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Rates of car ownership in the United States exceed that of all other large nations in the world. This high rate contributes to the unexpressed demand for road space that renders highway expansion useless as a strategy for decreasing traffic congestion. It also necessitates the provision of on-site parking in residential buildings, decreasing the affordability of housing in urban areas. Furthermore, the curb-side parking needed to make room for the high number of cars in the country takes away space that could be used for bike lanes, transit lanes, or widened sidewalks. Therefore, the United States could benefit from a reduction in rates of household car ownership. In this paper, I use cross-sectional data from the National Highway Transportation Survey to determine the impact on heavy and light rail on car ownership in American cities. I find that the presence of heavy rail is associated with a lower rate of car ownership, while the presence of light rail is not.

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Master of Landscape Architecture / Department of Landscape Architecture/Regional and Community Planning / William P. Winslow III / The proposed site development is situated in the ahupua’a of Honouliuli, in the district of Ewa on the island of Oahu, Hawaii and has been given the name Kaiaulu. Currently the University of Hawaii is planning to expand their campus in the Ewa district. The project site is 500 acres with the university occupying 204 acres. The remaining 296 acres of the site will be a mixed-use residential community. The design of the site addresses two main dilemmas: 1) creating a town-gown relationship between the university and surrounding mixed-use community and 2) promote the use of the two transit stations that will be located on the site for the new light rail system that will be implemented on the island in the next few years. To better understand the relationships between the institution and the surrounding neighborhood communities and how to successfully incorporate light rail stations into the communities, research was conducted to address the issues stated above. Literature was reviewed with a focus on the guidelines, principles, terms, and relative issues on each topic. Two precedent studies were then conducted relating to town-gown relationships and the implementation of light rail systems and stations. The program and the placement of the transit stations, the institution, and the mixed-use communities were based on the site inventory and analysis of the existing site. With the strategic placement of the transit stations and the university campus, students and residents of the surrounding community are encouraged to interact. Additionally, by making the transit stations welcoming, convenient, and safe, the light rail encourages the students and residents of the communities to lessen the use of their automobiles and use the public transit as a means of reaching their destinations around the island. The design of Kaiaulu brings the students of the institution and the residents and visitors of the surrounding communities together and creates a strong town-gown relationship.

This report examines how the neighborhoods along the Metro Blue line have changed over the past two decades, and reflects on the current emerging issue in Transit oriented development (TOD), which is promoting equitable transit neighborhoods. The primary study area includes the route of the Metro Blue line through Los Angeles County where the most economically disadvantaged and marginalized communities are located in the county. In order to investigate the impact of the rail line effectively, the concept of Walksheds are used as the units of analysis, which is defined as the area within a half-mile walking distance from the transit station. Focusing on social equity impact of the transit system operation, the comparison analysis between Los Angeles County and the twenty-two Walksheds of each station in the line evaluates the changes in the close-by neighborhoods while also looking at various social demographic indicators that can reflect demographic shifts using decennial Census data of 1990, 2000, and 2010. While looking at the change through time series data analysis vertically, the performance of each station area is examined horizontally. Therefore, comparative analysis is conducted in four stages to figure out the extent to which the neighborhoods have changed, how rapidly the change occurred and whether the neighborhood change occurred in a positive way or not. The result from the four comparative analyses indicates that the Metro Blue line did not work as a catalyst for promoting economic opportunity in the region in spite of the initial expectations of its advocates. In the beginning of the rail operation of 1990, the neighborhoods along the rail line were excluded and poverty was widespread in the region. However, even after two decades, the twenty-two Walksheds along the Metro Blue Line still remain as undesirable places to live and marginalized as compared to the rest of the county. Moreover, the neighborhood change in the twenty-two Walksheds is negatively linked to the Walksheds based on the result of the comparative analysis. / text

