Doctor of Philosophy, The Ohio State University, 2023, Geography

Accessibility is a fundamental measure in public transportation research and policy making; it represents a user's ability to travel and reach destination afforded by a public transit service. Accessibility plays a crucial role in a public transit service's useability, a community's livability, and residents' well-being. Higher accessibility can promote modal shifts from other unsustainable transportation to public transit, which decreases the carbon and air pollution, curbs congestion, and improves social equity and public health. However, many US cities still have major gaps in public transit accessibility and reliability. The issue of inadequate public transportation accessibility and reliability also remains a grave concern for scientific and planning communities: the lack of in-depth, holistic, and reliable understanding of accessibility impedes our ability to make informed and evidence-based decisions during both the planning and operation phases. In this dissertation, I introduce a new research framework – real-time accessibility – to better understand and improve public transit systems with high-resolution real-time geospatial data. The framework utilizes real-time information to assess different dimensions of system performance of public transit services and behaviors of passengers in the systems. I investigate four empirical questions with the framework based on the Central Ohio Transit Authority (COTA) bus system in Columbus, Ohio, a low-frequency bus system in a typical mid-size car-dependent city. First, I study the impact of new dockless scooter sharing services on local public transit systems. While they can significantly improve accessibility, equity and sustainability issues such as uneven distribution, high cost, and low capacity limit the collaboration between public transit and scooters. Second, I study the unreliability of public transit systems and the unrealistic assumptions made by schedule-based and retrospective-based measures used by rese (open full item for complete abstract)

Committee: Harvey J. Miller (Advisor); Andre Carrel (Committee Member); Huyen Le (Committee Member); Ningchuan Xiao (Committee Member) Subjects: Geographic Information Science; Geography; Information Science; Sustainability; Transportation; Transportation Planning; Urban Planning

Doctor of Philosophy, University of Akron, 2020, Integrated Bioscience

The Laurentian Great Lakes system holds approximately 20% of the world's available surface freshwater while being an immense economic engine for the region. Lake Erie, one of the five North American Great Lakes is classified as highly stressed and deteriorating. Flooding and erosion issues stemming from record-high water levels, as well as excessive nutrients causing harmful algal blooms which compounds the problems. This work investigates novel ways to approach, solve, and manage some of Lake Erie's most pressing problems. First, a historical political ecology approach was used to trace the history of land use practices that transformed the Great Black Swamp into the industrialized agricultural system that the Maumee River Watershed (MRW) is today. The analysis chronicles transformations in structure and function of the MRW implicating diverse drivers such as agricultural practices, legacy nutrient reservoirs, altered landscape hydrology, and energy policy while making policy recommendations at various scales. Second, a low-cost, open-source DIY spectrophotometer was developed in order to obtain crowd-sourced data to understand nutrient loading trends throughout the watershed, particularly the MRW. Tests of this device indicate that the typically expensive hardware is not the limitation. Rather, reagent performance is the leading cause of uncertainty. Third, a social-ecological risk and vulnerability model to flooding and erosion was created for the Ohio Lake Erie shoreline by adapting established maritime coastal indices to the limnological system. The result is both a foundation for Ohio's Department of Natural Resources, Office of Coastal Management to identify scientifically-informed, place-based priority management areas for erosion and flooding, as well as a methodological roadmap to adapt the Coastal and Place Vulnerability Indices to the other Great Lakes' states and provincial shorelines.

Committee: Peter Niewiarowski (Advisor); Hunter King (Committee Member); John Huss (Committee Member); Robin Kundis Craig (Committee Member); Lance Gunderson (Committee Member) Subjects: Biochemistry; Biology; Ecology; Environmental Management; Environmental Science; Geographic Information Science; Public Policy; Sustainability; Water Resource Management

MA, University of Cincinnati, 2024, Arts and Sciences: Geography

This thesis studies the early detection of COVID-19 cases at the county level in the United States(U.S) by identifying significant clusters of reported cases in terms of both space and time. We performed a retrospective space-time scan statistical analysis to detect emerging clusters of the COVID-19 pandemic. Moreover, the proposed study has the potential to offer significant insights into the dynamics of disease spatial patterns among urban and rural communities. This understanding would allow for targeted interventions and the allocation of resources for the COVID-19 pandemic, as well as future global health challenges and emerging epidemics. Using a retrospective space-time scan statistic technique, we identified counties into high-risk, medium-risk, and low-risk categories for COVID-19 transmission. We achieved this by analyzing the incidence rates across the counties in in the U.S. from the beginning of the pandemic in late January 2020 to the end of April 2022, including of a total of 105 weeks. We systematically evaluated the incidence rates from the start of the pandemic to the 105th week, considering significant events like the first outbreak in March 2020, the relaxation of preventive measures during a later phase, the significant rise during the winter wave, and the emergence of the Delta variant's wave in September 2021. In order to test this hypothesis, we proposed a framework that implements data visualization and Geographic Information Science (GIS) to identify and categorize clusters according to the time at which they emerged during different stages of the pandemic.

