ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- All Subjects: urban planning
Description
With the advent of new mobility services and technologies, the complexity of understanding the mobility patterns has been gradually intensified. The availability of large datasets, in conjunction with the transportation revolution, has been increased and incurs high computing costs. These two critical challenges require us to methodologically handle complex transportation problems with numerical performance: fast, high-precision solutions, and reliable structure under different impact factors. That is, it is imperative to introduce a new type of modeling strategy, advancing the conventional transportation planning models. In order to do this, we leverage the backbone of the underlying algorithm behind machine learning (ML): computational graph (CG) and automatic differentiation (AD). CG is a directed acyclic graph (DAG) where each vertex represents a mathematical operation, and each edge represents data transfer. AD is an efficient algorithm to analytically compute gradients of necessary functionality. Embedding the two key algorithms into the planning models, specifically parametric-based econometric models and network optimization models, we theoretically and practically develop different types of modeling structures and reformulate mathematical formulations on basis of the graph-oriented representation.
Three closely related analytical and computational frameworks are presented in this dissertation, based on a common modeling methodology of CG abstraction. First, a two-stage interpretable machine learning framework developed by a linear regression model, coupled with a neural network layered by long short-term memory (LSTM) shows the capability of capturing statistical characteristics with enhanced predictability in the context of day-to-day streaming datasets. Second, AD-based computation in estimating for discrete choice models proves more efficiency of handling complex modeling structure than the standard optimization solver relying on numerical gradients, outperforming the standard methods, Biogeme and Apollo. Lastly, CG allows modelers to take advantage of a special problem structure for the feedback loops, a new class of problem reformulation developed through Lagrangian relaxation (LR), which makes CG based model well suited for reaching a high degree of the integrated demand-supply consistency.
Overall, the deep integration of the practically important planning models with the underlying computationally efficient ML algorithms can enhance behavioral understanding of interactions in real-world urban systems, and the proposed differentiable mathematical structures will enable transportation decision-makers to accurately evaluate different demand-side and supply-side scenarios with a higher degree of convergency and optimality in more complex transportation systems.
ContributorsKim, Taehooie (Author) / Pendyala, Ram RP (Thesis advisor) / Zhou, Xuesong XZ (Thesis advisor) / Pan, Rong RP (Committee member) / Lou, Yingyan YL (Committee member) / Arizona State University (Publisher)
Created2021
Description
Transit agencies are struggling to regain ridership lost during the pandemic. Research shows that riding transit was among the most feared activities during the pandemic due to people’s high perceived risk of infection. Transit agencies have responded by implementing a variety of pandemic-related safety measures in stations and vehicles, but there is little literature assessing how these safety measures affect passengers’ perception of safety. This study implements surveys, interviews, and observations in Berlin, Germany to assess how passengers’ demographic characteristics and experiences with safety measures are related to their perception of safety using transit. Females and older age groups were more likely to perceive transit as riskier than males and younger age groups. The results provide little evidence to suggest that safety measures have a significant impact on passengers’ perception of safety, however. If this result is supported by future research, it suggests that transit agency investments in pandemic safety measures may not help them to regain ridership.
ContributorsKatt, Noah (Author) / Salon, Deborah (Thesis advisor) / Meerow, Sara (Committee member) / King, David (Committee member) / Arizona State University (Publisher)
Created2022
Description
The Phoenix area is often considered the mecca of suburban residential sprawl and for as long as the city has been growing, retail development has followed. Despite occurring alongside residential sprawl, retail development does not have the same characteristics as residential suburban sprawl and has more closely followed national retail trends. Regardless, there are still some differences, therefore the research question that will be asked here is how have the characteristics of retail development in Greater Phoenix followed the national trends of retail developments that were established in each decade since the 1950s? Characteristics were gathered from a literature review and 29 sample retail developments from various types of retail formats popularized in the various decades including commercial strips, regional shopping centers, big box centers, factory outlet malls, power centers, power parks, and lifestyle centers were surveyed. Overall, it was found that many retail developments in Phoenix are larger than the national standard. Additionally, retail formats like power parks, power towns, and big box centers included more small and medium sized inline or strip storefronts than the national standard. But, in general, many characteristics other than those already mentioned did not vary much from the national norms. In the end, retail development will continue to be important as the Phoenix area continues to grow into one of the biggest metros in the country.
