Project Narrative

Redrawing the Lines: Mapping the Legacy of Redlining in U.S. Cities

Identifying that inequality is a cyclical, generational trap begins with recognizing the impacts of history and policy on modern-day society. Redlining has significantly influenced the narrative surrounding housing. In the mid-20th century, redlining facilitated structural discrimination in lending and financial services, perpetuating the economic underdevelopment of neighborhoods designated for redlining. Much of the evidence unearthed in recent literature reveals the discriminatory reasoning behind specific risk assessments. From racist verbiage rationalizing discrimination to bigoted neighborhood classification systems, redlining activities would persist until the Fair Housing Act in 1968 officially prohibited them (Nelson et al., 2018). 

Nevertheless, legislation is often crafted from a position of privilege. Society’s infrastructure breeds inequity as it stands. New Orleans exemplifies this idea. Dr. Ari Kelman of the University of California, Davis, writes about the post-1950 urban push to mitigate New Orleans’ environmental vulnerabilities. Levees were raised, wetlands were drained, and land was reclaimed at the expense of the socioeconomically disadvantaged: “New Orleanians became stratified, with poorer people of color often concentrated on low land” (Kelman, 2005, para. 10). This redevelopment effort was not neutral but a residual impact of redlining on the city. 

This leads us to our research question: How has redlining evolved from a historical housing policy into an interconnected system of inequality, and how can a temporal narrative illustrate its long-term consequences? Divergent outcomes persist within metropolitan areas, underscoring the gaps that redlining has created. Through an extensive literature review, we identified three cities—Oakland, New Orleans, and Detroit—in which certain notable events highlighted the consequences of redlining. Our objective is twofold: to map the relationships between redlining and neighborhood-level economic outcomes and to uncover veiled narratives connecting redlining with deep-rooted infrastructural inequities.

Throughout history, cities have evolved, and maps have changed, but the original intent remains. In the 1930s, the federal government etched inequality into paper through the Home Owners’ Loan Corporation (HOLC) maps, which categorized Black and immigrant neighborhoods as “hazardous.” It encased them in red lines, deeming them unworthy of investment and care (Nelson et al., 2018). These maps are not static; they are blueprints for exclusion that have evolved, mutated, and embedded into every layer of city life. Across decades, the inhumane boundaries seeped into concrete policy, shaping the very streets and highways of Oakland, Detroit, and New Orleans. Red zones did not merely mark these cities; they shaped them. 

In Oakland, postwar “urban renewal” became a tool to dismantle Black economic prosperity. The development of Interstate 980 and the West Oakland BART station divided thriving communities, splitting them in half and leading to disinvestment in them (Self, 2003, pp. 255–260). In Detroit, HOLC determinations fueled white flight and suburbanization, while redlined neighborhoods were denied mortgages and forced into predatory loans. They produced a dual-tier housing system that undermined housing stability and scapegoated Black Detroiters for urban decline (Sugrue, 2005, p. 37). In New Orleans, the legacy of redlining became an environmental disaster. Laura Pulido highlights how environmental racism includes development decisions regarding land use that benefit a white majority (Pulido, 2016, p. 7). This translates into why New Orleans neighborhoods with failing levees had higher minority populations. These cities exemplify the various avenues of inequality in contemporary society. 

The Fair Housing Act of 1968 was a vision that outlawed explicit red zones but did not dismantle the systems it created. Our project continues where redlining was presumed to end, displaying how inequality mutated to credit scores that replaced racial covenants, environmental racism relocating blame, and highways cementing racism into the streets of the “hazardous.” These inequalities persist in neighborhoods, targeting the same communities and perpetuating the same systems that determine which areas are of lower value. Thus, we argue that redlining was not undone but repaved. Redlining and its afterlife are the timelines our project traces. The red zones may be formally removed from maps, but their effects have solidified into a cartography of exclusion in which some futures remain disposable.

