This dissertation examines how racialized urban structure is organized by two interrelated features---edges (sharp spatial transitions in racialized group composition) and flows (movement of people)---and how those features vary across time and urban space. Across three empirical chapters, it combines de‑identified mobile-phone tracking data and Census data to analyze racial segregation dynamics (flows), the alignment between movement-cluster boundaries and racialilzed group edges (edges ↔ flows), and tract‑level associations between childhood exposure to racialilzed group edges and adult income (edges → life chances). Chapter 2 (“Daily Dynamics of Urban Racial Segregation in the United States”) uses mobile-phone tracking data and Census demographics in 18 U.S. commuting zones (CZs), estimating dynamic racial segregation hour‑by‑hour and compares it to a residential baseline computed from inferred home locations. Dynamic racial segregation frequently falls below residential levels: in every CZ except St. Louis, the minimum hourly estimate is under one‑half of the residential baseline; in 13 of 18 CZs, even the maximum hourly estimate remains below the residential level. Hourly patterns are systematic: racial segregation is lowest 8–11 a.m. and highest 10 p.m.–1 a.m. Weekends are generally more segregated than weekdays, but Friday and Saturday evenings are the least segregated evening hours in the panel. Together, these results indicate strong temporal regularities consistent with compelled mobility, social isolation, and cosmopolitan theoretical perspectives. Chapter 3 (“The Relationship Between Spatial Racial Structure and Movement Patterns Across U.S. Cities") analyzes whether movement cluster boundaries coincide with racialized edges across the 100 most populous CZs. It constructs block‑group origin–destination networks from 95.4 million mobile-phone tracking observations ($\approx 5.7$ million devices), then identifies “movement communities” with the Leiden algorithm. Running Leiden 100 times and recording how often a block group lies on a movement community border yields a movement‑boundary propensity measure. Local spatial gradients in racialized group density (composite and group‑specific) are computed from 2020 Decennial Census block‑group data. The analysis finds that Black spatial gradients show the strongest and most pervasive alignment with movement boundaries (significant positive association in 51 of 100 CZs), while patterns for White, Hispanic, and Asian gradients are mixed. A cross‑CZ meta‑analysis indicates that alignment strengthens as residential segregation increases. Overall, the analysis suggests there is a relationship between the organization of racialized groups in urban space and how people collectively navigate urban space. Chapter 4 (“Assessing the Neighborhood-Level Association Between Childhood Racial Boundaries and Adult Income”) investigates the neighborhood-level relationship between growing up near sharp racial boundaries (edges) and average income in adulthood. It uses tract-level racial demographic gradients from the 1990 Decennial Census linked to federal tax income data from Opportunity Insights for the 1978–1983 birth cohort in the 50 most populous U.S. commuting zones. The analysis reveals modest but statistically detectable associations: specifically, tracts with more pronounced nearby racial “edges” tend to have slightly lower average adult incomes among Black residents and slightly higher averages among White residents