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A large proportion of energy demand comes from urban areas, mostly from buildings and transport, the use of which has impacts on climate and air quality through the emissions of greenhouse gases and other pollutants. To effectively mitigate these impacts, a better understanding of the relationship between energy and urban form variables is crucial. The link between energy and urban variables has been demonstrated before and it is recognised in many aspects of the cities, such as human behaviour and transport dynamics. This research goes forward by analysing the correlation and scaling between energy consumption and different land use typologies derived from urban form variables, as well as at other scales. The work is built on readily available datasets for England to guarantee the replicability of the methodology and ensure the reliability of the results. A combined energy use metric integrating buildings and commute transport produces helpful insights into energy consumption patterns and it is obtained at a large geographic scale. The identification of local scale consumption patterns is attractive to policymakers and planners by providing them detailed information to direct local-level policies. On the other hand, the derived land use typologies deliver new knowledge about the spatialisation of the urban system and to establish the link with the energy use. The results reveal that the relationship between energy and urban variables favours the application of compact city to reduce carbon-based energy consumption. This means that better energy efficiency is achieved by areas with higher population density. The analysis also shows that socio-economic variables have higher impact on energy consumption than physical variables. Moreover, differences at city scale and for the land use typologies are identified, demonstrating the importance of focusing the analysis according to the goal. In sum, the results from this work provide new insights about the relationship between energy and urban characteristics that can be used by policymakers and planners to outline more focused and detailed actions to mitigate energy use in England.

This thesis provides a detailed case study of the havelis of Jaisalmer, Rajasthan. Jaisalmer was selected as the study area not only because of the abundance and richness of the havelis in this region, but also because of the extreme nature of the climate in and around the area. In addition, the haveli has the added advantage of being a high-density urban form; economically and ecologically significant in the context of India's rapidly expanding urban population and associated energy and environmental crisis. Environmental data was collected in and around two havelis within the fort, over a period of twelve months, focusing on the larger of the two monitored buildings, Hotel Suraj. In addition a short transverse comfort survey was conducted on the streets of Jaislamer, and subsequently evaluated in the wider context of accepted adaptive model comfort prediction equations. The results of the survey are applied to the assessment of the collected environmental data, in terms of predicted occupant thermal comfort. The relationship between indoor and outdoor temperature is examined in detail and an attempt made to develop indoor temperature prediction equations for each of four long term monitored zones in Hotel Suraj. With all results revealing mass as the governing factor for the modification of climate in the havelis, a substantial portion of this thesis is subsequently focused on developing methodologies for determining the decrement factor and time lag of indoor zones in relation to outdoors. A new finding is the impossibility of a shift in daily temperature cycle of more than 6 hours (or 0.25 of the cycle frequency). Considerable effort has been expended on the visual presentation of data for this study. This has involved the development of two stand-alone computer programs for the presentation of thermal data, included on the CD at the end of this thesis.

The widespread adoption of autonomous cars has the potential to revolutionize urban transportation, but what impact will it have on urban form? This thesis examines the hypothesis that adopting autonomous cars can transform street space into a more human-centric purpose, leading to more livable and sustainable cities. The research was conducted through a literature review, analysis of case studies, and the development of specific street designs in order to reveal possible scenarios. The literature review suggests that adopting autonomous cars can reduce the need for parking and increase the efficiency of transportation. Furthermore, the rise of shared cars is expected to revolutionize the way people move. With the advent of autonomous cars, it is possible that personal cars will become less necessary as people can rely on these constant-moving vehicles for transportation. These changes will impact our cities creating new opportunities to improve the urban space. The thesis explores these challenges and opportunities through design for the actual urban environment of Washington D.C. As the capital of the United States, the country where cars have significantly shaped its cities, it is also home to influential political and policy-makers. As a result, the city offers a good opportunity to rethink the future urban environment when this technology will be widely adopted. The findings of this thesis suggest that the adoption of autonomous cars has the potential to transform urban form reclaiming street space for people, but also requires careful planning and design to ensure that the benefits are distributed equitably and the negative impacts are minimized. The thesis concludes with four street proposals, each performing a different role in the city and the results provoke a reflection of the role of the street in our cities.

This dissertation explores urban form metrics and their environmental outcomes, the impact of motorways on urban sprawl, and transportation accessibility across three interrelated chapters. Chapter 1 begins by examining the relationship between urban form metrics in 462 cities worldwide. By employing the K-Means clustering algorithm and statistical analysis, we uncover distinct typologies of urban form, highlighting the complex relationship between measures such as weighted density, street connectivity, compactness and two environmental outcomes—air pollution and green space access. Findings demonstrate that the emphasis on higher density comes with trade-offs in green space and PM2.5 exposure, while street connectivity is crucial for reducing PM2.5 emissions. Context-specific correlations caution against generalizations, providing a foundation for understanding urban processes and identifying effective policy responses. Chapter 2 examines the impact of motorways on urban sprawl by investigating the correlation between motorway construction period and two key urban form metrics—street connectivity and density—across diverse understudied global contexts. By temporally separating the effects and utilizing a panel fixed effects model, we mitigated concerns related to endogeneity, allowing for a better understanding of the causal impact of motorways. Results highlight the context-dependent nature of the impact of motorway construction and proximity on urban sprawl across various areas. In Chapter 3, we introduce the Individual Experienced Utility-Based Synthesis (INEXUS) accessibility metric, designed to improve upon existing accessibility metrics by accounting for individual preferences and constraints within an agent-based regional transportation model. By differentiating between Potential INEXUS and Realized INEXUS, this metric offers a comprehensive view of transportation accessibility, considering the diverse needs of various subpopulations. We apply this approach to a case study involving alternative ridehail pricing scenarios, demonstrating its effectiveness in evaluating differences in accessibility within and between population groups. These three chapters collectively contribute to a more comprehensive understanding of the complex dynamics at play in urban areas, offering insights for policymakers, urban planners, and researchers. The dissertation underscores the importance of context-specific urban planning and transportation policies, emphasizing the need for sustainability, equity, and adaptability in the face of urban challenges, providing insights for shaping more resilient and inclusive cities.

Through rapid urbanisation, urban green spaces (UGS) have become increasingly limited and valuable in high-density urban environments. However, meeting the diverse requirements of sustainable urban development often leads to conflicts in UGS usage. For example, the presence of stormwater treatment facilities may hinder residents' access to adjacent UGS. Traditional approaches to UGS design typically focus on separate evaluations of human wellbeing and stormwater management. However, using questionnaires, interviews, and surveys for human wellbeing evaluation can be challenging to generalise across different projects and cities. Additionally, professional hydrological models used for stormwater management require extensive knowledge of hydrology and struggle to integrate their 2D evaluation methods with 3D models. To address these challenges, this thesis proposes a novel framework to integrate the two types of analysis within a system for balancing the needs of human wellbeing and stormwater management in UGS design. The framework incorporates criteria and parameters for evaluating human wellbeing and stormwater management in a 3D model and introduces an approach to compare these two needs in terms of UGS area and suitable location. The contributions of this thesis to multi-objective UGS design are as follows: (1) defining human wellbeing evaluation through Accessibility and Usability assessment, which considers factors such as connectivity, walking distance, space enclosure, and space availability; (2) simplifying stormwater evaluation using particle systems and design curves to streamline complex hydrological models; (3) integrating the two evaluations by comparing their quantified requirements for UGS area and location; and (4) incorporating parameters to provide flexibility and accommodate various design scenarios and objectives. The advantages of this evaluation framework are demonstrated through two case studies: (1) the human wellbeing analysis based on spatial parameters in the framework shows sensitivity to site variations, including UGS quantity and distribution, population density, terrain, road context, height of void space, and more; (2) the simplified stormwater analysis effectively captures site variations represented by UGS quantity and distribution, building distribution, as well as terrain, providing recommendations for each UGS with different types and sizes of stormwater facilities. (3) With the features of spatial parameter evaluation, the framework is feasible to adjust relevant thresholds and include more parameters to respond to specific project needs. (4) By quantifying the two different requirements for UGS and comparing them, any UGS with high usage conflicts can be easily identified. By evaluating all proposed criteria for UGSs in the 3D model, designers can conveniently observe simulation and adjust design scenarios to address identified usage conflicts. Thus, the proposed evaluation framework in this thesis would be valuable in effectively supporting further multi-objective UGS design.

The introduction and emphasis of the automobile in the early 20th century changed the course of the development of American cities. It gave rise to suburbia and the American Dream. The infrastructure that supported the automobile shaped and defined the extents of the city. The automobile allows for the extents of urban environments to grow outwards threating agricultural lands that support the nation. Emerging social trends and advancements in transportation could be the next step toward a healthier and more sustainable urban environment. As nations all over the world discuss and debate the means and methods for achieving sustainable futures, society’s dependence on an outdated machine designed for consumption seems counterintuitive and hypocritical. It’s time to reconsider American cities and infrastructure.

