Defines the concept of the arcology as conceived by architect Paolo Soleri. Arcology combines "architecture" and "ecology" and explores a visionary notion of a self-contained urban community that has agricultural, commercial, and residential facilities under one roof. Two real-world examples of these projects are explored: Arcosanti, AZ and Masdar City, Abu Dhabi, UAE. Key aspects of the arcology that could be applied to an existing urban fabric are identified, such as urban design fostering social interaction, reduction of automobile dependency, and a development pattern that combats sprawl. Through interviews with local representatives, a holistic approach to applying arcology concepts to the Phoenix Metro Area is devised.

Bicyclist and pedestrian safety is a growing concern in San Francisco, CA,

especially given the increasing numbers of residents choosing to bike and walk. Sharing

the roads with automobiles, these alternative road users are particularly vulnerable to

sustain serious injuries. With this in mind, it is important to identify the factors that

influence the severity of bicyclist and pedestrian injuries in automobile collisions. This

study uses traffic collision data gathered from California Highway Patrol’s Statewide

Integrated Traffic Records System (SWITRS) to predict the most important

determinants of injury severity, given that a collision has occurred. Multivariate binomial

logistic regression models were created for both pedestrian and bicyclist collisions, with

bicyclist/pedestrian/driver characteristics and built environment characteristics used as

the independent variables. Results suggest that bicycle infrastructure is not an important

predictor of bicyclist injury severity, but instead bicyclist age, race, sobriety, and speed

played significant roles. Pedestrian injuries were influenced by pedestrian and driver age

and sobriety, crosswalk use, speed limit, and the type of vehicle at fault in the collision.

Understanding these key determinants that lead to severe and fatal injuries can help

local communities implement appropriate safety measures for their most susceptible

road users.

Economic inequality is always presented as how economic metrics vary amongst individuals in a group, amongst groups in a population, or amongst some regions. Economic inequality can substantially impact the social environment, socioeconomics as well as human living standard. Since economic inequality always plays an important role in our social environment, its study has attracted much attention from scholars in various research fields, such as development economics, sociology and political science. On the other hand, economic inequality can result from many factors, phenomena, and complex procedures, including policy, ethnic, education, globalization and etc. However, the spatial dimension in economic inequality research did not draw much attention from scholars until early 2000s. Spatial dependency, perform key roles in economic inequality analysis. The spatial econometric methods do not merely convey a consequence of the characters of the data exclusively. More importantly, they also respect and quantify the spatial effects in the economic inequality. As aforementioned, although regional economic inequality starts to attract scholars' attention in both economy and regional science domains, corresponding methodologies to examine such regional inequality remain in their preliminary phase, which need substantial further exploration. My thesis aims at contributing to the body of knowledge in the method development to support economic inequality studies by exploring the feasibility of a set of new analytical methods in use of regional inequality analysis. These methods include Theil's T statistic, geographical rank Markov and new methods applying graph theory. The thesis will also leverage these methods to compare the inequality between China and US, two large economic entities in the world, because of the long history of economic development as well as the corresponding evolution of inequality in US; the rapid economic development and consequent high variation of economic inequality in China.

With high potential for automobiles to cause air pollution and greenhouse gas emissions, there is concern that automobiles accessing or egressing public transportation may cause emissions similar to regular automobile use. Due to limited literature and research that evaluates and discusses environmental impacts from first and last mile portions of transit trips, there is a lack of understanding on this topic. This research aims to comprehensively evaluate the life cycle impacts of first and last mile trips on multimodal transit. A case study of transit and automobile travel in the greater Los Angeles region is evaluated by using a comprehensive life cycle assessment combined with regional household travel survey data to evaluate first-last mile trip impacts in multimodal transit focusing on automobile trips accessing or egressing transit. First and last mile automobile trips were found to increase total multimodal transit trip emissions by 2 to 12 times (most extreme cases were carbon monoxide and volatile organic compounds). High amounts of coal-fired energy generation can cause electric propelled rail trips with automobile access or egress to have similar or more emissions (commonly greenhouse gases, sulfur dioxide, and mono-nitrogen oxides) than competing automobile trips, however, most criteria air pollutants occur remotely. Methods to reduce first-last mile impacts depend on the characteristics of the transit systems and may include promoting first-last mile carpooling, adjusting station parking pricing and availability, and increased emphasis on walking and biking paths in areas with low access-egress trip distances.

