ETD Search Results: instcode:osu

1. abdulkarim, dina. The Restorative Effects of Livable Spaces.

Degree: PhD, City and Regional Planning, 2012, Ohio State University

► The present research builds on Whyte’s work on livable places in by… (more)

Subjects: Urban Planning

Keywords: Public Places, Public Plazas, Livability, Restorativeness

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2. Anacker, Katrin B. Analyzing mature suburbs through property values.

Degree: PhD, City and Regional Planning, 2006, Ohio State University

► The United States can be characterized as a nation of suburban homeowners.… (more)

▼ The United States can be characterized as a nation of suburban homeowners. More than 50 percent of Americans live in suburbs, and almost 19 percent of them live in so-called first suburbs. Nationwide the homeownership rate is almost 70 percent. For the majority of homeowners, a home represents the biggest investment in their lives and many expect their property values to increase. If mature suburbs have problems or are in decline, then property values may decrease and investment value will be lost. Recently, many mature suburbs have become concerned that history will repeat itself and they will see the same decline that central cities have witnessed. This study uses mixed methods (i.e., expert interviews and regressions) to create a definition of mature suburbs, to provide an overview of public policies that benefit homeowners in mature suburbs, to analyze how property values of single family homes in mature suburbs have behaved compared with those in central cities and developing suburbs, and to analyze what specific factors have influenced property values of single family homes in mature suburbs compared with those in central cities and developing suburbs. The geographic scope of this study is three counties in Ohio: Cuyahoga (Cleveland area), Franklin (Columbus area), and Hamilton (Cincinnati area). Expert interviews reveal that despite the common perception of a policy blindspot some policies do benefit homeowners in mature suburbs. However, current policies should be modified to benefit both mature suburbs in need and homeowners that want to break even on their investment. Overall, mature suburbs are unique. Despite many stereotypes, there is variety in terms of residents and housing stock that should receive attention in future research efforts. Quantitative analyses of the mature suburbs in the study show that there is no overall suburban decline in terms of property values, although some communities should be concerned with their appreciation rates. The analyses also show that housing space and adjacency to work places and transportation networks are important variables that should be factored in by policy makers. The situation that mature suburbs are in does not seem to be hopeless. Advisors/Committee Members: Morrow-Jones, Hazel A.

Subjects: Urban and Regional Planning

Keywords: housing; property values; house prices; mature suburbs; Cleveland; Columbus, OH; Cincinnati

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3. Arya, Sanjeev. Empirical Modeling of Regional Stream Habitat Quality Using GIS-Derived Watersheds of Flexible Scale.

Degree: PhD, City and Regional Planning, 2002, Ohio State University

► Two new watershed-delineation approaches are used to build statistical regression models that… (more)

Keywords: Biotic Integrity; Habitat; Stream; GIS; Watershed; Scale; Regression; Ecoregion; ECBP; QHEI

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4. Ataov, Anli. Children’s perception of urban waterfronts and their responses to them – emotional reactions and perceived opportunities for activity.

Degree: PhD, City and Regional Planning, 1998, Ohio State University

► Urban waterfronts can have important affects on children’s environmental experiences. Attributes of… (more)

▼ Urban waterfronts can have important affects on children’s environmental experiences. Attributes of urban waterfronts can elicit strong feelings about the significance of those sites. By looking at this section of cities from children’s point of view, it becomes possible to derive children’s essential evaluative and behavioral responses and salient visual attributes. This can thereby help identify the design features for a planning practice of urban waterfronts where children are a consideration. This study aims to explore children’s emotional and behavioral responses to urban waterfront scenes and visual attributes consonant with those responses, and examine multiple relationships between them.Ninety 9 to 11 years-old children of different school, ethnic, and gender backgrounds participated in the study. They saw representative color images of urban waterfronts, ranked based on their preference, and responded to two sets of questions for the most liked, the second most liked, and the least liked scenes. I applied the first set of questions from an anthropological method, the Heuristic Elicitation Methodology (HEM). HEM suggests developing the constructs from the subjects’ responses in their own language and give equal emphasis to qualitative and quantitative methods. This set included open-ended questions. They revealed the frequency of mentions of evaluative and behavioral responses and salient visual attributes in children’s own language. The second set included structured questions to which children answered with a “yes” or “no.” I included these questions to test the applicability of visual attributes and evaluative appraisals found relevant to people’s environmental experiences in previous investigations. The data analysis included five issues: 1) relationships between derived attributes and appraisals; 2) relationships between selected attributes and appraisals; 3) children’s perception; 4) relationships between attributes and behaviors; and 5) group comparisons. I applied content analysis to derive the meaningful structures of evaluative appraisals, behavioral patterns, and visual attributes, and I used various multivariate analyses to reveal underlying dimensions of perception and understand the relationships between appraisals, behaviors, and attributes. The analyses revealed the following results: 1) ‘people’, ‘visual form’, and ‘nature’ explain preference, and ‘compatible land-use’, ‘dilapidated nature’, and ‘crowding’ explain dislike for the scenes; 2) Children’s ‘aesthetic value’ positively relates to the attributes ‘naturalness, order, and information’, and children’s ‘fear’ positively relates to ‘enclosure’; 3) Children perceive urban waterfront scenes in two dimensions including man-made/naturalness and compatible land-use/disorder; 4) Behaviors and attributes involve five relationships between: a) water-related and nature and man-made, b) interaction with nature, c) physical and openness, d) social interaction and people, and e) exploratory and man-made; 5) Few differences exist among the subgroups. Advisors/Committee Members: Nasar, Jack L.

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5. Ayman, Ismail M. A multiobjective tradeoff model for stormwater runoff, flooding and housing return.

Degree: PhD, City and Regional Planning, 1998, Ohio State University

► A multiobjective model was developed first, to integrate, within a single framework,… (more)

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6. Beck, Rachel K. The Impact of Community Satisfaction on Retention among Army Personnel.

Degree: Master of City and Regional Planning, City and Regional Planning, 2012, Ohio State University

► In an effort to retain high quality service members in its All-Volunteer… (more)

Subjects: Urban Planning

Keywords: quality of life, community satisfaction, livability, retention, military, Army

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7. Beydoun, Mustapha. Vehicular characteristics and urban air pollution: socioeconomic and environmental policy issues.

