies according to their impact on vehicle miles traveled (VMT), and consequently, their impact on congestion mitigation, energy conservation, and pollution and greenhouse gas emission reduction. This research has several objectives: (1) re-examine the effects of built-environment factors on travel behavior, in particular, VMT in five US metropolitan areas grouped into four case study areas; (2) develop consistent models in all case study areas with the same model specification and data sets to enable direct comparisons; (3) identify factors such as existing land use characteristics and land use policy decision-making processes that may explain the different impacts of built environment on VMT in different urban areas; and (4) provide a prototype tool for government agencies and decision makers to estimate the impact of proposed land use changes on VMT. The four case study areas include Seattle, WA; Richmond-Petersburg and Norfolk-Virginia Beach, VA; Baltimore, MD; and Washington, DC. Our empirical analysis employs Bayesian multilevel modeling method with various person-level socioeconomic and demographic variables, and five built-environment factors including residential density, employment density, entropy (measuring level of mixed-use development), average block size (measuring transit/walking friendliness), and distance to city center (measuring decentralization and level of infill development). Our findings show that promoting compact, mixed-use, small-block, and infill developments can be effective in reducing VMT per person in all four case study areas. However, the effectiveness of land use plans and policies encouraging these types of land development is different both across case study areas and within the same case study area. We have identified several factors that potentially influence the connection between built environment shifts and VMT changes including urban area size, existing built environment characteristics, transit service cover- age and quality, and land use decision-making processes.
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    A multi-dimensional multi-level approach to measuring the spatial structure of U.S. metropolitan areas
    (Journal of Transport and Land Use, 2018) Nasri, Arefeh; Zhang, Lei
    For many years, attempts to measure the urban structure and physical form of metropolitan areas have been focused on a limited set of attributes, mostly density and density gradients. However, the complex nature of the urban form requires the consideration of many other dimensions to provide a comprehensive measure that includes all aspects of the urban structure and growth pattern at different hierarchical levels. In this paper, a multi-dimensional method of measuring urban form and development patterns in urban areas of the United States is presented. The methodology presented here develops several variables and indices that contribute to the characterization and quantification of the overall physical form of urban areas at various hierarchical levels. Cluster analysis is performed to group metropolitan areas based on their urban form and land-use pattern. This allows for a better utilization of land-use transportation planning and policy analyses used by planners and researchers. This clustering of urban areas could eventually help policymakers and decision makers in the decision-making process to evaluate land-use transportation policies, identify similar patterns, and understand how similar policies implemented in urban areas with similar urban form structure would result in more efficient and successful planning in the future.