This report explores the long-term demographic changes occurring near Dallas Area Rapid Transit (DART) stations. The study area chosen to employ the shift share method consists of two segments of DART stations along the Red Line in Dallas, Texas. The downtown DART study area consists of census tracts surrounding light rail stations: Cedars, Convention Center, Union Station, West End, Akard, St. Paul, and Pearl, and the DART suburban study area consists of census tracts around the following stations: City Place, Mockingbird Station, Lovers Lane, Park Lane, Walnut Hill, Forest Lane, and LBJ/Central. Using the shift share method with demographic data obtained through the US Census Bureau from 1990 and 2005-2009 American Community Survey estimates, this analysis illustrates demographic changes over time as a result of light rail transit investments. The results indicate that demographic characteristics of residents have changed considerably since the introduction of light rail in Dallas. Although the growth trends in the DART neighborhoods are comparable to the growth trends of the city, the DART census tracts on average have experienced greater increases in population, attracted an influx of highly educated residents with higher household incomes, and experienced significant increases in high-density development surrounding transit stations. For the most part, growth has been stronger locally than on a citywide level, and these trends have occurred most noticeably in the downtown DART neighborhoods, where transit and financial measures have sparked a development boom in which total population and housing units have grown by the hundredth and even thousandth percentile. Additionally, these demographic changes create unintended consequences that affect people of varying socio-economic statuses. Although the shift of highly educated, wealthier individuals in neighborhoods creates a greater social mix among residents, lower-income residents of these transit neighborhoods quickly get priced out of their neighborhoods. / text

The 4-step process has been the standard procedure for transit forecasting for over 50 years. In recent decades, researchers have developed ridership forecasting regression models as alternatives to the costly and time consuming 4-step process. The model created by Lane, DiCarlantonio, and Usvyat in 2006 is among the most recent and most widely accepted. It includes station area demographics, central business district (CBD) employment, and the station areas’ built environments to estimate ridership. This report applies the Lane, DiCarlantonio, and Usvyat model to the North Line of Houston’s Metropolitan Transit Authority of Harris County (METRO). The report compares the 2030 ridership forecast created by METRO using the 4-step process with the LDU model forecasts. For the 2030 projections, this report obtained population and employment estimates from the Houston-Galveston Area Council and analyzed the data using Esri ArcMap and Caliper TRANSCadGIS software programs. The LDU model produced unrealistically high ridership numbers for the North Line. It estimated 108,430,481 daily boardings. METRO’s 4-step process predicted 29,900 daily boardings. The results suggest that the LDU model is not applicable to the Houston light rail system and is not a viable alternative to the 4-step process for this specific metropolitan area. The LDU method for defining Houston’s CBD was the main problem in applying the model. It calculated an extremely high CBD employment density compared to other cities of similar size. Even when the CBD size was manipulated to decrease employment density, the model still predicted 212,210 daily boardings for the North Line, nearly 10 times higher than METRO’s 4-step process estimate. In addition to the problems with the definition of the CBD, the creators of the LU model did not specifically explain how to define a metropolitan area. Multiple inconsistent and subjective definitions of a metro area can be used. This report employs three different definitions of the Houston metro, all of which produced three significantly different ridership forecasts in the LDU model. As a result of these flaws, the LDU model does not accurately apply to METRO’s North Line, and it does not serve as a viable alternative to METRO’s 4-step process. / text

abstract: It has been identified in the literature that there exists a "spatial mismatch" between geographical concentrations of lower-income or minority people who have relatively lower rates of car ownership, lower skills or educational attainment and who mainly rely on public transit for their travel, and low-skilled jobs for which they more easily qualify. Given this situation, various types of transportation projects have been constructed to improve public transit services and, alongside other goals, improve the connection between low-skilled workers and jobs. As indicators of performance, measures of job accessibility are commonly used in to gauge how such improvements have facilitated job access. Following this approach, this study investigates the impact of the Phoenix Metro Light Rail on job accessibility for the transit users, by calculating job accessibility before and after the opening of the system. Moreover, it also investigates the demographic profile of those who have benefited from improvements in job accessibility----both by income and by ethnicity. Job accessibility is measured using the cumulative opportunity approach which quantifies the job accessibility within different travel time limits, such as 30 and 45 minutes. ArcGIS is used for data processing and results visualization. Results show that the Phoenix light rail has improved job accessibility of the traffic analysis zones that are along the light rail line and Hispanic and lower-income groups have benefited more than their counterparts. / Dissertation/Thesis / M.U.E.P. Urban and Environmental Planning 2014

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