Transportation infrastructure in urban areas has significant impacts on socio-economic activities, land use, and real property values. This dissertation proposes a more comprehensive theory of the positive and negative relationships between property values and transportation investments that distinguishes different effects by mode (rail vs. road), by network component (nodes vs. links), and by distance from them. It hypothesizes that transportation investment generates improvement in accessibility that accrue only to the nodes such as highway exits and light rail stations. Simultaneously, it tests the hypothesis that both transport nodes and links emanate short-distance negative nuisance effects due to disamenities such as traffic and noise. It also tests the hypothesis that nodes of both modes generate a net effect combining accessibility and disamenities. For highways, the configuration at grade or above/below ground is also tested. In addition, this dissertation hypothesizes that the condition of road pavement may have an impact on residential property values adjacent to the road segments. As pavement condition improves, value of properties adjacent to a road are hypothesized to increase as well. A multiple-distance-bands approach is used to capture distance decay of amenities and disamenities from nodes and links; and pavement condition index (PCI) is used to test the relationship between road condition and residential property values. The hypotheses are tested using spatial hedonic models that are specific to each of residential and commercial property market. Results confirm that proximity to transport nodes are associated positively with both residential and commercial property values. As a function of distance from highway exits and light rail transit (LRT) stations, the distance-band coefficients form a conventional distance decay curve. However, contrary to our hypotheses, no net effect is evident. The accessibility effect for highway exits extends farther than for LRT stations in residential model as expected. The highway configuration effect on residential home values confirms that below-grade highways have relatively positive impacts on nearby houses compared to those at ground level or above. Lastly, results for the relationship between pavement condition and residential home values show that there is no significant effect between them.

Some differences in the effect of infrastructure on property values emerge between residential and commercial markets. In the commercial models, the accessibility effect for highway exits extends less than for LRT stations. Though coefficients for short distances (within 300m) from highways and LRT links were expected to be negative in both residential and commercial models, only commercial models show a significant negative relationship. Different effects by mode, network component, and distance on commercial submarkets (i.e., industrial, office, retail and service properties) are tested as well and the results vary based on types of submarket.

Consequently, findings of three individual paper confirm that transportation investments mostly have significant impacts on real-estate properties either in a positive or negative direction in accordance with the transport mode, network component, and distance, though effects for some conditions (e.g., proximity to links of highway and light rail, and pavement quality) do not significantly change home values. Results can be used for city authorities and planners for funding mechanisms of transport infrastructure or validity of investments as well as private developers for maximizing development profits or for locating developments.

It has been identified in the literature that there exists a link between the built environment and non-motorized transport. This study aims to contribute to existing literature on the effects of the built environment on cycling, examining the case of the whole State of California. Physical built environment features are classified into six groups as: 1) local density, 2) diversity of land use, 3) road connectivity, 4) bike route length, 5) green space, 6) job accessibility. Cycling trips in one week for all children, school children, adults and employed-adults are investigated separately. The regression analysis shows that cycling trips is significantly associated with some features of built environment when many socio-demographic factors are taken into account. Street intersections, bike route length tend to increase the use of bicycle. These effects are well-aligned with literature. Moreover, both local and regional job accessibility variables are statistically significant in two adults' models. However, residential density always has a significant negatively effect on cycling trips, which is still need further research to confirm. Also, there is a gap in literature on how green space affects cycling, but the results of this study is still too unclear to make it up. By elasticity analysis, this study concludes that street intersections is the most powerful predictor on cycling trips. From another perspective, the effects of built environment on cycling at workplace (or school) are distinguished from at home. This study implies that a wide range of measures are available for planners to control vehicle travel by improving cycling-level in California.