Committee: Diego Cuadros Ph.D. (Committee Chair); Xi Chen Ph.D. (Committee Member); Robert South Ph.D. (Committee Member) Subjects: Geography

Doctor of Philosophy, The Ohio State University, 2022, Geography

The rise in rates of opioid overdose is a public health crisis in the United States. Retrospective studies show that the opioid overdose crisis is not homogeneously distributed across space and time, and there is increasing recognition that its etiology is rooted in part by social determinants such as poverty, environmental disadvantage, isolation, and social upheaval. It's important to understand the spatiotemporal variation in opioid overdose emergencies and its possible social and environmental determinants to guide public policy responses to the crisis as the obtained knowledge can benefit health care administration and epidemiological purposes, coupled with the need for generating reliable risk assessment for small geographical areas. This dissertation aims to develop new spatial-temporal methods and utilize new geospatial data for understanding the space-time pattern of opioid overdose events (OOEs) and associated socio-environmental factors for OOEs. This dissertation consists of three major parts: 1) Understand how OOEs evolved over space and time using a regionalized sequence alignment method; 2) Understand the social and physical environmental determinants in OOEs at high spatial-temporal resolution using found geospatial data; and 3) Use city municipal 311 service requests as indicators of neighborhood distress and predicting the trends of OOE hotspots when OOEs data is not available. The outcome of this dissertation helps us understand the critical spatiotemporal characteristics of the opioid overdose crisis and provides valuable information to identify the potential socio-economic and environmental drivers of the crisis as well as geographic areas where vulnerable populations are located, and where interventions should be implemented.

Committee: Harvey Miller (Advisor); Ayaz Hyder (Committee Member); Elisabeth Root (Committee Member); Desheng Liu (Committee Member) Subjects: Geographic Information Science; Geography; Public Health

PHD, Kent State University, 2021, College of Arts and Sciences / Department of Geography

Cancer epidemiology has a long history of applying geographic thinking to address long-standing place-based disparities. This dissertation adds new knowledge to geospatial approaches to social determinants of cancer outcomes. It establishes a framework consisting of three dimensions in evaluating, identifying, and prioritizing spatially heterogeneous risk factors of cancer outcomes. The first dimension is protection. Using a space-time statistic, the first study evaluated whether a non-spatial healthcare policy, Medicaid expansion, has offered protection targeting spatially vulnerable populations against adverse cancer outcomes such as breast cancer late-stage diagnosis. The second dimension is phenotype. Using a classification and regression tree, the study disentangled how risk factors of late-stage breast cancer diagnosis were conceptualized and capsulized as phenotypes that labeled groups of homogenous geographic areas. It provides a novel angle to uncover cancer disparities and to provide insights for cancer surveillance, prevention, and control. The third dimension is priority. Using a geographic random forest along with several validation methods, the study emphasized the importance of the competing effect among risk factors of cancer mortality that are specific to geographic areas. The findings from this study can be used directly for priority settings in addressing the most urgent issues associated with cancer mortality. This dissertation demonstrated that geographic methodologies and frameworks are useful and are imperative to cancer epidemiology.

Committee: Jay Lee (Committee Chair); Jun Li (Committee Member); James Tyner (Committee Member); Xinyue Ye (Committee Member) Subjects: Epidemiology; Geographic Information Science; Geography; Health; Health Care; Health Care Management; Oncology; Public Health; Public Policy; Statistics

Master of Arts, Miami University, 2017, History

Through textual analysis and mapping of 1790s published travel accounts, this project examines how lower class individuals utilized the growing British Empire to expand their societal status and travel opportunities. Modeled on early novels of the mid-eighteenth century such as Robinson Crusoe and Pamela, these supposedly “true” travel accounts showed their protagonists using personal connections, patronage, and employment to overcome adversity and rise socially. Individuals demonstrated mobility through their public image, dress, and speech. Passing for middle class was difficult, although often achievable through education, conduct, and finances. A publicly available interactive map in ArcGIS Online was created. It shows the routes of travel, characteristics of the travelers' social status, and quotations from the primary sources, allowing them to be compared. The interactive map was built from the travel accounts descriptions of their travels, social status, financial status, and employment through manual data entry. The map is designed to be accessible and appealing to a broad public, enlarging the audience beyond specialists in digital humanities.

Committee: Renee Baernstein Dr. (Advisor); Lindsay Schakenbach Regele Dr, (Committee Member); Robbyn Abbitt Mrs. (Committee Member) Subjects: British and Irish Literature; European History; Geographic Information Science; Geography; History; Literature