Degree: PhD, City and Regional Planning, 2004, Ohio State University

► The primary goals of this research were to clarify the relationships between… (more)

▼ The primary goals of this research were to clarify the relationships between vehicular emissions and (1) vehicular and socioeconomic characteristics, and (2) ambient pollution concentrations. To this end, the study utilizes data from three inspection and maintenance (I/M) programs, the US Census, and the US Environmental Protection Agency’s National Emission Inventory and Air Quality System. The study finds that vehicle characteristics do affect vehicle emissions. Model-year, fuel economy, mileage, and engine size are the most significant vehicle characteristics, although other characteristics, such as vehicle weight, make, and certain engine attributes are also found to influence emissions. The dirtiest 10% of the vehicular fleet, the high-emitters, are responsible for a disproportionately large percentage of CO, HC, and NO emissions. For example, high-emitters account for more on-road CO emissions than the cleanest 75% of the vehicle fleet. High emitters are found to be a problem for all makes, model-years, and vehicle types. A strong connection between fuel efficiency and emissions is found in all vehicle makes and for all model-years. The current regulatory disconnect between vehicle fuel economy and emission standards thus needs to be bridged. This can be done by changing the way vehicle emissions are regulated: by regulating emissions in grams/gallon, rather than the current grams/mile standard. The socioeconomic characteristics of vehicle owners have an important effect on vehicle emissions. Both income and education are the most important socioeconomic variables with regard to emissions, although education proves to be a slightly better explanatory variable than income. Race and the urban character of an area are also found to be important predictors of vehicle emissions and emission test failure. Lastly, the study finds that the NET on-road car and truck emissions estimates and those derived from the study’s Massachusetts I/M data to be fairly consistent with one another. Although a relationship is found between vehicular CO emissions and ambient CO, none was found between NO emissions and ambient NO. The analysis of the relationship between vehicular NO and HC emissions and ambient ozone levels led to confounding results, due to data limitations and the long-distance character of ozone pollution. Advisors/Committee Members: Guldmann, Jean-Michel.

Keywords: Air pollution; Emissions; vehicles; I/M programs; Fuel efficiency; Socioeconomic characteristics

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8. Braam, Sierk Hendrik. Harrison West: a case study of gentrification and economic and racial integration.

Degree: Master of City and Regional Planning, City and Regional Planning, 1996, Ohio State University

► Harrison West has felt the forces of gentrification through the concerted effort… (more)

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9. Chen, Wei-Bin B. Optimal allocation of stormwater pollution control technologies in a watershed.

Degree: PhD, City and Regional Planning, 2006, Ohio State University

► In recent decades, more than 90 percent of urban growth in the… (more)

Keywords: BMPs, optimal allocation, sediment, GIS, TMDL, EQS, water quality, nonpoint pollution, linear programming, integer programming, SWMM, simulation

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10. Chun, Bum Seok. Three-Dimensional City Determinants of the Urban Heat Island: A Statistical Approach.

Degree: PhD, City and Regional Planning, 2011, Ohio State University

► There is no doubt that the Urban Heat Island (UHI) is a… (more)

▼ There is no doubt that the Urban Heat Island (UHI) is a mounting problem in built-up environments, due to the energy retention by the surface materials of dense buildings, leading to increased temperatures, air pollution, and energy consumption. Much of the earlier research on the UHI has used two-dimensional (2-D) information, such as land uses and the distribution of vegetation. In the case of homogeneous land uses, it is possible to predict surface temperatures with reasonable accuracy with 2-D information. However, three-dimensional (3-D) information is necessary to analyze more complex sites, including dense building clusters. Recent research on the UHI has started to consider multi-dimensional models. The purpose of this research is to explore the urban determinants of the UHI, using 2-D/3-D urban information with statistical modeling. The research includes the following stages: (a) estimating urban temperature, using satellite images, (b) developing a 3-D city model by LiDAR data, (c) generating geometric parameters with regard to 2-/3-D geospatial information, and (d) conducting different statistical analyses: OLS and spatial regressions. The research area is part of the City of Columbus, Ohio. To effectively and systematically analyze the UHI, hierarchical grid scales (480m, 240m, 120m, 60m, and 30m) are proposed, together with linear and the log-linear regression models. The non-linear OLS models with Log(AST) as dependent variable have the highest R2 among all the OLS-estimated models. However, both SAR and GSM models are estimated for the 480m, 240m, 120m, and 60m grids to reduce their spatial dependency. Most GSM models have R2s higher than 0.9, except for the 240m grid. Overall, the urban characteristics having high impacts in all grids are embodied in solar radiation, 3-D open space, greenery, and water streams. These results demonstrate that it is possible to mitigate the UHI, providing guidelines for policies aiming to reduce the UHI. Advisors/Committee Members: Guldmann, Jean-Michel.

Subjects: Climate Change; Land Use Planning; Urban Planning

Keywords: Urban Heat Island; spatial analysis; 3-D city model

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11. Coston, Wanda Brendette. The stages of gentrification and neighborhood revitalization : a case study of the Dennison Place and Victorian Village neighborhoods, the Near North Side community, Columbus, Ohio.

Degree: Master of City and Regional Planning, City and Regional Planning, 1984, Ohio State University

Advisors/Committee Members: Gerckens, Laurence C.

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12. Cubukcu, Ebru. Investigating wayfinding using virtual environments.