The commercial deployment of automated vehicles (AVs) is around the corner. With the development of automation technology, automobile and IT companies have started to test automated vehicles. Waymo, an automated driving technology development company, has recently opened the self-driving service to the public. The advancement in this emerging mobility option also drives transportation reasearchers and urban planners to conduct automated vehicle-related research, especially to gain insights on the impact of automated vehicles (AVs) in order to inform policymaking. However, the variation with urban form, the heterogeneity of mode choice, and the impacts at disaggregated levels lead to the dynamics of the impacts of AVs, which not comprehensively understood yet. Therefore, this dissertation extends existing knowledge base by understanding the dynamics of the impacts from three perspectives: (1) examining the role of urban form in the performance of SAV systems; (2) exploring the heterogeneity of AV mode choices across regions; and (3) investigating the distribution of energy consumption in the era of AVs. To examine the first aspect, Shared AV (SAV) systems are simulated for 286 cities and the simulation outcomes are regressed on urban form variables that measure density, diversity, and design. It is suggested that the compact development, a multi-core city pattern, high level of diversity, as well as more pedestrian-oriented networks can promote the performance of SAVs measured using service efficiency, trip pooling success rate, and extra VMT generation. The AV mode choice behaviors of private conventional vehicle (PCV) users in Seattle and Knasas City metropolitan areas are examined using an interpretable machine learning framework based on an AV mode choice survey. It is suggested that attitudes and trip and mode-specific attributes are the most predictive. Positive attitudes can promote the adoption of PAVs. Longer PAV in-vehicle time encourages the residents to keep the PCVs. Longer walking distance promotes the usage of SAVs. In addition, the effects of in-vehicle time and walking distance vary across the two examined regions due to distinct urban form, transportation infrustructure and cultural backgrounds. Kansas City residents can tolerate shorter walking distance before switching to SAV choices due to the car-oriented environment while Seattle residents are more sensitive to in-vehicle travel time because of the local congestion levels. The final part of the dissertation examines the demand for energy of AVs at disaggregated levels incorporating heterogeneity of AV mode choices. A three-step framework is employed including the prediction of mode choice, the determination of vehicle trajectories, and the estimation of the demand for energy. It is suggested that the AV scenario can generate -0.36% to 2.91% extra emissions and consume 2.9% more energy if gasoline is used. The revealed distribution of traffic volume suggests that the demand for charging is concentrated around the downtown areas and on highways if AVs consume electricity. In summary, the dissertation demonstrates that there is a dynamics with regard to the impacts and performance of AVs across regions due to various urban form, infrastructure and cultural environment, and the spatial heterogeneity within cities.

The impacts of climate change are beyond the observable effects on the environment and it requires extensive efforts in all aspects of society to take actions and ensure a sustainable future. Therefore, it is crucial for policymakers to understand the associated risks, plan for the adverse impacts brought by climate change and make informed decisions. To assist this, through a variety of operations research models and case studies from three projects, this dissertation examines climate change mitigation and adaptation strategies and explores relevant policy implications at three different scales: the urban city level, the individual project level, and the national level. Chapter 2 focuses on vehicle fuel efficiency policies at the urban scale. Given the large and rapidly increasing share of global energy consumption taking place in cities, it becomes crucial to understand the interactions between urban form and energy consumption and avoid unintended policy consequences. By extending the classic monocentric city model to incorporate endogenous investment in vehicle fuel efficiency by households, we investigate the systemic impacts of vehicle fuel efficiency on urban form and urban form feedbacks for energy consumption in cities. We prove analytically that raising vehicle fuel efficiency induces a more compact urban form if households are underinvesting in efficiency, but a more sprawling urban form if efficiency is increased beyond the rational household optimum. In the former case, the urban form adjustment further reduces energy use in the transportation and residential sectors. In the latter case, the urban form adjustment increases vehicle travel, which offsets at least some of the direct reduction in transportation energy use stemming from the efficiency improvement (direct rebound). Additionally, its larger homes demand more energy in the residential sector (indirect rebound). Numerical illustrations are included to confirm the analytical findings for a stylized city. Chapter 3 addresses decision-making under uncertainty on infrastructure resilience upgrade programs. As climate change threatens to cause increasingly frequent and severe natural disasters, decision-makers must consider costly investments to enhance the resilience of critical infrastructures. Evaluating these potential resilience improvements using traditional cost-benefit analysis (CBA) approaches is often problematic because disasters are stochastic and can destroy even hardened infrastructure, meaning that the lifetimes of investments are themselves uncertain. In this work, we develop a novel Markov decision process (MDP) model for CBA of infrastructure resilience upgrades that offer prevention (reduce the probability of a disaster) and/or protection (mitigate the cost of a disaster) benefits. Stochastic features of the model include disaster occurrences and whether or not a disaster terminates the effective life of an earlier resilience upgrade. From our MDP model, we derive analytical expressions for the decision-maker’s willingness to pay (WTP) to enhance infrastructure resilience and conduct a comparative static analysis to investigate how the WTP varies with the fundamental parameters of the problem. The applicability of this MDP framework is demonstrated by two case studies of electric utility infrastructure hardening programs. The first case study considers elevating a flood-prone substation and the second evaluates upgrading transmission structures to withstand high winds. Results from these two case studies show that assumptions about the value of lost load during power outages and the distribution of customer types significantly influence the WTP for the resilience upgrades and are material to the decisions of whether or not to implement them. In Chapter 4, we use the US-TIMES model to explore the decarbonization pathways in the U.S. by modeling portfolios of granular sectoral mitigation policies in the electricity, transportation and buildings sectors. By combining the complementary dimensions of techno-economic and political-organizational feasibilities, we design three different policy scenarios based on portfolios of sectoral mitigation policies that would be politically feasible under Low Alignment, Medium Alignment and High Alignment scenarios of the federal government’s commitment to reducing GHG emissions. We compare these three scenarios with the business-as-usual (BAU) scenario and a stylized 80% system-wide decarbonization scenario. This work contributes to the literature by incorporating granular sectoral climate policies in an energy system optimization to enhance policy realism. Our findings highlight the significance of decarbonizing the electricity sector and electrifying the other sectors such as transportation to cost-effectively reduce GHG emissions. Given the complexity of the energy system, the effectiveness of sectoral policies should be evaluated from a systems level. Our findings also reveal that the GHG emissions reduction relative to 2010’s emissions in Low Alignment, Medium Alignment and High Alignment scenarios are 24.4%, 36.5%, and 44.3%, respectively. The average abatement costs of employing these portfolios of policies are $16.2, $15.8 and $12.8/tCO2e, which are 4.1, 2.1, 1.6 times as high as the average abatement costs obtained through the optimal (least system-wide cost) decarbonization pathways. The AACs that we obtain in this study is lower than mainstream estimates of Social Cost of Carbon (Interagency Working Group on Social Cost of Greenhouse Gases, 2015; Nordhaus, 2017). This suggests that even if political considerations mean that we do not necessarily follow the most cost-effective approach to decarbonize the economy, there are still likely to be net benefits. Each of these three projects, on its scale, captures the underlying characteristics of climate change mitigation or adaptation strategies. While the focus of each project varies, they serve the common goal of providing system-wide and high-level insights on decision-making for cost-effectively reducing GHG emissions or adapting to the impacts of climate change.

Urban biodiversity plays an important role in ecological processes and ecosystem services within cities, making conservation a priority in many municipal sustainability plans. Urban green spaces (UGS) have been a key strategy for conservation by providing habitat for wildlife, including bird communities. While the ecological attributes necessary to enhance the habitability of UGS for bird communities are relatively well known, an understanding of how variation of surrounding urban built form influences avian richness outcomes in these spaces is less understood. As new urban areas continue to develop and UGS become increasingly important habitat areas, urban designers and planners will need a better understanding of the ways in which urban built form patterns influence avian biodiversity outcomes in UGS. To that end, this study investigates this relationship using high resolution land cover data, building LiDAR data, and twenty years of bird occurrence data from the eBird community science program in well-surveyed UGS in Los Angeles, California. Results confirm previous findings that an increase in UGS size is associated with more avian richness. Interestingly, both multivariate regression models, urban form metrics and site-level metrics, performed well in predicting avian richness. Moreover, an increase in the following urban built form metrics, Aggregation Index and Landscape Shape Index, were associated with higher levels of richness, suggesting that more compact and complex shape building patterns support better avian richness outcomes in UGS. These findings contribute to a more complete understanding of how urban built form patterns influence avian biodiversity outcomes and inform urban planning and design of new urban areas aiming to maximize ecological potential for avian biodiversity conservation.