ContributorsGallegos, Jairus Donald (Author) / King, David (Thesis advisor) / Davis, Jonathan (Committee member) / Ó Huallacháin, Breandán (Committee member) / Arizona State University (Publisher)
Created2022
Description
Food waste is one of the most significant food system inefficiencies with environmental, financial, and social consequences. This waste, which occurs more at the consumer stage in high income countries, is often attributed to consumers’ behavior. While behavior is a contributing factor, the role of other contextual factors in influencing this behavior has not been systematically analyzed. Understanding contextual drivers of consumer food waste behavior is important, as behavior sits in a matrix of technology, infrastructures, institutions and social structure. Hence designing effective interventions will require a systems perceptive of the problem. In paper 1, I used Socio-ecological framing to understand how personal, interpersonal, socio-cultural, built, and institutional environments contribute to food waste at the consumer stage. In paper 2, I explored the perception of stakeholders in Phoenix on the effectiveness and feasibility of possible interventions that could be used to tackle consumer food waste. In paper 3, I examined the impact of knowledge and awareness of the environmental consequence of food waste in terms of embedded water and energy on the cognitive factors responsible for consumer food waste behavior. Across these three papers, I have identified three findings. First, the most influential factor responsible for consumer food waste is meal planning, as many decisions about food management depend on it. However, there are many contextual factors that discourage meal planning. Other factors identified include the wide gap between food producers and consumers, the low price of food, and marketing strategies used by retailers to encourage food purchases. Systems level interventions will be required to address these drivers that provide an enabling environment for behavioral change. Second stakeholders in the city overwhelmingly support and agree that education will be the most effective and feasible intervention to address consumer food waste, 3) there is need to carefully craft education materials to inform consumers about other resources, such as water and energy, embedded in food waste to stimulate a personal norm that motivates change in behavior. In this study, I emphasize the need to understand the root causes of consumer food waste and exploration of systems level interventions, in combination with education and information interventions that are being commonly used.
ContributorsOpejin, Adenike Kafayat (Author) / Aggarwal, Rimjhim (Thesis advisor) / White, Dave (Thesis advisor) / Garcia, Margret (Committee member) / Merrigan, Kathleen (Committee member) / Arizona State University (Publisher)
Created2022
Description
Nonlinear responses in the dynamics of climate system could be triggered by small change of forcing. Interactions between different components of Earth’s climate system are believed to cause abrupt and catastrophic transitions, of which anthropogenic forcing is a major and the most irreversible driver. Meantime, in the face of global climate change, extreme climatic events, such as extreme precipitations, heatwaves, droughts, etc., are projected to be more frequent, more intense, and longer in duration. These nonlinear responses in climate dynamics from tipping points to extreme events pose serious threats to human society on a large scale. Understanding the physical mechanisms behind them has potential to reduce related risks through different ways. The overarching objective of this dissertation is to quantify complex interactions, detect tipping points, and explore propagations of extreme events in the hydroclimate system from a new structure-based perspective, by integrating climate dynamics, causal inference, network theory, spectral analysis, and machine learning. More specifically, a network-based framework is developed to find responses of hydroclimate system to potential critical transitions in climate. Results show that system-based early warning signals towards tipping points can be located successfully, demonstrated by enhanced connections in the network topology. To further evaluate the long-term nonlinear interactions among the U.S. climate regions, causality inference is introduced and directed complex networks are constructed from climatology records over one century. Causality networks reveal that the Ohio valley region acts as a regional gateway and mediator to the moisture transport and thermal transfer in the U.S. Furthermore, it is found that cross-regional causality variability manifests intrinsic frequency ranging from interannual to interdecadal scales, and those frequencies are associated with the physics of climate oscillations. Besides the long-term climatology, this dissertation also aims to explore extreme events from the system-dynamic perspective, especially the contributions of human-induced activities to propagation of extreme heatwaves in the U.S. cities. Results suggest that there are long-range teleconnections among the U.S. cities and supernodes in heatwave spreading. Findings also confirm that anthropogenic activities contribute to extreme heatwaves by the fact that causality during heatwaves is positively associated with population in megacities.