Degree: PhD, City and Regional Planning, 2003, Ohio State University

► Wayfinding is the spatial knowledge about one’s current location, destination, and the… (more)

▼ Wayfinding is the spatial knowledge about one’s current location, destination, and the spatial relation between them. Wayfinding problems threaten people’s sense of well-being, and cause loss of time and money. Designers and planners can improve wayfinding when they understand how physical environmental factors affect people’s wayfinding performance. This study explores the effect of personal and physical environmental characteristics on wayfinding performance. The personal characteristics include gender, age, and familiarity. The physical environmental characteristics include plan layout complexity, physical differentiation and its components vertical and horizontal differentiation. The experiment had eighteen (2 x 3 x 3) simulated environments, with two plan layouts (complex and simple), three kinds of vertical differentiation (no differentiation, object landmarks, and building landmarks) and three kinds of horizontal differentiation (no differentiation, road width variation, road pavement variation), and it also had four different question orders. 166 volunteers (98 male, 68 female) were tested individually. Participants were randomly assigned to one of the question orders and to one of the simulated environments with the constraint that there would be equal number of people in survey types, in plan layout conditions, in vertical differentiation conditions, and in horizontal differentiation conditions. The experiment had a learning phase and a test phase. In the learning phase, participants actively explored one of the simulated environments at their leisure up to four minutes. In the test phase the participants completed three spatial knowledge tasks (a direction estimation task, a navigation task, and a sketching task) and a survey which had questions on gender, age, frequency of playing computer game, realism of the simulated environment judgement and wayfinding strategies used in the navigation task. As expected, the Simple layouts, Higher Physical Differentiation, Vertical or Horizontal differentiation yielded better wayfinding performance than Complex layouts, Lower Physical differentiation, and No Vertical or Horizontal differentiation. Males performed better than Females, and performance improved with Familiarity. Advisors/Committee Members: Nasar, Jack L.

Keywords: Wayfinding; Environmental Psychology; Virtual Environments; Cognition

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13. Cubukcu, Kemal Mert. Geography and the cost of network infrastructure: the case of local telephone systems.

Degree: PhD, City and Regional Planning, 2003, Ohio State University

► On February 8, 1996, the U.S. Congress enacted the Telecommunications Act of… (more)

▼ On February 8, 1996, the U.S. Congress enacted the Telecommunications Act of 1996 to promote competition and reduce regulation in local telephone service, in order to secure lower prices and higher quality of service. The promise of competition in local service, however, has largely remained unfulfilled, and there is still much unknown about the cost structure of the telephone industry at the local level. The question of whether natural monopoly characteristics have ever existed has never been fully answered, and is still a valid one. The purpose of this research is to expand earlier empirical research on telephone costs by accounting for the site-specific (hedonic) characteristics of the service territory. In past research, these characteristics have been approximated by population density, customer density, or service territory area. In order to achieve a better understanding of the cost structure of the telephone industry, both total cost and disaggregate capital investment cost functions have been developed and econometrically estimated while including site-specific physical and geographical characteristics, such as (1) soil, (2) slope, (3) environmental quality, (4) service territory size, (5) street pattern, (6) population density, (7) land uses, and (8) exchange proximity. A translog total cost function is estimated at the company level, using 1980 data for 41 telephone companies operating within the state of New York. Disaggregate capital investment cost functions are estimated at the local exchange level for five different plant components: central office equipment, buildings, cables, pole lines, and underground conduits. A separate equation for the share of underground investment in total cable (underground and overhead) investment is also estimated. The size of the samples used in these estimations varies between 65 and 615, depending upon the data availability for the selected variables. Additive, log-log, and Box-Cox functional forms are considered, and the optimal functional form is selected using log-likelihood ratio tests. The empirical results show that site-specific factors (1) are significant determinants of costs in the telephone industry, and (2) provide substantial advantages (or disadvantages) to telephone companies regarding the output levels where economies of scale or density are exhausted. The results also show that significant cost savings and scale economies are achieved by expansion through densification (fixed service territory size). At the company sample mean, economies of scale are exhausted for a market of 61,543 telephone units. Economies of density, however, are exhausted at 610,836 units, a much higher level. These thresholds vary with the site-specific cost factors. Among the plant components, the strongest economies of density are achieved in pole (ε=0.60) and cable (ε=0.74) capital investments, followed by central office equipment (ε=0.92) and underground conduit (ε=0.90) investments. The only component where the exchanges experience diseconomies of density is buildings (ε=1.12). The total economies of density are 0.83 at the sample mean, implying that monopoly is the optimal form of production. It is concluded that monopoly is the optimal form of production for predominantly small to mid-size markets, when the expansion is achieved through densification, which implies a need for mergers among existing small and mid-size companies and exchanges. However, for larger markets and for newly emerging service areas, competitive entry to the market should be encouraged. Advisors/Committee Members: Guldmann, Jean-Michel.

Keywords: cost function; telephone systems; public utility economics; GIS

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14. Gough, Meghan Z. Factors Influencing Intergovernmental Collaboration in Planning: Lessons Learned from Post-Katrina Mississippi.

Degree: PhD, City and Regional Planning, 2008, Ohio State University

► The goal of this study was to identify the factors that promote… (more)

▼ The goal of this study was to identify the factors that promote or inhibit intergovernmental collaboration for planning. While research in planning stresses the value in collaborative planning, there is little attention paid to the factors that form and sustain collaborative relationships for planning. This is important due to the political nature of planning and due to the complexity of land use decision-making that demand collaborative problem solving. Using collaborative planning and network literatures as the theoretical basis, a framework was developed to test the factors that influenced decisions to work collaboratively instead of independently in post-Hurricane Katrina Mississippi. Following Hurricane Katrina, Mississippi Governor Haley Barbour established a framework for planning and rebuilding the Mississippi Gulf Coast that involved an inclusive and collaborative planning approach. The intention was the development of vertical collaboration between local and state governments, and horizontal collaboration between local governments. Because literature suggests that a crisis will increase collaboration, post-Katrina Mississippi offered an important opportunity to understand factors that influence the proclivity for intergovernmental collaboration. Respondent experiences, accounts, emotions, and opinions were documented through semi-structured interviews that were designed to encourage discussion about decisions to collaborate or to work independently. Data were coded using qualitative methods that tested the theoretical factors. Additionally, these methods allowed for emergent themes that fell out of the framework in order to provide additional explanation for vertical and horizontal intergovernmental collaboration. While all the theoretical factors influenced collaboration, the highest cited explanations for decisions to collaborate with other entities involved concerns about inclusion of actors, capacity potential, trust, and leadership. Costs of collaboration, planning knowledge, and values and cultural norms emerged as important influences on intergovernmental collaboration. Although more complex forms of collaboration were rare among Mississippi Gulf Coast communities, it appears that facilitated leadership and interdependence played important roles in establishing and maintaining collaborative relationships. Due to the increasing need for collaborative problem solving in land use planning, this study contributes to a more holistic understanding about what factors are important and how they can be utilized to build collaborative relationships for planning. Advisors/Committee Members: Evans-Cowley, Jennifer.

