Date of Graduation

9-2025

Document Type

Thesis

Degree Name

Master of Science in Geology (MS)

Degree Level

Graduate

Department

Geosciences

Advisor/Mentor

Xiao Huang

Committee Member

Brad Peter

Third Committee Member

John Shaw

Keywords

human mobility; Inequity; machine learning; mobile phone; SafeGraph data; urban park

Abstract

Urban Park accessibility inequities have been a longstanding issue globally and the United States in particular. Despite the benefits that urban parks provide, use and access is not equitably distributed among the population, often favoring historically privileged populations over others (disadvantaged). Fortunately, improvements have been made in recent years to promote balanced park distribution in some cities; however, evidence still shows that most cities are behind. Interestingly, the rise in human mobility data has facilitated the study of human behavior and use of activity spaces. This thesis advances the existing studies on park accessibility and emerging human mobility to study park accessibility inequities in American cities in an integrated fashion. The objectives are clearly defined to analyze city-wide patterns in park visitation and empirically uncover the influence of socioeconomic and demographic factors by highlighting observed disparities that perpetuate long-term inequities in park accessibility. Additionally, the study aims to model dynamic visitation patterns, considering the evidence and trends in current accessibility. The important theoretical, methodological, and contextual knowledge gained in this study could greatly benefit decision-makers, and the recommendations are particularly useful to urban planners, city administrators and managers, and private businesses seeking to find better ways to eradicate inequities, foster balanced use/access to public parks, and promote inclusive cities for all Americans.

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