The Baghdad–Berlin Railway played a central role in the modernization of the City of Mosul, including its urban form, its architecture, and its housing. The development of railway infrastructure led to the opening of new streets, particularly Nineveh (Ninawa) Street, and the establishment of the Mosul railways and its complex, including the Mosul railway station and the railway workers’ housing. Comparative case studies will illustrate the railway’s impact on the modernization, urban form, architecture, and housing of cities in other locations to show how the establishment of the railway and changes in technology impacted the town’s conversion into a different type of city, a city with an ethnically mingled community. This conversion can inspire current urban and architectural designers in the development and reconstruction of this city, especially given its present devastation resulting from the war to liberate it from ISIS.

Most previous studies on vitality were conducted through qualitative method. Though there is a new trend that conducting quantitative research on relationship between urban form and urban vitality, with many new breakthroughs in recent technological advancements, there is still a lack of studies on urban vitality from a perspective of social media data. This report focuses on an exploratory analysis of how impacts of urban form effect on urban vitality through a quantitative method. It particularly explores influence of the six identified metrics of urban form on Yelp reviews as a proxy for urban vitality in 23 block groups within the three main cities of the Texas Triangle. The six metrics are also categorized into three types of elements, including density, urban layout, and street layout design. The analysis of the study combines a literature review and a multi-level and multivariate regression model. The aim of the report is to explore the influence of each urban form indicator on urban vitality and propose policies and guideline for future development. The result indicates that out of the three elements of urban form, density has the most significant association with urban vitality. Activity density, connected node ratio and average block length are strongly correlated with vitality. The report can be served as a start point for a more comprehensive future research.

Wayfinding is a cognitive activity that is embedded in a complex social and spatial environment. People use their cognitive ability to gather spatial information from their surrounding environment while navigating and finding their way through space. Lynch (1960) argued that there is a relationship between physical perceivable urban elements and urban legibility, and that a strong legible city would help form a strong mental image of the city. In turn, a very imageable city would facilitate urban orientation and wayfinding performance. However, in addition to spatial information other external information like navigational aids and social environment could assist navigators to reach their desired destinations easier. With the ubiquity of “wayshowing” tools such as paper maps, digital maps, smart phone navigators, and local signage, pedestrians are able to locate themselves in an unfamiliar environment and find their desired destinations. Each of these tools provides specific spatial information in particular ways, with a range of limitations in their use. The way visitors to a new city wayfind in the digital era and their social and spatial interaction with their surrounding environment has been given less research attention than might be expected. In addition, physical urban elements are not the only characteristics that shape urban form. Spatial configuration of urban layout and land use are other influential factors that influence people’s route choice behaviour. This study aims to explore: a) the effects of different wayfinding tools, such as paper maps, GPS and non-mapping on an individual’s spatial cognition; b) the effects of urban form and navigational aids on people’s wayfinding performance; c) the effects of urban form and navigational tools on navigators’ social and spatial interaction with space; and, d) how people make sense of an unfamiliar urban environment and find their ways within it while using different types of navigational aids. 38 participants who had never visited Brisbane, Australia, were recruited and placed in one of the three groups, given different wayfinding tools, and asked to find seven pre-determined tourist destinations. A wide set of qualitative and quantitative methods were used including GPS tracking, think-aloud recordings, sketch mapping, other cognitive tests and post-test interviews, combined with built environment analysis using space syntax. The results showed clear differences in the cognitive tests across the three groups of participants who navigated using different wayfinding tools (GPS, maps, paper maps, signage only). The GPS group neither were the best nor the worst compared with the two other groups. However, this is not seemingly because they were looking more at their devices and not looking around, as think-aloud utterances showed no significant difference in mentions of landmarks between the groups. But passively following the suggested route shown by GPS reduced their reliance on the environmental information to wayfindMultivariate regression models revealed showed that digital navigation is fundamentally altering first-time visitors’ use of the city and affecting our natural movement and urban experience. In addition, the analysis of social interaction of navigators with space revealed that GPS navigators are becoming “anti-social”. The analysis of the think-aloud utterances by three groups of participants showed clear differences in wayfinding performance, in terms of strategies and using spatial information, across three groups of participants who navigated using different wayfinding tools. There is a modest methodological contribution of the study is in using the think-aloud methodology along with GPS tracking and cognitive mapping, space syntax techniques, and post-test interview in combination, to observe and analyze human wayfinding behavior. The outcomes of the thesis could be used to improve the effectiveness of the navigational aids and legibility of urban environments. Designers should consider routes that will likely be suggested by GPS navigation in how they design, manage and operate street and pathway networks. Designers will need to experiment on the best methods to discourage digital navigators from taking less desirable routes, for instance encouraging them onto street segments with greater commercial and recreational activity.

Telework is a flexible way of working in time and space, using communication technologies for teamwork relationships. It has become prevalent during recent decades in many countries including Australia. Socio-behavioural studies of positive and negative effects of telework have focused mainly on non-place-related factors. The role of place-related factors such as physical, spatial, infrastructure and environmental characteristics has been overlooked in many studies. The central research proposition explored in this thesis is the significance of these latter factors in explaining teleworkers’ level of work motivation. The research addresses this gap by analysing the effectiveness of the home as the most common place of telework in Australia and explores the factors determining teleworkers’ work motivation. A conceptual framework is developed to illustrate how place-related in addition to non-place-related factors affect the work motivation of teleworkers, guided by Self-Determination Theory exploring the psychology of motivation. A quantitative methodology is used to collect quantitative data defined identified in the conceptual framework from a survey of 277 employee and self-employed home-based teleworkers across Australia. Descriptive and inferential analyses provide an understanding of the character and status of Australian telework. Predictive analyses identify factors significantly affecting Australian teleworkers’ work motivation such as age, income, life stage, dwelling type, length of residence, workload, telework arrangements, workspace size, equipment, distraction, isolation, public transport access, private vehicle use and local area characteristics. The results also confirm the central research proposition that place-related factors have critical roles in explaining teleworkers’ level of work motivation. The results support a review of the position of telework at local and metropolitan levels of Australian planning policy to increase teleworkers’ level of work motivation. Policy suggestions for government support include encouraging formal telework agreements, modifying homes for telework for vulnerable social groups, developing telework on the outskirts of Australian cities and in small regional cities, encouraging compact urban form, and developing collective work hubs at the local level.

This dissertation examines the impact of parking policies and social influence on commute mode choice using discrete choice analysis. A key feature of the dissertation is overcoming the problem of insufficient data by using unique datasets, building unique datasets, or exploring appropriate estimation strategies and assumptions. Chapter 1 studies the impact of parking prices on the decision to drive to work using the California Household Travel Survey. The chapter tackles estimation challenges posed by insufficient parking information. The first challenge is the estimation of parking prices for those who do not drive, which is addressed by using a sample selection model. The second challenge is to understand the effect of the extent of the prevalence of Employer-Paid parking coupled with incentive programs offered in-lieu of parking. To address this challenge, two extreme scenarios are examined, and a range for the marginal effects of parking prices is estimated; one scenario assumes everyone receives Employer-Paid parking coupled with in-lieu of parking incentives, and the second assumes that no one is offered such incentives. The results suggest that higher parking prices reduce driving, regardless of the followed approach. It is estimated that a 10% increase in parking prices leads to a 1 - 2 percentage point decline in the probability of driving to work. Moreover, there seems to be no evidence of sample selection bias. The evidence suggests that parking pricing can indeed be an effective transportation demand management tool. Chapter 2 extends the analysis of Chapter 1 to simultaneously estimate the impact of parking pricing, parking availability, and urban form on commute mode choice. The joint role of these three factors is examined using a dataset that is constructed by merging three major different data sources. The California Household Travel Survey data are matched to two unique datasets on parking for Los Angeles County; one for prices and the other availability. Chapter 2 first examines how these three factors affect the binary decision of whether to drive, while controlling for a rich set of covariates. The analysis then becomes more specific and examines how these factors affect particular commute modes in a multinomial context. The results indicate that parking prices have a significant negative impact on the decision to drive to work, where a 10% increase in parking prices is associated with a 1.1% drop in the probability of driving to work. Both on-street and off-street parking availability at home, as well as urban form measures of the workplace tract, are found to significantly affect commute mode choices. These findings have important policy implications in terms of minimum parking requirements, maximum parking standards, employer-paid parking, and parking pricing policies. Chapter 3, on the other hand, examines the impact of a number of fundamental determinants of commute mode choice on transit use, and introduces the role of social influence. The determinants explored cover socioeconomic characteristics, built environment and neighborhood characteristics, transit accessibility, and trip characteristics. Social interactions have been found to affect many of the decisions of economic agents, and are likely to play a role in the decision to use transit. A unique dataset is built to conduct this analysis across a number of major US cities and examine the effects in both the residence and workplace neighborhoods, where a neighborhood is defined as a census tract. Social influence is explored along three different dimensions: space (neighborhood), income, and race. A novel instrumental variable is constructed in order to identify spatial social influence, and an alternative identification strategy is devised to identify income-group and racial social influence. The evidence suggests that spatial social influence exists among both coworkers and residential neighbors, and that peer effects among coworkers are larger than those among residential neighbors. Moreover, income-group social influence, among both coworkers and residential neighbors, plays a significant role in the rich commuter's decision to use transit. However, racial social influence does not affect a commuter's decision to use transit, regardless of race.