By overlaying the HOLC redlining maps with modern census data, our data visualizations illustrate how the historical racial prejudice stemming from redlining continues to deny these communities opportunities to improve their upward mobility. Using data from the U.S. Census’ Opportunity Insights dataset, we analyze trends in metrics such as job growth rate, median household income, and job density to demonstrate how formerly redlined neighborhoods continue to experience limited upward mobility. These spatially determined inequalities became transportation infrastructure, lending practices, and environmental racism, all of which reinforced geographic and racial segregation.

Structural racism did not die; it adapted. In Oakland, we witnessed how transportation routes fractured Black communities. In Detroit, lending inequalities drove hundreds of thousands of foreclosures. In New Orleans, environmental injustice relegated minorities to high-risk areas. Accordingly, we conclude that the observed reinforcement of redlining has been sustained by similar policy inequities across all three cities. Policymaking often favors affluence and deprioritizes minorities, which embeds biases into urban development, creating sinkholes through invisible forces for these communities. Until minorities gain stronger representation in development policies, urbanization will continue to be a contradictory force to their success.

Our methodology draws from the seven principles of Data Feminism as summarized in Yasamin Rezai’s “Data Stories for/from All: Why Data Feminism Is for Everyone,” the transparency framework offered by Boyd Davis, Vane, and Kräutli, and Faithe Day’s insistence for Black Digital Humanities to govern racialized politics (Boyd Davis et al., 2019; Day, 2024; Rezai, 2022). 

To examine and challenge power, we reveal the 1930s Home Owners’ Loan Corporation security maps as racial technologies through their marking of Black and immigrant neighborhoods as “hazardous”, foreshadowing the modern inequalities we trace to Oakland, Detroit, and New Orleans (Nelson et al., 2018). The redefinition of the maps as racially motivated also allows us to negate the belief that the Fair Housing Act reversed all harms. We redefine data that drove inequality by quantifying the extent to which modern-day redlining events overlap with areas that were historically redlined, with the chosen inequality for each city. 

To elevate emotion and embodiment, we draw inspiration from the Mapping Inequality project, which integrates digitized redlining maps with neighborhood descriptors and demographics (Nelson et al., 2018). By incorporating personal stories into spatial data, the project humanizes a process that is often reduced to zoning or finance. To rethink binaries and hierarchies, we reject HOLC’s A/B/C/D categorization, which employs a continuous gradient of harm, and instead recognize that marginalization exists on a spectrum, subjected to multiple layers of infrastructural violence. This aligns with Faithe Day’s emphasis on acknowledging complexity and resisting oversimplification (Day, 2024). To embrace pluralism, we integrate community narratives, local reports, and statistical data to offer diverse perspectives. This ensures that, instead of merely describing the affected populations, we include them in the work that is created. 

To consider context, we draw on Boyd Davis et al.’s reminder that humanistic data are subjective and sometimes untrustworthy. Thus, we explicitly state our limitations, including those related to data availability, differences between HOLC and modern map boundaries, and the specific manner in which we utilize the maps (Boyd Davis et al., 2019). To make labor visible, we maintain a public research log that documents assumptions, decisions, and discarded avenues from the exploration process. Citations list community sources, activist archives, and open-source contributors alongside student analysts, underscoring that DH projects are always collaborative efforts.

To substantiate our methods, we now discuss the tools that will be used and explain their rationale. ArcGIS allows us to visualize the historical and contemporary patterns of redlining. In particular, we overlay the HOLC classifications onto modern urban maps of our selected cities, much like the Mapping Inequality project, which includes Oakland, Detroit, and New Orleans, to understand the impacts of redlining policies resulting from infrastructural changes, such as transportation projects, and post-natural disaster recovery efforts. ArcGIS also includes spatial functions that allow us to identify these overlaps and embed case-specific annotated narratives, pop-ups, and filters onto the maps. Additionally, we intend to utilize temporal mapping to illustrate how urban development has evolved, comparing historically redlined zones with the current quality of life, environmental risk, and health data. Therefore, these tools will not create any bias with the data as well, “The importance of letting the data speak for itself was stressed (Mayer-Schönberger & Cukier, 2013).” (Prescott, 2023, para. 7). 