Subjects: Urban planning

Keywords: collaboration; land use planning; Hurricane Katrina; Mississippi

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15. Hoffman, Wayne Joseph. Race and property values: a study of five racially changing neighborhoods in Columbus, Ohio.

Degree: Master of City and Regional Planning, City and Regional Planning, 1972, Ohio State University

Advisors/Committee Members: Mills, W. Raymend.

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16. Hudson, Christopher J. Suburban sprawl, central city decline and the case for metropolitan cooperation in Franklin County, Ohio.

Degree: Master of City and Regional Planning, City and Regional Planning, 1995, Ohio State University

Advisors/Committee Members: Morrow-Jones, Hazel.

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17. Hur, Misun. Neighborhood Satisfaction, Physical and Perceived Characteristics.

Degree: PhD, City and Regional Planning, 2008, Ohio State University

► Researchers from many disciplines have examined neighborhood satisfaction. The research has focused… (more)

▼ Researchers from many disciplines have examined neighborhood satisfaction. The research has focused more on the personal, social, and psychological dimensions than on the physical environment in relation to neighborhood satisfaction. When studies include physical characteristics, they tend to look at the perceived physical characteristics, possibly overlooking the impact of the physical environmental features on neighborhood satisfaction. Furthermore, while studies have identified physical attributes of environments related to “aesthetic” response, research has not examined the link between physical and judgmental ratings of those attributes, nor has it looked at the link between those measures and neighborhood satisfaction. This dissertation builds a conceptual model that focuses on the multi-level connections among the physical, perceptual, and evaluative measures of the neighborhood environment as determinants of overall neighborhood satisfaction. It uses on-line survey, on-site observations, and the combined satellite image processing and GIS spatial analysis. The survey asks residents to rate their perceptions and evaluations of the neighborhood environment, and then to rate their overall neighborhood satisfaction. 382 survey responses were collected in Franklin County, Ohio. Observations assess the conditions of the fixed and semi-fixed physical environmental elements on 2021 blocks. For observations, this study designed, used, and tested the neighborhood physical environment inventory (NPEI) instrument on a handheld Personal Digital Assistant (PDA). The Normalized Differential Vegetation Index (NDVI) method was combined with GIS spatial analysis. To assess both structural and measurement relations in a single model, this study uses a Structural Regression Model based on the two-step modeling process. The findings reveal the significant direct and indirect effects of physical, perceptual, and evaluative measures on neighborhood satisfaction. The results extend the understanding of the neighborhood environment and residents´ quality of life. Methodologically, the study demonstrates advances in data collection through its on-line survey, on-site observation via a personal digital assistant (PDA), and GIS. Advisors/Committee Members: Nasar, Jack L.

Subjects: Area planning and development; Urban planning

Keywords: Neighborhood Satisfaction; Physical and Perceived Environmental Attributes; On-line Survey; Satellite Image Processing; GIS; Neighborhood Physical Environment Inventory; PDA; NDVI; Structural Regression Model; CFA; Incivilities; Vacant House

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18. Imeokparia, Timothy Oserejenoria. The design, implementation, and evaluation of an interactive multimedia environmental design research information system: architectural design review as case study.

Degree: PhD, City and Regional Planning, 2005, Ohio State University

► This dissertation reports on the design, implementation, and evaluation of an interactive… (more)

▼ This dissertation reports on the design, implementation, and evaluation of an interactive multimedia information system for environmental design research knowledge (IMMEDRIS). One of the primary goals of IMMEDRIS is to leverage the Internet as a channel for accelerating the dissemination and sharing of environmental design research (EDR) knowledge. To meet the requirement of the different user groups, a number of subsystems were designed to facilitate a complex set of views of EDR information for different contexts and applications. The prototype of IMMEDRIS as deployed has a tutorial and a decision aiding subsystem installed as a pilot project and evaluated in their function supporting the decision making process required by local government aesthetic-control regulations. Philosophical discussions and empirical research on the fundamental importance of categories to both learning and communication provides the framework for the design of IMMEDRIS. The design of the tutorial subsystem relies on the idea of visual learning developed in cognitive science and the notion of ostension explicated by Wittgenstein. The decision aiding subsystem is predicated on the notion of judgment as a contingent and contextual practice rather than as a practice guided by determinately fixed categories. Based on accounts by Kant and Wittgenstein on the role of examples in learning concepts and making judgments the decision aiding subsystem relies on a purely procedural criteria under a standard of reasonable method. It outlines a decision procedure which relies on our ability for “empirical classification” and “empirical predication.” With aesthetic judgment as a paradigmatic example and the architectural design review function of most local governments in the United States as case study, the dissertation seeks to locate the goal of objectivity and the methodology of quantification of much EDR within a broader normative framework to give their findings meaning. The project that forms the basis of this dissertation offers a tool that enables the application of concepts derived from EDR to problem solving and decision making. The dissertation evaluated the effectiveness and utility of the tutorial and decision aiding subsystems of the prototype. It was evaluated for usability and its effectiveness in improving a decision making task. Advisors/Committee Members: Nasar, Jack L.

Subjects: Urban and Regional Planning

Keywords: environmental aesthetics, environmental design research, applicability Gap, research utilization, information system

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19. Joshi, Puspa Man. Reasoned Action Versus Planned Behavior In Bus Use.

Degree: PhD, City and Regional Planning, 2003, Ohio State University

► Socioeconomic variables did have significant effects on micro-level variables. Gender had significant… (more)

Keywords: Fishbein Ajzen Beliefs Attitude Behavioral Intention Bus Using Behavior Transportation

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20. Jun, Hee-Jung. Diverging Paths: The Determinants of Neighborhood Change Across Space and Time.