Given our rapidly changing society, the complexity of residential energy often hinders the efficacy of energy conservation policies designed to address our current social and environmental problems. Therefore, understanding this complexity appears to be essential to successfully building and efficiently implementing energy policies. The present dissertation attempts to advance our understanding of the dynamics and complexity of residential energy consumption by investigating various determinants and contextual factors through the three interrelated pieces of applied research. Using American Housing Survey (AHS) data, the first study investigates the dynamics of residential energy consumption at the micro level. It is found that the electricity consumption of households who have moved into new homes is generally lower than average, and their consumption is found to increase as the period of residence increases. The second study examines the relationship between the choice of energy-efficient systems and inter-agent dynamics. By employing a logistic regression model with two national datasets, the Residential Energy Consumption Survey (RECS) and the American Community Survey Public Use Microdata Sample (ACS PUMS), the empirical analysis reveals statistically significant differences in the installation of solar energy systems among households with different degrees of two major inter-agent issues—split incentives and split decision-making problems. The last study focuses on the complexity of residential energy consumption relevant to the surrounding environments, and it pays special attention to seasonality. Based on city-wide data from Chicago and using a special econometric model, the empirical analysis reveals the seasonal dynamics between urban forms and residential energy consumption. Through these three empirical studies, this dissertation explores the dynamics of residential energy consumption in various dimensions and reveals the complicated mechanisms that determine residents’ choices with respect to energy consumption. The evidence from this study is especially important because it reinforces the conclusion that there is no panacea when addressing energy issues. This study suggests that policy-makers and planners should instead thoroughly understand a wide range of contextual factors and their influences in order to develop more effective, context-specific energy policies that best fit each distinct geographical and socio-economic situation.

This paper uses annual, tract-level data to estimate the economic impact of the Seattle area’s newly operational light rail system and recently implemented toll on a bridge traversing Lake Washington, the large lake immediately east of Seattle that bisects the region. Two modeling approaches are utilized in the estimation of each transit intervention’s economic impact: the primary model allows the transit intervention to affect the designated impact area prior to the system’s operation, under the assumption that individuals will respond to the knowledge of the change and relocate accordingly. The secondary model accounts for an impact from the intervention upon its operation. Zoning designations are incorporated into the measurement of a tract’s proximity to the transit interventions to control for the possibility of the expansion of a residential or commercial presence. The economic impact from the light rail and toll are modeled both individually and in a combined model. The impact of the light rail is measured within a ¼ mile of stations. Two station types are controlled for within the estimation of the light rail system’s economic impact: retrofit stations previously existed as bus stations that were fit with light rail infrastructure, while new stations were built specifically for the light rail. Both station types are associated with increases in population density and housing density, and decreases in employment density, while the prevalence of public sector employment has decreased around new stations. The two station types differently attract residents based on age. A majority of the increases in population and housing density surrounding stations occurred prior to the system’s operation, whereas a majority of the decrease in employment density surrounding stations occurred during the system’s first year of operation. Narrow and broad definitions of bridge proximity are utilized in estimating the toll’s impact. The toll is associated with small increases in population density and employment density using both definitions of bridge proximity. Within the narrow definition of bridge proximity, a majority of the increase in population density occurred prior to the toll’s operation, whereas a majority of the increase in employment density occurred during the toll’s first year of operation. Within the broad definition of bridge proximity, a majority of the increases in population and employment density occurred once the toll was operational. Neither transit intervention has affected the prevalence of African Americans within the designated transit impact areas.

Recent years have witnessed an explosion in the science of networks. Much of this research has been stimulated by advances in statistical physics and the study of complex systems – that is, systems that comprise many interrelated components whose interactions produce unpredictable large-scale emergent behavior. Cities are complex systems formed both through decentralized, bottom-up, self-organizing processes as well as through top-down planning interventions. Humans shape their urban ecosystems (the built environment, institutions, cultures, etc.) and are in turn shaped by them. Cities comprise numerous interdependent components that interact through networks – social, virtual, and physical – such as street networks.This dissertation examines urban street networks, their structural complexity (emphasizing density, connectedness, and resilience), and how planning eras and design paradigms shape them. Interventions into a complex system often have unpredictable outcomes, even if the intervention is minor, as effects compound or dampen nonlinearly over time. Such systems’ capacity for novelty, through emergent features that arise from their components’ interactions, also makes them unpredictable. These interactions and the structure of connections within a system are the subject of network science. In cities, the structural characteristics of circulation networks influence how a city’s physical links organize its human dynamics. Urban morphologists have long studied the built form’s complexity and, following from scholars such as Jane Jacobs and Christopher Alexander, various urban design paradigms today speak both directly and indirectly to the value of complexity in the built environment. However, these claims are often made loosely, without formally connecting with theory, implications, or evaluation frameworks.This dissertation develops an interdisciplinary typology of measures for assessing the complexity of urban form and design, particularly emphasizing street network analytic measures. Street network analysis has held a prominent place in network science ever since Leonhard Euler presented his famous Seven Bridges of Königsberg problem in 1736. The past 15 years have been no exception as the growth of interdisciplinary network science has included numerous applications to cities and their street networks. These studies have yielded new understandings of urban form and design, transportation flows and access, and the topology and resilience of urban street networks. However, current limitations of data availability, consistency, and technology have resulted in four substantial shortcomings: small sample sizes, excessive network simplification, difficult reproducibility, and the lack of consistent, easy-to-use research tools. While these shortcomings are by no means fatal, their presence can limit the scalability, generalizability, and interpretability of empirical street network research.To address these challenges, this dissertation presents OSMnx, a new tool to download and analyze street networks and other geospatial data from OpenStreetMap for any study site in the world. OSMnx contributes five capabilities for researchers and practitioners: first, the downloading of political boundaries, building footprints, and elevation data; second, the scalable retrieval and construction of street networks from OpenStreetMap; third, the algorithmic correction of network topology; fourth, the ability to save street networks as shapefiles, GraphML, or SVG files; and fifth, the ability to analyze street networks, including projecting and visualizing networks, routing, and calculating metric and topological measures. These measures include those common in urban design and transportation studies, as well as measures of the structure and topology of the network. This study illustrates the use of OSMnx and OpenStreetMap to consistently conduct street network analysis with extremely large sample sizes, with clearly defined network definitions and extents for reproducibility, and using non-planar, directed graphs.This study collects and analyzes 27,000 U.S. street networks from OpenStreetMap at metropolitan, municipal, and neighborhood scales – namely, every U.S. city and town, census urbanized area, and Zillow-defined neighborhood. It presents wide-ranging empirical findings on U.S. urban form and street network characteristics, emphasizing measures relevant to graph theory, urban design, and morphology such as structural complexity, connectedness, density, centrality, and resilience. We find that the typical American urban area has approximately 26 intersections/km2, 2.8 streets connected to the average node, 160m average street segment lengths, and a network that is 7.4% more circuitous than straight-line streets would be. The typical city has approximately 25 intersections/km2, 2.9 streets connected to the average node, 145m average street segment lengths, and a network that is 5.5% more circuitous than straight-line streets would be. The typical Zillow neighborhood has approximately 46 intersections/km2, 2.9 streets connected to the average node, 135m average street segment lengths, and a network that is 4.4% more circuitous than straight-line streets would be. At all three scales, 3-way intersections are by far the most prevalent intersection type across the U.S.We find a strong linear relationship, invariant across scales, between total street length and the number of nodes in a network. This contradicts some previous findings in the literature that relied on smaller sample sizes and different geographic contexts. We also find that most networks demonstrate a lognormal distribution of street segment lengths. However, an obvious exception to lognormal distribution lies in those networks that exhibit substantial uniformity network-wide. At the neighborhood scale, examples include downtown neighborhoods with consistent orthogonal grids, such as that of Portland, Oregon. At the municipal scale, examples include towns in the Great Plains that have orthogonal grids with consistent block sizes, platted at one time, and never subjected to sprawl. These spatial signatures of the Homestead Act, successive land use regulations, urban design paradigms, and planning instruments remain etched into these cities’ urban forms and street networks today. Nebraska’s cities have the lowest circuity, the highest average number of streets per node, the second shortest average street segment length, and the second highest intersection density. These findings illustrate how street networks across the Great Plains developed all at once and grew little afterwards – unlike, for instance, cities in California that were settled in the same era but were later subjected to substantial sprawl.The characteristics of a city street network fundamentally depend on what “city” means: municipal boundaries, urbanized areas, or certain core neighborhoods? The first is a political/legal definition, but it captures the scope of city planning jurisdiction and decision-making for top-down interventions into a street network. The second captures the wider self-organized human system and its emergent built form, but tends to aggregate multiple heterogeneous built forms together into a single unit of analysis. The third captures the nature of the local built environment and lived experience, but at the expense of a broader view of the urban system and metropolitan-scale trip-taking. In short, multiple scales in concert provide planners a clearer view of the urban form and the topological and metric complexity of the street network than any single scale can.The emerging methods of computational data science, visualization, network science, and big data analysis have broadened the scope of urban design’s traditional toolbox. Such methods may yield new insights and rigor in urban form/design research, but they may also promulgate the weaknesses of reductionism and scientism by ignoring the theory, complexity, and qualitative nuance of human experience crucial to urbanism. The tools we use shape the kinds of questions we can even ask about cities. Today, the dissemination of quantitative network science into the social sciences offers an exciting opportunity to study the dynamics and structure of cities and urban form, but paths forward must consider cities as uniquely human complex systems, inextricably bound up with politics, privilege, power relations, and planning decisions.This dissertation comprises six substantive chapters bookended by introductory and concluding chapters. As a whole, the dissertation is divided into two primary parts. The first comprises chapters 2 and 3 and develops the theoretical framework. Chapter 2 introduces the background of the nonlinear paradigm by discussing systems, dynamics, self-similarity, and the nature of prediction in the presence of nonlinearity. These foundations set up the complexity theories of cities and the study of networks presented in chapter 3. This first part of the dissertation emphasizes the dynamics of complex urban systems before we turn our attention to their structure in the second part. Urban circulation networks serve as a physical substrate that underlies and organizes the city’s complex human interactions. Chapter 4 collates various indicators of complexity from multiple research literatures into a typology of measures of the complexity of urban form, emphasizing the scale of urban design practice. In particular, it presents several measures of network complexity and structure that we then operationalize in chapters 5, 6, and 7. Methodologically, chapter 5 introduces OSMnx, a new tool to acquire, construct, correct, visualize, and analyze complex urban street networks. Chapter 6 applies OSMnx empirically in a small case study of street networks in Portland, Oregon. Chapter 7 then expands the empirical application of OSMnx to a large study of 27,000 urban street networks at various scales across the U.S. These street networks and measures data sets have been shared in a public repository for other researchers to re-purpose.