ContributorsYang, Xueli (Author) / Yang, Zhihua (Thesis advisor) / Lai, Ying-Cheng (Committee member) / Li, Qi (Committee member) / Xu, Tianfang (Committee member) / Zeng, Ruijie (Committee member) / Arizona State University (Publisher)
Created2023
Description
The aim of this dissertation is to develop an understanding of the relationships between the daily commute, commuting stress, and Health-Related Quality of Life (HRQOL) based on a case study in Georgetown Guyana. Three separate but connected pieces of work were attempted to accomplish this aim. First, a scoping review was conducted using the Joanna Briggs Guidelines to elucidate the factors that contribute to commuting stress that have already been explored in the literature. This scoping review unearthed 11 factors across three broad categories. The commute-specific factors which contribute to commuting stress include, the length of the commute and the mode of the commute (whether active or non/active). The built environment factors include the levels of traffic congestion, the type of infrastructure that is in place, the landscape that lines the commuting route, and the experience of non-compliant fellow commuters. Personal factors include gender, age, hours of work, and quality of sleep. These factors along with a few others were then tested within a binomial regression framework that utilized data from 427 working adults. The results mirrored what was found in the literature. In addition, there was clarification of the roles of two factors for which the literature appeared to have not comprehensively addressed. These are modes of commute, that is persons who commute by private means are less likely to experience commuter stress than persons who commute via public means. In the third task, the relationship between these novel commute-specific factors and HRQOL. The result of this study demonstrated that persons who used private commuting and who were more satisfied with the commute infrastructure were more likely to have higher HRQOL scores than those who were not satisfied with the commute infrastructure in place and those who used public transportation. The results further demonstrated that commuting stress mediated the relationship between satisfaction with commute infrastructure and HRQOL, but it did not mediate the relationship between commuting mode and HRQOL. To address these issues, it is recommended that action be taken at the micro, meso, and macroeconomic levels. Keywords: urbanization, daily commute, stress, health-related quality of life, Guyana
ContributorsVan-Veen, Davon (Author) / Chhetri, Netra NC (Thesis advisor) / Jamme, Hue-Tam HJ (Committee member) / Ross, Heather HR (Committee member) / Arizona State University (Publisher)
Created2023
Description
The lack of in-depth understanding of why policies succeed or fail in implementation puts future policymaking in a situation of having insufficient information to craft effective interventions. Mainstream policy implementation theory is rooted in a democratic institutional setting. Much less empirical research and theory addresses implementation in top-down authoritarian contexts, such as China. This study addresses the research question of how the Chinese governance context affects stakeholder’s behavior in combating air pollution, based on the analysis of implementation of three particular air pollution policies: (i) Natural gas / electricity conversion from coal, for winter heating, (ii) Widespread deployment of New Energy Vehicles, and (iii) The shutting down of cement production in northern China during the winter heating period to avoid overlapping pollution emissions from winter heating.
This study identifies flexibility and accountability as two important characteristics of the Chinese governance context, and traces how they affect stakeholder behavior and coalition formation, which in turn impacts policy implementation performance. The case study methodology triangulates analysis of government policy documents, secondary data, and the results of semi-structured key informant interviews.