Degree: PhD, City and Regional Planning, 2010, Ohio State University

► The principal research question is “Why do some neighborhoods in U.S. urban… (more)

▼ The principal research question is “Why do some neighborhoods in U.S. urban areas stay economically healthy and others do not?” This study proposes three hypotheses on diverging paths of neighborhood change: first, neighborhood change is produced by interactions of factors at the metropolitan, municipal, and neighborhood scales; second, “the politics of scale”—city size and the homogeneity level of household interests in a municipality—is an important factor leading to different paths and outcomes of neighborhood change; and third, factors of neighborhood change have altered over time. The primary data set used in this study is the Neighborhood Change Data Base by GeoLytics that includes the decennial census data across the country from 1970 to 2000 at the census tract level. This study examines the proposed hypotheses with a random sample of 35 metropolitan areas and analyzes the data set using multilevel modeling. Using per capita income and average housing value in neighborhoods, this study develops an index of neighborhood economic condition and uses the change of this index as the dependent variable in the empirical analyses. The explanatory variables included in the model are based on the theories on neighborhood change and the comprehensive model of neighborhood change proposed in this study. This study finds clear evidence to support the proposed hypotheses. First, neighborhood change is produced by interactions of factors at the metropolitan, municipal, and neighborhood scales. Secondly, the politics of scale matters in neighborhood change in that neighborhoods are more likely improve economically in smaller and more homogeneous cities. Finally, factors affecting neighborhood change have altered over time. Based on the findings, this study suggests that it is essential to take metropolitan, municipal, and neighborhood contexts into account together in setting public policies for community development. With regard to the politics of scale, larger and more heterogeneous cities should learn from smaller and more homogeneous cities by, for example, working to increase community interaction, which is positively related to city growth. Finally, because the factors associated with neighborhood change were different in different time periods, local governments should plan in preparation for housing market change. By taking the municipal and metropolitan contexts as well as the neighborhood context into account, this study helps improve our understanding of diverging paths and determinants of neighborhood change. If we know why neighborhoods undergoing changes move in different directions and how the influences of neighborhood change have altered over time, we can do a better job of designing policies to ameliorate different conditions. In a more theoretical vein, this study contributes to the literature by providing a comprehensive model of neighborhood change over space and time. Advisors/Committee Members: Morrow-Jones, Hazel A.

Subjects: Urban planning

Keywords: neighborhood; neighborhood change; multilevel modeling

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21. Kim, Jun-Pill. LAND-USE PLANNING AND THE URBAN HEAT ISLAND EFFECT.

Degree: PhD, City and Regional Planning, 2009, Ohio State University

► Local climate changes due to urbanization have been well documented. These changes… (more)

Subjects: Environmental science

Keywords: Remote Sensing, Urban heat island (UHI), Land-use planning

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22. Kim, Moon-Jeong. Residential Location Decisions: Heterogeneity and the Trade-off between Location and Housing Quality.

Degree: PhD, City and Regional Planning, 2010, Ohio State University

► This dissertation is a socio-economic approach to the residential location model. Heterogeneity… (more)

▼ This dissertation is a socio-economic approach to the residential location model. Heterogeneity of households’ residential location decisions and actual trade-offs made in the housing market are explored. Specifically, this dissertation explores both heterogeneous residential location decisions among different categories of households and trade-offs between location and housing quality. It is assumed that social values are reflected in locations, and locations with highly valued characteristics are preferred by homebuyers, and that living in preferred locations means that the household has higher social status. In order to live in preferred locations, households may have to make a trade-off by giving up some housing quality. This research uses a repeat homebuyers’ dataset in Franklin County, which is the central county in the greater Columbus, Ohio metropolitan area. I utilize the two-stage nested logit model with interaction terms for different household characteristics. The estimation results provide a range of information about households’ residential location decisions. First, households with school-aged children are attracted to locations with high school quality and high-income neighbors, while choosing older houses (with more bedrooms). In other words, they make a trade-off by choosing older houses—less expensive homes in the housing market—in order to live in these preferred locations. Second, middle-income households with school-aged children are more likely to choose these same preferred locations, but they tend to choose older and smaller houses with more rooms. As expected, their relatively limited incomes seem to stimulate the trade-off between location and housing quality. They even accept higher crime rates in their community choices. Third, households with householders who are 50 years old and over prefer safer communities, indicating that safety is an important social value to this group. In their dwelling choices, this group is more likely to choose multi-family attached houses (e.g., condos, duplexes, and townhouses) with fewer bedrooms. This group’s age-specific circumstances seem to affect their housing choices significantly. The operationalization of the concept of social status with the status of locations as preferred locations is one contribution of this work. The second contribution is that this study broadens the perspective of the residential location modeling by providing a variety of determinants associated with community and dwelling characteristics. The utilization of the random utility theory—particularly the nested logit modeling—makes the third contribution. I believe that this study will help extend the understanding of actual determinants of residential location decisions in the U.S. housing market, and improve the urban residential location theory. Advisors/Committee Members: Morrow-Jones, Hazel A.

Subjects: Urban planning

Keywords: residential location decisions; trade-offs; heterogeneity; random utility modeling

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23. Kim, Tae-Kyung. Dynamic analysis of sulfur dioxide monthly emissions in U.S. power plants.

Degree: PhD, City and Regional Planning, 2004, Ohio State University

► The Clean Air Act Amendments (CAAA) of 1990 marked a moving away… (more)

▼ The Clean Air Act Amendments (CAAA) of 1990 marked a moving away from command-and-control air quality regulations towards a market-based approach, whereby polluters are assigned annual emission allowances, and are free to select the minimum-cost approach that will keep their actual annual emissions within this allowance limit. Within this context, the objectives of this research are to better understand (1) the temporal patterns of SO2 emissions from power plants, and (2) the factors affecting fuel choice and SO2 emissions. Large power plant-related datasets from various sources are collected, processed, and combined for empirical analyses, to explain monthly fuel shipments, fuel consumptions, sulfur shipments, gross and net SO2 emissions, and fuel choices. Because of the interdependency of these various sulfur dioxide, simultaneous equations estimation techniques are used. The empirical findings are as follows. First, forecasts of electricity demand and fuel prices are the main determinants of the amounts and types of fuel shipments. The relationship between fuel shipments and forecasted fuel needs is very strong for the current month, and gradually weakens over future months, due to forecasting difficulties and the costs of fuel inventories. Second, net SO2 emissions increase with allowances, although not proportionately, because of the likely effects of allowance banking and trading. Third, each plant reduces SO2 emissions gradually over time, to account for the future more stringent Phase II emissions constraints. Fourth, plants emit less in winter, possibly because higher electricity leads to reduced unit SO2 emission abatement costs. Finally, plants with an FGD usually consume more high-sulfur fuels due to their potential abatement capability. An integrated analysis of the effects of changing emission allowances and installing FGD is conducted through a simulation. Reducing allowances by 1% leads to an emissions reduction of 0.15% at the plant level. However, if allowances were reduced uniformly nationwide, this effect would be stronger because of reduced allowance trading opportunities. Advisors/Committee Members: Guldmann, Jean-Michel.