During the last decade, Brazil has witnessed the construction of an unprecedented number of social housing developments, due to an ambitious federal program named “My House My Life” (Minha Casa Minha Vida - MCMV). In seven years, it has contracted 4.2 million of housing units, and 2.6 million of them were already delivered to beneficiaries. The program is currently in its third phase, and it covers three different ranges of income with two main goals: to boost the construction sector and reduce the housing deficit of the country by encouraging homeownership. However, the resultant large scale developments are providing residents with housing units of reduced square footage, located in peripheral locations, with few or no access to basic services and commercial activity. In such conditions, these developments become “dormitory neighborhoods”, since they lack enough infrastructure to meet the population’s daily needs, such as education, health care, commercial activity, job opportunities, social interactions, etc. Standardization of architectural and urban solutions are a way of reducing costs and usually results in the decrease of the development’s overall quality. This thesis first discusses the Brazilian current housing provision situation and the interconnected relation between social and spatial structures of cities. Searching for a more sustainable urban form, it builds a conceptual framework that expands the eight components for sustainable communities presented by the Egan Wheel by incorporating design strategies to reach them. It was performed an assessment, based on the conceptual framework, of one of the largest MCMV’s development, located in the city of Londrina, second biggest city of the State of Paraná, South of Brazil. This study focuses on the urban form of the development, pointing out that any people’s habitat should be consisted of more than a shelter, it should be complemented by a healthy neighborhood that promotes human interaction, and encourages prosperity. Then, it was proposed an alternative master plan to the case study, which has maintained ninety percent of the total current residents and offered quality public and green spaces with a more rational urban form, which also takes into consideration the social processes that define a community.

This report seeks to improve Seoul's existing urban planning system through the elements and practices of current Form-Based Code (FBC) in United States. Because Seoul's planning system has similar problems with the conventional zoning practice that the FBC purposes to overcome, the FBC practices in US provides meaningful examples that could help make Seoul's planning system more organized and sustainable. First, this report presents definitions, purpose, background, basic principles and elements of the FBC, and then explores expected benefits and criticism that has emerged from various reports and publications. Second, the Miami, Florida and Denver, Colorado FBC cases are analyzed and assessed to examine its real impact and implications for a citywide FBC adoption. The conclusion of this study provides what should be considered important to an FBC and how to apply an FBC to Seoul, and conclusion of this study.

This thesis presents the development and application of a suite of models to examine transit-orientation – measured primarily as mode share – of metropolitan areas. Transit-orientation in urban planning relates to empirical or qualitative relationships between urban structure and use of public transport (‘transit’) and to development that encourages transit use. Studies are usually at a local level, or have utilised overly simple parameters such as population density. Mode share modelling in transport planning is commonly based on behaviourally-based logistic models. The research described here has used geospatial and regression techniques to estimate transit-orientation based on demographics, urban structure, transit infrastructure and transit service at a detailed (travel zone) metropolitan-wide level. The core of this comprises a two stage logistic model suite to predict car ownership and rail, transit and active mode share and travel. The research has also included improvements to an associated road traffic assignment model used to measure the car travel impacts. The models were developed using data from Sydney, Australia, but the approach has international application. The thesis includes a Sydney case study, applied in the context of a paradigm of deferred transit investment common in cities with post World War automobile dominance. The models are applied to backcast and forecast scenarios to measure demand and operational effects, and to calculate economic sustainability impacts. The case study recognises the path dependence and resultant long term lock-in of the Sydney case, and offers comment on the current Sydney transport plan.

Urban heat islands aggravated by accelerating climate change present significant threats to human health and economic productivity, increasing energy consumption to maintain human comfort and thus the ecological footprint of cities and their inhabitants. Most Australian capital cities have developed strategies to absorb significant population growth within existing boundaries by promoting a more compact settlement form to limit further urban sprawl, increase the efficiency of infrastructure and reduce transport related greenhouse gas emissions. In the absence of climate sensitive considerations, however, contemporary planning policy disregards the fact that higher urban densities potentially intensify urban heat islands, as evident not only in compact city centres, but also in recent suburban developments. This PhD research demonstrates how the design of neighbourhoods can influence the urban microclimate at local scale, and thus the carbon footprint and liveability of our cities. The study compared the morphology of precincts and streets in relation to air and surface temperatures, with the focus on the modifying effect of individual urban form parameters such as vegetation, street geometry, volumetric building density, and urban surface characteristics. Airborne remote high-resolution thermal and hyper-spectral imaging and Lidar were employed to examine the spatial structure of neighbourhoods and their diurnal thermal patterns across the Sydney metropolitan area. Two flights were carried out at midnight and noon on calm and clear days in August 2012 in conjunction with simultaneous in-situ measurements obtained in automobile transects. Key outcomes include the development of a methodology for automated morphological classification into Local Climate Zones and city-wide thermal mapping based on a combination of remotely sensed data sets. The comparative analysis of local surface heat island magnitudes allows the assessment of a neighbourhood’s vulnerability to urban warming within the context of different urban densities. A statistical analysis quantified individual contributions of derived urban form parameters to air and surface temperature modification at precinct and street scale, including urban canyon geometry, vegetation abundance, surface cover and albedo. The resulting predictive statistical models enable the assessment of the heat island potential of proposed urban developments and scenario modelling of urban warming mitigation strategies in existing neighbourhoods.