Findings include: (i) The Chinese government has a very strong implementation capability to pass directives down and scale up, enabling rapid accomplishment of massive goals. It also has the capability to decide how the market should come into play, and to shape public opinion and ignore opposition; (ii) Interventions from the authoritarian government, given China’s vast economy and market, and the efficient top-down tiered bureaucratic system, risk distorting the market and the real policy goals during the implementation process; (iii) There tends to be an absence of bottom-up participation and feedback mechanisms; (iv) An effective self-correction mechanism, associated with flexibility and adaptability by a myriad of stakeholders often enables effective policy adjustment.
Policy implications include: (i) Policy implementation concerns need to be integrated into policy design; (ii) More thorough discussion of options is required during policy design; (iii) Better communication channels and instruments are needed to provide feedback from the bottom-up; (iv) On complex policy issues such as air pollution, pilot projects should be carried out before massive adoption of a policy.
This study identifies flexibility and accountability as two important characteristics of the Chinese governance context, and traces how they affect stakeholder behavior and coalition formation, which in turn impacts policy implementation performance. The case study methodology triangulates analysis of government policy documents, secondary data, and the results of semi-structured key informant interviews.
Findings include: (i) The Chinese government has a very strong implementation capability to pass directives down and scale up, enabling rapid accomplishment of massive goals. It also has the capability to decide how the market should come into play, and to shape public opinion and ignore opposition; (ii) Interventions from the authoritarian government, given China’s vast economy and market, and the efficient top-down tiered bureaucratic system, risk distorting the market and the real policy goals during the implementation process; (iii) There tends to be an absence of bottom-up participation and feedback mechanisms; (iv) An effective self-correction mechanism, associated with flexibility and adaptability by a myriad of stakeholders often enables effective policy adjustment.
Policy implications include: (i) Policy implementation concerns need to be integrated into policy design; (ii) More thorough discussion of options is required during policy design; (iii) Better communication channels and instruments are needed to provide feedback from the bottom-up; (iv) On complex policy issues such as air pollution, pilot projects should be carried out before massive adoption of a policy.
ContributorsZhang, Feifei (Author) / Webster, Douglas (Thesis advisor) / Pijawka, David (Committee member) / Cai, Jianming (Committee member) / Muller, Larissa (Committee member) / Arizona State University (Publisher)
Created2020
Description
This dissertation research studies long-term spatio-temporal patterns of surface urban heat island (SUHI) intensity, urban evapotranspiration (ET), and urban outdoor water use (OWU) using Phoenix metropolitan area (PMA), Arizona as the case study. This dissertation is composed of three chapters. The first chapter evaluates the SUHI intensity for PMA using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) product and a time-series trend analysis to discover areas that experienced significant changes of SUHI intensity between 2000 and 2017. The heating and cooling effects of different urban land use land cover (LULC) types was also examined using classified Landsat satellite images. The second chapter is focused on urban ET and the impacts of urban LULC change on ET. An empirical model of urban ET for PMA was built using flux tower data and MODIS land products using multivariate regression analysis. A time-series trend analysis was then performed to discover areas in PMA that experienced significant changes of ET between 2001 and 2015. The impact of urban LULC change on ET was examined using classified LULC maps. The third chapter models urban OWU in PMA using a surface energy balance model named METRIC (Mapping Evapotranspiration at high spatial Resolution with Internalized Calibration) and time-series Landsat Thematic Mapper 5 imagery for 2010. The relationship between urban LULC types and OWU was examined with the use of very high-resolution land cover classification data generated from the National Agriculture Imagery Program (NAIP) imagery and regression analysis. Socio-demographic variables were selected from census data at the census track level and analyzed against OWU to study their relationship using correlation analysis. This dissertation makes significant contributions and expands the knowledge of long-term urban climate dynamics for PMA and the influence of urban expansion and LULC change on regional climate. Research findings and results can be used to provide constructive suggestions to urban planners, decision-makers, and city managers to formulate new policies and regulations when planning new constructions for the purpose of sustainable development for a desert city.