Keywords: Sulfur dioxide emissions; Annual emission allowances; Emission trading; Environmental regulation; Clean Air Act Amendments of 1990

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24. Kim, Youngkook. Impacts of Transportation, Land Uses, and Meteorology on Urban Air Quality.

Degree: PhD, City and Regional Planning, 2010, Ohio State University

► Criteria air pollutants, such as nitrogen oxides (NOx), carbon monoxide (CO), sulfur… (more)

▼ Criteria air pollutants, such as nitrogen oxides (NOx), carbon monoxide (CO), sulfur dioxide (SO2), particulate matter (PM), and ozone (O3), are characterized by temporal and locational hot spots in urban areas, frequently violating pollution standards, and, as a result, threatening the health and well-being of the population. Several factors, such as the intensity and duration of emissions, the chemical reactions among pollutants, the uptake and assimilation of pollutants by urban vegetation, and the meteorological factors that induce chemical reactions and atmospheric dispersion, have been considered as explanatory variables in air quality models. Among them, emissions from motor vehicles turn out to be a key determinant of the spatial and temporal patterns of ambient pollution concentrations. The purpose of this research is to formulate and estimate (1) metropolitan-wide time-series air quality models and (2) land-use regression (LUR) air quality panel models, in order to explain spatio-temporal variations in pollution concentrations. Using the Seoul Metropolitan Area as a case study, traffic counts, vehicle-kilometers-traveled (VKT), land uses, and meteorological factors, such as solar radiation, temperature, humidity, wind speed and wind direction, are used as explanatory variables. An extensive understanding of atmospheric pollutants chemistry is reflected in the formulation of these models. Differences in concentrations measured at air quality monitoring stations (AQMs) across the week (weekdays vs. Sunday) and geographical locations (roadside vs. background), are also investigated using dummy variables and the product of these variables with the original variables. The results of the time-series models and panel regression models indicate that traffic counts and VKT are significant in explaining the concentrations of both directly emitted pollutants, such as NO2, CO, SO2, and PM, and O3, a secondary pollutant. The concentrations of the directly emitted pollutants are positively correlated with vehicle flows. In the case of O3, however, vehicle emissions have a negative impact on O3 concentrations. Since solar radiation, temperature, humidity, and wind speed influence both chemical reactions and physical dispersion, these factors are closely correlated with pollution concentrations. In particular, solar radiation plays a critical role regarding NO2 and O3 concentrations. Ultraviolet (UV) radiation causes the photodissociation of NO2, providing favorable conditions for the generation of O3 in the troposphere. The estimated models confirm that solar radiation have a positive effect in the O3 models, and a negative one in the NO2 models. Reduced traffic flows on Sunday increase the ratio of volatile organic compounds (VOC) to NOx and, consequently, lead to favorable conditions for O3 generation. Less O3 titration and less HNO3 formation occur on Sunday as compared to weekdays, resulting in higher O3 concentrations on Sunday. For directly emitted pollutants, reduced traffic flows on Sunday induce a decrease in concentrations. The locations of the AQMs turn out to be critical. Traffic flows closer to AQMs have larger impacts on pollution concentrations. The product terms between VKT and roadside dummy variable display the expected results: for directly emitted pollutants, the coefficients are significant and positive, suggesting that the impacts of roadside VKT are greater than those of background VKT. In the case of O3, the estimated coefficients are negative, indicating that the negative impacts of VKT on O3 concentrations are increased at roadside areas. Nitric oxide emissions from commercial and residential areas have a negative impact on O3 concentrations. Plants have an O3 assimilation capacity, but also emit biogenic VOC during the growing seasons, generating simultaneous negative and positive impacts. The overall vegetative areas impact on O3 concentrations is positive. For directly emitted pollutants, however, vegetative areas have a negative impact. Since residential, commercial, and industrial areas generate anthropogenic emissions, the coefficients of these land uses are positive. Advisors/Committee Members: Guldmann, Jean-Michel.

Subjects: Urban planning

Keywords: air pollution; time-series model; panel model; land-use regression

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25. Lee, David Jung-Hwi. Optimal Regional Allocation of Population and Employment: Application of a Spatial Interaction Commuting Model.

Degree: PhD, City and Regional Planning, 2010, Ohio State University

► The objectives of this dissertation are: (1) to develop a commuting spatial… (more)