Kepler.gl renders large geotagged datasets with scathing clarity and efficiency. Our workflow with this tool is as follows: scrape data from the Opportunity Insights Datasets, which encompass household income mobility, job densities, and incarceration rates, process it, and visualize salient and nuanced trends in these indicators across different geographies. By integrating Kepler.gl’s layered animations with ArcGIS’s annotated historical narrative, we display the legacy of redlining through dynamic, accessible representations while ensuring accessibility. 

To accurately represent the nuances of redlining as a spatiotemporal complex, we have created an interactive timeline using TimelineJS. It serves as a chronological narrative that complements other visualizations and textual analysis, threading key urban policy shifts, transportation, and general infrastructure projects, and post-disaster recovery efforts across our selected cities. This contextualizes redlining within the century of urban planning, elucidating how different forms of inequality, such as transportation development in Oakland, are entangled within the harmful legacy of redlining. We move beyond the subversive notion that redlining is a closed-form definition and frame it as a causal system that continues to unfold. 

These tools focus on adopting Davis, Vane, and Kräutli’s ethical visualization and Rezai’s data feminism. The use of Kepler.gl was inspired by Hepworth and Church’s Racial Terror Lynching Map example. By grounding our analysis in these principles, we present visualizations as layered narratives that convey a deeper understanding of the data. In addition, through Hepworth and Church’s reading, “the goal of this visualization ethics should be ‘increasing understanding [for users] while minimizing harm’ to represent people and places (Cairo, 2014).” (Hepworth & Church, 2023, para. 6). This quote further emphasizes the importance of ethical visualization, allowing us to be mindful when using these digital tools and how the visualizations we create could impact the way the audience interprets the data. However, we believe that this further underscores the value of digital tools for our project. Although it can be further argued that “There is no neutral visualization: the intention [is] based on a shared understanding of the objectives” (Boyd Davis et al., 2021, para. 35), which allows some interpretations to be preferred over others; therefore, it is essential to keep in mind when creating our visualizations to have a balanced argument. Consequently, it is evident the importance of these digital tools in our project. 

In conclusion, the income and privilege gap is inexorably fracturing American metropolitan areas into microcosms. In this divisive climate, key perpetrators of these gaps are especially crucial to analyze. Redlining, despite its ban some time ago, has left a wake of destruction etched into urban policies and infrastructure that shape our cities today. Through transportation improvement and disinvestment patterns, we can see how they mirror the red lines drawn arbitrarily by the HOLC nearly a century ago, marking the persistence of structural inequality across the contiguous United States. Through tools like ArcGIS and datasets from Opportunity Insights, we uncover hidden consequences through a sociodemographic lens by creating an engaging, ethical, and unbiased collection of maps and descriptions that illustrate how the effects of redlining have persisted to this day.

There is a clear call for action. Policymakers should amend state Community Reinvestment Act rules to prioritize infrastructure upgrades in historically redlined census tracts. Community organizations can utilize our map layers to advocate for more equitable transportation and lending policies with city councils. Furthermore, we encourage fellow practitioners of Digital Humanities to replicate this analysis in additional cities and to test how other modern events, such as credit-scoring algorithms, support or disrupt the observed patterns. Likewise, anyone can explore the interactive layers of our project and draw meaningful insights. 

We understand that visualizations, especially those related to inequality, are never neutral, despite our good intentions. As creators, building a revealing and engaging narrative is akin to playing God, selecting and arranging elements to imbue a specific meaning. However, this illusion of control obscures the very voices that need to reach us—people who live in seclusion can be visually represented, but can be overshadowed by overcomplexity and clutter. Redlining is far from being closed; it is constantly evolving. With these insights, we can reform our cities, not with lines of exclusion, but with constructions that support inclusivity, making legible what has been shrouded over the years.