ContributorsWang, Chuyuan (Author) / Myint, Soe W. (Thesis advisor) / Brazel, Anthony J. (Committee member) / Wang, Zhihua (Committee member) / Hondula, David M. (Committee member) / Arizona State University (Publisher)
Created2018
Description
A well-insulated dark conventional rooftop can be hotter than any other urban surface, including pavements. Since rooftops cover around 20 – 25% of most urban areas, their role in the urban heat island effect is significant. In general, buildings exchange heat with the surroundings in three ways: heat release from the cooling/heating system, air exchange associated with exfiltration and relief air, and heat transfer between the building envelope and surroundings. Several recent studies show that the building envelope generates more heat release into the environment than any other building component.Current advancements in material science have enabled the development of materials and coatings with very high solar reflectance and thermal emissivity, and that can alter their radiative properties based on surface temperature. This dissertation is an effort to quantify the impact of recent developments in such technologies on urban air. The current study addresses three specific unresolved topics: 1) the relative importance of rooftop solar reflectance and thermal emissivity, 2) the role of rooftop radiative properties in different climates, and 3) the impact of temperature-adaptive exterior materials/coatings on building energy savings and urban cooling. The findings from this study show that the use of rooftop materials with solar reflectance above 0.9 maintain the surface temperature below ambient air temperature most of the time, even when the materials have conventional thermal emissivity (0.9). This research has demonstrated that for hot cities, rooftops with high solar reflectance and thermal emittance maximize building energy savings and always cool the surrounding air. For moderate climate regions, high solar reflectance and low thermal emittance result in the greatest building energy cost savings. This combination of radiative properties cools the air during the daytime and warms it at night. Finally, this research found that temperature-adaptive materials could play a significant role in reducing utility costs for poorly insulated buildings, but that they heat the surrounding air in the winter, irrespective of the rooftop insulation.
Through the detailed analysis of building façade radiative properties, this dissertation offers climate-specific design guidance that can be used to simultaneously optimize energy costs while minimizing adverse warming of the surrounding environment.
ContributorsPrem Anand Jayaprabha, Jyothis Anand (Author) / Sailor, David (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Huang, Huei-Ping (Committee member) / Wang, Liping (Committee member) / Yeom, Dongwoo Jason (Committee member) / Arizona State University (Publisher)
Created2022
Description
City governments have an opportunity to address historic environmental injustices through the management of their urban forests. When applying environmental justice to the management of urban trees, the common approach is to plant new trees in areas with high proportions of underserved residents and low tree canopy. This is the approach taken by many programs, such as the MillionTrees programs in Los Angeles and New York City. However, these initiatives do not always result in just outcomes and, in some cases, exacerbate existing inequities. This suggests the need for a model of urban tree canopy (UTC) justice that encapsulates distributive, procedural, and recognition justice. In this thesis, I suggest such a model of UTC justice that incorporates ecosystem services and disservices to understand resident satisfaction with neighborhood trees. I then apply the model to the case of the Phoenix, Arizona metropolitan area by assessing local UTC plans for mentions of environmental justice. Finally, I use multiple regression analysis to identify the relationship between neighborhood tree canopy percentage and resident satisfaction with neighborhood trees. Results indicate that tree canopy is a statistically insignificant determinant of resident satisfaction in 23 of 30 models. This supports my model of UTC justice in that it suggests that there is a confounding variable between UTC provisioning and resident satisfaction. This thesis culminates in recommendations for city governments, including the use of longitudinal socioecological surveys to evaluate the need for and success of UTC plans for environmental justice.
ContributorsCrichlow, Timara (Author) / DesRoches, Tyler (Thesis advisor) / Coseo, Paul (Thesis advisor) / Melnick, Rob (Committee member) / Pataki, Diane (Committee member) / Arizona State University (Publisher)
Created2024