▼ The objectives of this dissertation are: (1) to develop a commuting spatial interaction model incorporating various spatial structure variables, such as Competing Destinations (CD) and Intervening Opportunities (IO) factors with Tobit regression; (2) to develop optimization planning applications with both linear and non-linear programming utilizing the empirically estimated Tobit models with the goal of minimizing total commuting costs, and (3) to assess multiple regional scenarios combining alternative land development strategies and zonal population density constraints. All the models are applied to the Fredericksburg Area (FAMPO Region) combining the counties of Stafford, Spotsylvania, King George, and Caroline, and the city of Fredericksburg in the State of Virginia. Census Transportation Planning Package (CTPP) 2000 data and Auditor’s property data are used. The empirical results support considering the spatial structure of the region in the modeling process. The independent variable of this research, commuting flow, is a censored variable and seems appropriate to be handled with Tobit model. Four different spatial interaction commuting models have been estimated using Tobit regression: (1) Model 1 with basic variables of the gravity model; (2) Model 2 with two more additional variables, which represent spatial structure. Those are intervening opportunities (IO) and competing destinations (CD) variables; (3) Model 3 with further additional socio-economic variables; and (4) Model 4 extends Model 3 by adding quadratic terms. These four models are estimated by Tobit regression, and the results point to improvements by adding spatial structure variables and additional socio-economic variables and the quadratic functional form demonstrates the best goodness-of-fit statistics. To measure the impacts of independent variables on the dependent variable, two further analyses are conducted: (1) elasticity; (2) marginal effect analysis. It is shown that marginal effect of each independent variable on the dependent variable varies depending on other variables in the quadratic model. Linear and non-linear planning optimization models are formalized and implemented using Fredericksburg Area Metropolitan Planning Organization (FAMPO) area data. The models spatially allocate population and employment to minimize total commuting costs. The results demonstrate that density constraints are critical in determining the distribution of population and employment. For a given land development strategy, the highest possible densities allow for minimizing commuting costs. However, commuting costs do not represent all urban and regional development costs. Thus, the results are extended to account for land development costs and congestion costs, leading to a comprehensive analysis of the implications of different density and land development strategies. The results demonstrate that the optimal development densities are very sensitive to the congestion cost function. With increase of congestion level, a land development strategy allowing for sprawl to some extent could be a smart policy to reduce regional vehicle mile travel (VMT) and consequently total pollution level as well. Advisors/Committee Members: Guldmann, Jean-Michel.

Subjects: Urban planning

Keywords: Commuting, Spatial Interaction Modeling, Normative Planning Models, Tobit regression, Forecasting, Spatial Structure, Competing Destinations, Intervening Opportunities, Optimization, Development Costs, Congestion Costs, Optimal Development Densities

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26. Li, Yanmei. The dynamic interaction between residential mortgage foreclosure, neighborhood characteristics, and neighborhood change.

Degree: PhD, City and Regional Planning, 2006, Ohio State University

► Many factors lead to mortgage default and foreclosure, and neighborhood characteristics are… (more)

▼ Many factors lead to mortgage default and foreclosure, and neighborhood characteristics are among the most important (Quercia and Stegman, 1992). However, few scholars have examined how neighborhood characteristics contribute to mortgage foreclosure (Cotterman, 2001; Baxter and Lauria, 2000; Lauria, 1998) and none of the previous studies have systematically addressed the mutual interaction between foreclosure and neighborhood characteristics and change. This research uses multiple datasets from Ohio’s two most populous counties to examine some of these previously omitted or understudied aspects of the issue. Particular attention has been paid to each neighborhood’s racial composition, economic level, housing prices and other housing stock characteristics as well as to the changes over time in those variables. The analysis starts with simple descriptive statistics, spatial autocorrelation analysis, and comparison of different foreclosure patterns in the two counties. Then spatial regression models, H-Robust models and Iterated Seemingly Unrelated Regression (ITSUR) are used to explain the interaction between mortgage foreclosure and neighborhood characteristics and change. The study finds that foreclosures cluster in low-income minority neighborhoods and inner cities, although suburban areas have seen an increase. Educational attainment, median household income, and average housing cost burden contribute to foreclosures in both counties. As expected there are similarities and disparities in the interaction of foreclosure and neighborhoods between the two counties. The use of panel data, Robust OLS, spatial lag models and SUR has solved some problems related to spatial dependence, heteroskedasticity and mutual non-recursive interaction between foreclosure and neighborhoods. The research not only contributes to the literate and methodology in related topics, but also contributes to our understanding of the relationship between foreclosure and neighborhoods, and will assist in the creation of better policies to deal with the issue of foreclosure. The policy recommendations include a strong focus on neighborhood foreclosure prevention, not just policies aimed at individual homeowners. These policies might focus on neighborhoods with low educational attainment, an increasing percentage black population, or a high female headship rate. This project suggests that foreclosure prevention programs not be the same in all places. Advisors/Committee Members: Morrow-Jones, Hazel A.

Subjects: Urban and Regional Planning

Keywords: Mortgage Foreclosure; Neighborhood Chacteristics; Neighborhood Change; Spatial Lag Model; H-Robust OLS; Seemingly Unrelated Regression (SUR)

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27. Lu, Jia. Land-Use Structure And Population And Employment Densities: Empirical Analysis Of The Columbus (Ohio) Metropolitan Area.

Degree: PhD, City and Regional Planning, 2008, Ohio State University

► Population and employment densities have been the focus of many studies in… (more)

▼ Population and employment densities have been the focus of many studies in recent decades. Because of their complex characteristics, it is difficult to model them with simple functional forms and variables. In the past, the negative exponential model, with distance(s) to major Central Business District(s) (CBDs), as the major explanatory variables(s), have been tested extensively, using a monocentric framework initially and a polycentric one more recently. As an alternative to these models, a new density modeling approach is proposed in this research, based on the integration of concepts related to both multiple population and employment centers and landscape ecology theory. Regression models are specified to estimate the empirical relationships between population and employment densities, and (1) distances to major CBDs, (2) distances to amenities and disamenities, and (3) landscape indices that characterize the land-use structure. A comprehensive spatial and non-spatial database is built over all Traffic Analysis Zones (TAZ) of the seven counties of Central Ohio. Extensive applications of GIS have been necessary to compute indices and distances to CBDs, amenities, and disamenities, as well as to map urban morphology and distances. Negative exponential models have been estimated at both the metropolitan and county levels, using ordinary least square regression. The best exponential models at the metropolitan level, with distances to the 43 major CBDs within the seven counties as independent variables, explained about 58% and 59% of the variations in population and employment densities, respectively, but several distance coefficients were not significant and of the wrong signs. Estimated at the county level, homogenous exponential models for population and employment densities explain: 39% and 42% of variations in Franklin County; 63% and 73% of variations in Delaware County; 67% and 64% of the variations in Licking County; 84% and 76% of the variations in Fairfield County; 61% and 73% of the variations in Pickaway County; 59% and 68% of variations in Madison County; and 58% and 82% of variations in Union County, respectively. Finally, the best pooled models of population and employment densities, with county dummy variables, second-order terms for the significant landscape indices (MECI: Mean Edge Contrast Index, and DO3: Dominance Index), and five interaction variables, explain about 66% and 73% of the variations in population and employment densities in the Columbus MSA, respectively. The results provide evidence that distances to major metropolitan and county CBDs and two spatial indices significantly explain the variations of both population and employment densities. MECI and DO3 are consistently significant across the seven counties. In addition, the distances to the MSA and county CBDs play important roles in most models. The results provide further evidence that the Columbus MSA is polycentric for both population and employment densities. Models for rural counties tend to perform better than urban counties, due to their less complicated residential and employment spatial structure. Areas for further research are discussed. Advisors/Committee Members: Guldmann, Jean-Michel.