Relationship between land use/ land cover (LULC) and land surface temperature in urban areas has been widely studied. But it is less well explored how urban form, in terms of spatial configuration of land cover patches within a city contributes towards land surface temperature. This study explored it through a case study on Hamilton County, Ohio. LULC classes and land surface temperature were derived from Landsat images for three time periods (1990, 2000, and 2010). Spatial metrics were applied on LULC maps to measure different dimensions of urban form. Areas with similar urban form were identified through cluster analysis and were assigned to different rural-urban transect zones. It was found that, transect zones followed the pattern of land use changes within the study area. With gradual decrease of natural area (or increase of built-up areas), rural transect zones decreased and urban transect areas increased over time. This change in land use composition influenced the temperature variability within the transect zones. Linear regression analysis was performed to evaluate which specific dimensions of urban form and land use distribution significantly influenced land surface temperature within the transect zones. It was found that higher percentage of built-up areas significantly increased surface temperature while higher fragmentation of these areas can help to reduce temperature. On the other hand, it did not find any significant influence of open space/grassland for reducing temperature. Forest areas were found to be effective for reducing the intensity of urban heat island. This finding indicates that, landscape fragmentation through forests (i.e. large trees) within urban built-up areas will have significant influence for reducing land surface temperature. It calls for ensuring more greenery within the developed areas through form-based codes.

Life cycle assessment (LCA) has been used for decades to study the environmental impacts of the built environment. This study extends work in this area by completing an LCA of the cumulative energy demand (CED) and global warming potential (GWP) of low, mid and high-rise multi-family dwellings. Using a hybrid LCA, this study finds that the CED and GWP for low, mid and high-rise multi-family residences increases from 37, 39, to 42 GJ/m2, and 3.6, 3.8, and 4 tCO2eq/m2 on average, respectively. As with previous studies, the operation phase dominates total life cycle energy, but with smaller share of 77% to 87%. A follow-up study examines how uncertainty in the energy intensity of materials might affect a building LCA. The exploration led to development of a knowledge-based bounding approach to mitigate uncertainty. Knowledge-based bounding maps knowledge of a product, such as country of origin or recycled content, to numerical uncertainty bounds. Gathering additional information about the product in question can shrink these bounds and, through an iterative process, reduce uncertainty until the goals of an LCA are met. Developing knowledge-based bounds for steel, this study finds that if steel type, recycled content and country of origin are all unknown, the life cycle carbon dioxide equivalent emissions of steel can vary from .7 to 5.9 kg tCO2eq per kg of steel. In contrast, with knowledge that the steel is un-alloyed, and, has a 64-100% recycled content, uncertainty bounds are reduced to .8-1.4 kg tCO2eq/kg steel. These two bounds are applied in life cycle assessment of concrete and steel framed buildings. The 0.7 to 5.9 kg tCO2eq emissions per kg of steel bound leads to ranges for the life cycle emissions too wide to distinguish the preferability of steel and concrete framed buildings. However, the lower bounds, 0.8-1.4 tCO2eq/kg of steel, shows unambiguously that steel-framed buildings have lower CO2 emissions.

Physical activity, including walking, can be a very healthy and sustainable mode of transportation. Children walking to their schools can get a lot of benefits from acquiring good habits that can be carried through their adulthood. Also, walking to school can reverse the trend of increasing obesity rates among children in the United States. This study is trying to identify the effect of urban form, presented in the distances between residences and schools, on the children’s behavior whether they walk to school or not depending on different urban forms around their schools. Two middle schools in Lincoln, Nebraska were selected as case studies using network analysis in Geographic Information System (GIS). These schools featured diverse socioeconomic status and urban form characteristics for their surrounded neighborhoods. A survey was conducted on a sample of one hundred and sixteen students from both schools. From our results, we found that 21.8% of the sample in Lefler School use active modes of transportation to their school located near the city center, where the school is built in a traditional neighborhood featuring grid street system and high connectivity. Only 6.7% of the sample in Scott School bike to school, and nobody walks to it, since Scott School is located in a late-modern neighborhood on the city’s fringes built in the 1990s, and features dead-end streets and low connectivity. We concluded that distances seem to increase in the latter neighborhood resulting in diminishing the number of students willing to walk or bike to their school. Other factors like parents’ and children’s perceptions about safety, traffic, convenience, and strangers might have an influence on determining the child’s behavior whether to walk to school or not. Advisor: Yunwoo Nam

This study arose from an idea that air pollutants and greenhouse gases from vehicles could be reduced by changes in urban form. Analyzing the results of related prior investigations showed that the researchers mainly argued that adjustment of typical urban form characteristics (e.g., degree of population density or sprawl) can reduce the amount of vehicle emissions. The policies considering typical urban form change cannot be easily realized, however, because changing population density and stopping urban sprawl are both very difficult and require a long time. In view of that limitation, this study tried to uncover more effective urban form factors to reduce vehicle emissions within the mid- or short-term. This research also attempted to examine vehicle emission reduction by changing both absolute and relative locations of urban functions (i.e. population, employment, and commercial facilities). To observe the relationship, some spatial-related variables from the location of urban functions are developed.To determine the relative location among urban functions, certain measurements are built. Based on the location concepts, key variables are constructed. Average daily vehicle miles traveled (ADVMT) is estimated to measure the amount of vehicle emissions, and then statistically tested its relationship with eight urban form factors. Based on the analysis results, when we have urban areas with similar population densities, an area with clustered populations and closely concentrated clusters produces fewer ADVMT and emissions. In addition, a short average distance between residences and the commercial areas they use frequently generates fewer emissions, too. The results also show that high population density, employment centrality, and longer commuting time also reduce vehicle emissions.This study additionally simulates the change in vehicle emissions based on residential development scenarios. The results show that residential development in suburbs considerably increases both VMT and vehicle emissions, compared with development in a downtown area.Based on the estimated VMT and quantity of vehicle emissions in the urban areas, there are definite differences according to the conditions of urban form factors. In addition, according to the simulations, considerable benefits exist with decreasing the quantity and costs of vehicle emissions through the changes of urban form factors.This study verifies the relationship between VMT, the quantity of vehicle emissions and urban form factors with a distinctive approach that also includes conventional factors. This study emphasizes the importance of the distribution of populations and other urban functions.

This dissertation empirically evaluates the association between urban form and the energy performance of neighborhoods focusing on their energy demand and on-site green energy supply. Urban form, the spatial pattern and density of urban physical objects, such as: buildings, streets, vegetation and open space, have a considerable long-term influence on macro-scale environments. Besides their well-known impacts on vehicle trips, the effects of urban form on space-conditioning energy use and on-site energy generation has recently received attention most likely as a result of the energy crisis of the late 2000s.However, these complex effects of urban form on their net energy savings, generation and potential trade-offs have not been rigorously and comprehensively evaluated due to computational limitations and the lack of data rich environments. In addition, we do not understand what kind of urban form is best for utilizing the benefits from new technologies (for example, efficient vehicles and solar photovoltaics) as they are rapidly being adopted in urban landscapes. Given the inertia of the built environment, it is imperative to alter urban form based on a thorough understanding and comprehensive assessment of urban systems. As our scholarship and practice of green initiatives has been somewhat piecemeal and short-sighted, it is critical that we construct comprehensive models to study the relationships between urban form and energy efficiency.Given this challenge, this dissertation assesses the impact of urban form on energy use and on-site green energy generation by developing and applying an empirically based data rich model. This research also provides an approach for evaluating potential trade-offs between energy demand and supply given specific urban form. Given these goals, this dissertation focuses on answering three questions that each represent energy demand, supply and trade-offs that are affected by urban form:(1) does urban form have impact on residential space-conditioning energy use?; (2) does urban form have influence on on-site solar energy potential?; and (3) how does the trade-off between vehicle energy use and on-site solar energy potential vary over urban density?To best account for a complex real-world environment in the model, this dissertation employs advanced three-dimensional urban models derived from Geographic Information Systems (GIS)and Light Detection and Ranging (LiDAR) data. This method successfully captures the physical conditions of real landscapes, including vegetation, which has been impossible to obtain until recent years. After extracting urban form and demographic variables through spatial analyses, it applies multivariate analysis to assess the impact of urban form on energy use and on-site energy generation controlling for other factors. The Cities of Sacramento and San Francisco, California are used in this research, however it is argued the approach is universal in nature.This dissertation reveals that urban form matters in reducing cooling energy demand and increasing on-site solar energy supply in cities. The results show higher population density, east-west street orientation, higher green space density within a 100ft radius and a higher sum of tree heights on the east, south and west sides of houses have statistically significant effects on reducing summer cooling energy use after controlling for other variables. With regard to impacts of trees on on-site solar energy generation, this research also discovers higher tree density, higher average tree heights and a higher variance of tree heights have significant impacts on reduction in the average rooftop insolation. Examining the trade-off between on-site solar energy potential and vehicle energy use, the results show that the density threshold that allows personal vehicle energy use becomes smaller than rooftop solar potential, changes as vehicle and solar technologies improve and different combinations of them become available.This dissertation is the first comprehensive validation of many of the early theoretical works on climate responsive urban design and on-site solar energy guidelines in the 1960s through the early 1980s. It supports the argument that more energy related incentives and regulations are imperative not only on a single building scale but also for its neighboring environment on a community wide scale. Finally, this research provides a new approach to how city planners can respond to technological advances and policy shifts in energy related areas.

In India, demand for urban mobility is increasing rapidly because of growth in urban populations, establishment of multiple employment sub-centers, suburbanization of households, better education, higher workforce participation rates, and rising incomes. An increase in discretionary spending is leading to higher household transportation budgets. Middle-income households in particular are investing in private vehicles such as motorized two-wheelers (TWs) and cars. At the same time, policies to reduce vehicle ownership through regulations and user costs remain underdeveloped and weakly enforced. This further increases households' willingness to use vehicles, especially for non-discretionary work trips. Higher private vehicle use is affecting other quality of life issues such as time spent commuting, accident rates, noise pollution, and particulate and greenhouse gas emissions. In part, this higher vehicle ownership and use is driven by land use dynamics in Indian cities, where growth within city municipal boundaries is constrained by regulations limiting floor-area ratios. As a result, much of the new growth has taken place in urban peripheries where land is cheap and building costs are low. In these peripheral areas, existing small and medium towns have become anchors for agglomeration, transforming into bedroom communities for emergent middle-class groups. Urban peripheral areas are usually undersupplied with transportation infrastructure such as roads or bus transit. This dissertation unpacks the question of why the middle-class in India is driven to owning and using TWs and cars by asking the following: (1) How does work location influence travel by public and private modes? (2) What factors encourage vehicle ownership in middle-class households? (3) What factors drive up vehicle use in middle-class households? The research was conducted using a travel survey dataset from the Greater Mumbai Region (GMR) that represents 1.5% of the households there. The GMR is among the most populated megacity regions in the world, housing over 22 million people. Its growth illustrates the transformation from a monocentric to a polycentric city which is seen in many rapidly growing Indian cities. In seeking to develop an understanding of how work location affected travel, this research identified employment sub-centers using work destination data. Of all middle-class home-based work trips, 67 percent ended in a sub-center, while 33 percent did not. Mean travel times and mean travel distances by train, TW and intermediate public transportation (IPT) modes such as rickshaws were longer for work destinations in sub-centers than for work destinations in the urban periphery, but trips made by buses were shorter in sub-centers. Car users traveled longer and farther compared to TW users for home-based work trips in the GMR. Trains were the speediest mode of travel in the GMR, but traveling by a TW or car was speedier than bus or IPT travel--confirming that having a private vehicle has advantages. This research used a multinomial logit model to analyze households' choice of having no vehicles, only TWs, or at least one car. Results indicated that household utility from both TWs and cars increased with household characteristics such as per capita annual income, living in an independent house or an apartment, number of rooms in the housing unit, housing location farther from a railway station, the presence of children under 5 years, and larger household size. Moreover, vehicle utility for households increased with the primary wage earner's characteristics including college education, employment, being married, making more trips across all modes, traveling during the morning peak, and working in the urban periphery. Household utility from both TWs and cars decreased when the primary wage earner had longer work trips and higher employment density at the work location. Regression models for vehicle kilometers traveled (VKT) and person kilometers traveled (PKT) for cars and TWs showed that vehicle use increased with number of employed persons in the household, and if the primary wage earner worked in the urban core. Vehicle use decreased if density of housing and jobs went up at either the home or work location. TW use went down with per capita annual household income. Overall findings indicate that demand for private vehicles is rising due to the following factors: better education, employment, higher incomes, suburbanization, peripheral employment node formation, and lack of public travel options. However, higher density decreases vehicle use. Without changes in policies encouraging higher well-managed densities, jobs-housing balance, and supply of adequate transit and IPT travel options, vehicle ownership and use will likely continue to grow rapidly in India.

The High-Speed Rail (HSR) was first constructed and operated in Japan in 1964. Today, several countries around Europe, Asia, and America have HSR services. As an emerged speedy ground transportation method, the HSR cooperates and competes with road, air, and water transportation and also contributes to economic development and passenger transportation. China proposed a National High-Speed Rail Network Plan in 2008 and began to build “JingHu Line,” which connects Beijing, Tianjin and Shanghai, in the same year. This thesis focuses on the HSR construction in China, especially the construction of “JingHu Line.” Beijing and Tianjin, the main cities served by this line, began to reconstruct the existing rail stations to meet the technical norms of HSRs. This thesis draws on existing literatures about urban development, urban form and high-speed rail station to evaluate the impact of the HSR station on the surrounding area. It specially focuses on the reconstruction of high speed rail station in Beijing and Tianjin to understand the connection between HSRs and other urban transport methods, the emergence of new urban spaces and the land-use change in the station area. In the thesis, I firstly review current literatures and define three important terms, “high-speed rail,” “urban form” and “rail station area,” which are the basis for this research. In the next section, I study the developing history of high-speed rail in the world, which is the background for this research and the main motivation for the construction of Chinese High-Speed Network. Moreover, I review the features of HSR transportation, because the unique features of HSRs directly influence the changing form of surrounding areas. The “Urban Catalysts Theory” and “Linkage Theory” as the theoretical underpinning for this research are introduced in the chapter three. These two theories are tools to understand interactions between the HSR station and the surrounding area. The chapter three also reviews current literatures relating the influence of HSR station on a city. In the case study, I look at constructions of the HSR station in Beijing and Tianjin to learn how the reconstruction projects were planned and built, how HSRs connect to the inner city transportation network and how the urban form change in the station area. Through this research, we can learn interactions between the construction of HSR station and the development in the station area. Also, the review of reconstruction projects of HSR station in Beijing and Tianjin provides experiences to other cities, which are going to have HSR services in following years.

Abstract: Background: Urban form is a contributor to physical inactivity, which is a problem around the world. The association between urban form and physical activity is not fully understood, in part because improved methodologies of assessing urban form are necessary. This thesis consists of four studies that examined the association between urban form and physical activity in Edmonton, Alberta, using Geographic Information Systems. The research goals of this thesis were: (1) to compare two objective methods of assessing urban form walkability; (2) to examine the association between objective and subjective urban form measures and physical activity; and (3) to compare self-reported physical activity of individuals living in high and low walkability neighborhoods. Methods: Study 1 addressed Goal 1 and focused on objectively measuring urban form walkability based on public health and architectural (space syntax) measures. Study 2 addressed Goal 2 and focused on urban form association with self-reported physical activity. Study 3 addressed Goals 2 and 3 and focused on urban form association with self-reported walking. Study 4 addressed Goal 3 and involved an observational study of the pedestrian, cyclist, and vehicular movement in four neighbourhoods stratified by walkability and socio-economic status (SES). Results: Study 1 revealed agreement between public health and space syntax measures of assessing urban form. Study 2 revealed that only the objective environment was associated with physical activity. Study 3 revealed that only the perceived environment was associated with walking. Study 3 also revealed that walking as recommended was not different for individuals living in environments objectively assessed as higher versus lower in walkability. Study 4 revealed that observed pedestrian movement was higher in volume in neighbourhoods objectively assessed as higher in walkability. Cyclist movement was lower in volume in the neighbourhood classified as lower in walkability and in SES than in the other three neighbourhoods. Vehicular movement was no different in volume in the four neighbourhoods. Conclusion: Both objective and subjective urban form influence physical activity. A common Social Ecological Models - Space Syntax framework would enable a better understanding of urban form influences on physical activity.

While we recognise that our current suburban form is unsustainable, and through regional growth management policy seek to intensify the city core and inner suburban areas, we do not have a new design programme for these liminal spaces. Intensification therefore falls to the suburban default, often resulting in compact suburbia, and undesirable urban environments. Using a ‘research through design process’ this thesis explores transit- oriented development as an alternative design programme for Addington, an inner suburban Christchurch space. Addington 2041 is a compact, mixed use, diverse urban landscape, clustered around a reactivated train network and station. Supported by educational, cultural, commercial, and residential activities, and a high quality pedestrian and public realm, Addington 2041 interprets an international urban form in the local context, and combined with a revealed sense of place and identity creates a liveable urban environment for the future.