Subjects: Geography; Urban planning

Keywords: Population And Employment Densities; Urban Modeling; Urban Geography; Land-Use Structure

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28. Morckel, Victoria Chaney. Predicting the Probability of Housing Abandonment Using Hierarchical and Spatial Models.

Degree: PhD, City and Regional Planning, 2012, Ohio State University

► By decreasing property values, discouraging private investment, and inviting criminal activities, abandoned… (more)

▼ By decreasing property values, discouraging private investment, and inviting criminal activities, abandoned houses contribute to neighborhood decline. Since some neighborhoods have more abandoned houses than others, dealing with this problem is important from an equity standpoint. To improve public policy and planning efforts, this study seeks to better understand why neighborhoods differ in their probability that a house will be abandoned. It examines four related questions using data from Youngstown, Ohio and Columbus, Ohio. First, the study considers what constructs are most salient to understanding abandonment, and how those constructs relate to the probability that a house will be abandoned. A factor analysis revealed that market conditions, gentrification, physical neglect, and socioeconomic conditions underlie abandonment. A multilevel regression model showed that three of the four constructs (market conditions, gentrification, and physical neglect) predict the probability of abandonment. Second, it asks whether abandonment exhibits spatial dependence at the neighborhood level, and if so, whether the regression model can be improved by taking this relationship into account. A Moran’s I statistic indicated that abandonment clusters in both cities of interest. Adding a spatially lagged abandonment variable to the multilevel regression model showed that the level of abandonment in surrounding neighborhoods influences the probability of abandonment in a neighborhood of interest. Third, it examines how other conditions in surrounding neighborhoods influence the probability. Adding a spatially lagged version of each factor to the regression model revealed that physical neglect in surrounding neighborhoods does not influence the probability of abandonment in a neighborhood of interest. However, the levels of market conditions and gentrification in surrounding neighborhoods do influence the probability. Finally, it considers whether the variable effects generalize between the two cities of interest. Adding interaction terms to the multilevel regression model showed that the effects of neighborhood level abandonment and gentrification were the same for both cities, while the effects of market conditions and physical neglect were stronger for Columbus. All of the lagged variable effects generalize, meaning that the effect of surrounding neighborhood conditions on the probability of abandonment is the same for Youngstown as it is for Columbus. Conclusion: Instead of thinking about housing abandonment in terms of a large number of variables, policy makers can conceptualize it as consisting of a smaller number of constructs. Factor scores, clusters of abandonment, and predicted probabilities can be mapped to suggest where to invest. The final regression model provides guidance for how to spend scarce recourses as well. It suggests that policy makers should enact strategies that decrease physical neglect in the neighborhood itself, and increase housing demand both in the neighborhood and in surrounding neighborhoods. Prevention of abandonment is likely the best strategy for dealing with the problem; and while more research is necessary to confirm, the suggestions proffered in this paper may serve to prevent abandonment. Furthermore, since most of the variables effects generalize between the two cities, it is possible that the results of this study generalize to other, similar cities as well. Advisors/Committee Members: Nasar, Jack.

Subjects: Urban Planning

Keywords: Housing Abandonment; Vacancy; Demolition; Housing Demand; Shrinking Cities

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29. Olwert, Craig Thomas. A Computable General Equilibrium Model of the City with Optimization of its Transportation Network: Impacts of Changes in Technology, Preferences, and Policy.

Degree: PhD, City and Regional Planning, 2010, Ohio State University

► This computable general equilibrium model determines the interactions of profit-maximizing firms from… (more)

Subjects: Transportation; Urban planning

Keywords: computable general equilibrium model; input-output data; zoning; urban economics

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30. Ozuduru, Burcu H. An empirical analysis of shopping center locations in Ohio.

Degree: PhD, City and Regional Planning, 2006, Ohio State University

► The shopping center system of a city or metropolitan area includes regional… (more)

▼ The shopping center system of a city or metropolitan area includes regional shopping centers, community centers, and neighborhood centers, each characterized by attributes such as size, layout, goods/services offered, number/type of stores, and trade area characteristics. There is a strong relationship between trade area characteristics of a shopping center and its attributes, and the shopping center systems of cities/metro areas are based on these relationships. A thorough evaluation of the trade area characteristics helps developers select the best sites for shopping centers and public officials make appropriate commercial zoning decisions. These characteristics can be proxied by demographic and socioeconomic characteristics, housing patterns, and the nature of retail competition in the trade areas. The purpose of this research is to empirically analyze the relationships between shopping center attributes and trade area characteristics, and to measure the level of geographic interdependence among consumers and shopping centers across counties and zip code areas in the state of Ohio. Two statistical techniques are used for these analyses: 1) Standard OLS Multiple Regression, 2) 2SLS Simultaneous Equations Estimation. The conceptual framework is based on Oppenheim’s retail allocation model. A large database is assembled using proprietary databases, such as Directory of Major Malls, National Research Bureau, and Demographics U.S.A., and public databases, such as Census of Population and Housing and County Business Patterns. The research finds strong relationships between shopping center attributes, proxied by shopping center size, and trade area characteristics, proxied by population, income, age groups, ethnicity, etc. In addition, the research uncovers various levels of geographical interdependence across shopping centers and consumers, pointing to the nature of retail competition in a shopping center system. The level of interdependence is higher at smaller geographical units, which generally constitute the primary trade areas of shopping centers. These results can be used by decision makers and developers for commercial zoning policy, and for shopping center site selection. Advisors/Committee Members: Guldmann, Burcu H.

Subjects: Urban and Regional Planning

Keywords: shopping centers; retail location; trade area characteristics; geographical interdependence; retail demand; retail supply

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