This research seeks to evaluate the possible causal relationship between land use or urban design regulation and subsequent built form patterns observable on the ground, using a quasiexperimental method. With increasing frequency, suburban towns and cities are investing in expensive overhauls of their General Plans and zoning ordinances based on vague promises of curbing sprawl, building a sense of place, and creating a new urbanism. However, the effectiveness of these novel codes is unknown and untested.In part I, case cities are selected based upon their notable achievement of placemaking goals: former automobile-oriented suburbs are now pedestrian-friendly and transit-oriented, with distinguished centers of dense mixed use. They are evaluated for the extent to which explicit, anticipatory land use planning and regulation played a role in creating this outcome. In part II, case cities are selected due their adoption of Smart Growth or New Urbanist regulatory regimes. They are evaluated for the extent to which land use and built form changed in the desired directions over the subsequent ten to twenty years of development as guided by the new regime.Findings from part I indicate that effective land use planning is indeed an requisite ingredient to successful urbanization and placemaking. Findings from part II, however, indicate that adoption of new regulatory regimes is not a predictor of success, making novel regulation, by itself, an unreliable indication that placemaking will be achieved. Finally, the research suggests a future hypothesis that it is the coupling of revised land use regulation with a continued culture of enforcement through the funding and support of planning departments and commissions that clearly predicts success in transforming suburban sprawl into urban places.

The sprawl of U.S. cities has attracted criticism from many sources in recent years. Among the greatest of the cited harms of sprawl is the alleged travel time burden that it imposes on its residents. Previous research has tested the relationship between the sprawl of business activity and travel times by examining only its effects on commuting times and has concluded that people do not choosing housing and work locations to minimize commutes. This research takes a more comprehensive approach by analyzing the relationship between household travel times and sprawl by testing the relationship between access to economic centers and daily household travel time. The relatively minor increase in household travel times with decrease in access to economic centers found by the analysis shows that people logically reduce trips to centers when choosing housing locations with less access to centers. The ability of people to make these reductions in travel is clearly increased by the dispersal of activity from the central business district and other centers. Comparison of predicted household travel times with an estimated rent gradient show that the increase in housing prices with improved access to subcenters is far less than would be expected given the predicted household travel times, contradicting the relationship between household travel time and housing prices embodied in central place theory and its limited polycentric extensions. An analysis of joined trips suggests that households with less access to economic centers used joined trips, in which multiple destinations are visited on a single trip from the home, to reduce household travel. All of the results suggest that auto use enables households throughout the metropolitan area to reduce travel time. The car has greater flexibility and speed than other modes, particularly in areas of lower density. The travel time savings and flexibility that are provided by the dispersal of economic activity have allowed people to choosing housing that they prefer at lower prices with little added transportation cost. Given these benefits we should carefully consider the manner and method we choose to reduce any negative externalities of sprawl and auto use.

The middle landscape, more commonly referred to as Suburbia, has become spatially discontinuous, lacking the cohesive union, open spaces and city centers that once defined community. Presently, the middle landscape's community spaces do not offer the opportunity for familiar and chance encounters or ritual activity. Large-scale housing development in Northern Virginia and in the mid-Atlantic region is continually segregating and ultimately destroying community and all links to the area's history. Located in Southern Fairfax County, the newly abandoned Lorton Central and Maximum Security Prison Facility provides an opportunity to serve as a catalyst for community in this area. This thesis investigates the historic precedence for creating successful community centers. The author's personal investigation is focused upon using form and function to accomplish this vision. By adaptively reusing the existing architecture alongside new construction, the intent is to create a dense urban town center at the abandoned historic site.

Norwood is a small city slightly younger than the City of Cincinnati. It is surrounded by Cincinnati in its entirety, although it has its own waterworks, garbage pickup, school system, and other services. Norwood takes pride in its independence from the larger city. However, its origins are linked to the Cincinnati and other settlements in the area. Norwood was once a mere coach shop, later an industrial satellite to Cincinnati, has suffered from the relocation of heavy industry to third world countries, and now looks for a place in the competition to attract new investment. Through all these stages Norwood has had a symbiotic relationship with Cincinnati. This thesis addresses the changes in the urban form in Norwood, Ohio from its very beginning. First as a crossroads tavern, then the subdivision of its land, its suburbanization, the relocation of some of Cincinnati's industry, the exodus of that same industry from Norwood, and finally the strategies that have allowed Norwood to be successful at the present time. It observes these changes in their interrelation to transportation modes and the effect their apparently thoughtless layout had in the urban fabric of the community. America is suffering from the consequences of urban sprawl, and some organizations are promoting a denser land use and the return to the central cities for residence. Because of its location and connectivity, Norwood could present an attractive destination if its business district and housing are revitalized. The proposal for light rail in Cincinnati includes Norwood in its first phase; the presence of transit in the area would result in faster restoration of the commercial and office activities that were once common along Montgomery Road. Norwood can benefit from its location in Cincinnati and the presence of available space for development. This thesis intends to contribute by analyzing the changes in transportation and urban form, which gave Norwood the road network it now has; and how this interconnected grid may be useful for the increased use of public transportation and economic development in the area.

The debate on the desirability of metropolitan compactness as a policy goal has many dimensions. One of the most significant dimensions is that of the impact of urban form on travel behavior, which directly relates to tailpipe pollution and travel-energy consumption. With this in mind, this dissertation explores several dimensions of metropolitan form as contributory factors to the variability in individual vehicle miles traveled (VMT) in the US metropolitan areas. Two themes are investigated. First, variations observed in individual VMT are associated with the form of the metropolitan region in which the traveler is located. Second, the influence of monocentric, polycentric and decentralized sprawling forms on VMT are evaluated within size class of metropolitan areas. Population, density, spatial Gini coefficient and Moran's I are used to quantitatively characterize metropolitan form. The research analyzes some 9,000 persons from 214 metropolitan areas with a population of less than three million. The data sources include the 1995 Nationwide Personal Transportation Survey (NTPS) and the 1990 Census Transportation Planning Package (CTPP). To deal with the nested data at four different levels (i.e., person, household, neighborhood and metropolis) multilevel analysis is applied. The results indicate that metropolitan form contributes overall only a small amount in predicting individual VMT; however, metropolitan spatial structure is one of the most significant variables for metropolitan areas of some but not all population sizes. In addition, development characterized by a relatively undifferentiated pattern of decentralization, as opposed to a more monocentric or polycentric patterns, increase individual VMT for the metropolitan areas of certain population size. The VMT-reduction effect of metropolitan form is limited and may only materialize in the long run. However, VMT reduction is only one of many goals in landuse policies, including more housing choices and higher accessibility; hence, it may not be considered as a precondition for implementing a land use policy. The deregulation of maximum density policy regarded as a primary cause of urban sprawl, however, may provide more housing choices and high accessibility on the one hand, and bring about VMT reduction on the other.

This dissertation research addresses the relation of transportation and land use planning, but differs from most work in this area in that it focuses on the outcome of transportation safety. Two major elements distinguish the research design of this dissertation from that of most other traffic safety studies. First, the dissertation defines a neighborhood's traffic safety performance as the number of crash-involved drivers per 1,000 licensed drivers residing in each neighborhood, regardless of the actual locations of crashes. Therefore, a neighborhood's traffic safety is considered improved only when local drivers face a lower probability of traffic crash involvement. This view transforms the focus of traffic safety from places---e.g., troublesome intersections---to people. Second, the study area in the dissertation covers neighborhoods throughout the entire Detroit metropolitan region, instead of pre-selecting case study neighborhoods. In order to identify the alternative neighborhood types, neighborhoods throughout the region are characterized using an innovative technique for defining neighborhoods, relying on geographic information system-based spatial analysis and statistical clustering. Neighborhoods are grouped into six neighborhood clusters: CBD, traditional urban, inner suburban, outer suburban, rural, and employment center, based on their (dis)similarities of physical environment settings and land use patterns. The findings lead to the conclusion that although higher density neighborhood settings raise local residents' traffic crash risk overall, the risk attributable to certain hazardous actions that are more likely associated with aggressive driving behaviors (e.g., speeding, following too close, disregarding traffic control, or failing to yield the right-of-way) by residents of these areas is lower. This suggests that, on the one hand, promoting more compact development alternatives and a wide range of alternative transportation mode choices would reduce the occurrence of aggressive driving behaviors, and thus result in desirable transportation safety outcomes. On the other hand, to the extent that planning is currently interested in enabling denser land use alternatives such as new urbanism, transit villages, or smart growth generally, greater attention needs to be paid to design for traffic safety. Such attention to design would help mitigate the potentially higher overall traffic risk associated with denser neighborhoods, especially those neighborhoods which are designed solely for high residential density without being accompanied by greater accessibility and diversified land use patterns.