Our data decisions revolve around accessibility and explainability. We tried to get our primary sources from trustworthy organizations—the city of Oakland—first hand accounts and blog reports because it ensures its credibility and makes sure that we have a wide variety of perspectives when it comes to writing the impact of redlining on the residents. In addition, we are aware of the harmful language used in some of the sources, namely the HOLC taxonomy for classification reports found in the University of Richmond’s Mapping Inequality. It is critical that we acknowledge this and make sure that we do not include this type of language in our popup descriptions so as to not intentionally offend anyone or subjugate anyone to the HOLC’s foregrounding of racist intent in their “community” betterment. 

The data we chose to include in our visualization is information on the major infrastructure that have deeply impacted the West Oakland community and made sure we included information from Opportunity Insights Atlas to show the impact of redlining and infrastructure on the community in present times. When creating the designs for our visualizations, we wanted to make it eye-catching to attract the attention of the audience and also have a clear distinction on the parts of the map as well. Therefore, we used different icons and different colors to represent the different infrastructures and housing areas as well.  

This map layers (1) the density of children (ages < 18) from low-income households in 2000, by race, per km²; (2) the mean adult-income percentile those same children later achieved in 2014-2015; (3) a Shannon diversity score measuring how evenly the three racial groups share that low-income child population; (4) the race holding >50 % of such children in each tract; (5) 1939 HOLC lending grades (A–D) that codified redlining; and (6) the 2024 TIGER/Line road network for orientation. Together, the layers trace how historic segregation maps onto the childhood geography and later economic mobility of disadvantaged Detroiters.

The purpose of this map is to recognize the long-lasting effects of redlining on Detroit's housing system. The 1939 HOLC map, from Mapping Inequality, layered with information from the Opportunity Insights Atlas, shows how the inception of these maps led to the perpetuation of spatial segregation despite the Fair Housing Act (FHA) and other government-sponsored attempts to rectify the inequalities cemented by redlining. The different colors on the map are taken from the HOLC map to remain accurate with the geo-coding done by the corporation, and the rest of the coloring displays how darker saturation correlates with higher statistics. We are aware and want to highlight that the language used by the HOLC is racially motivated and that the data from the Atlas may be skewed due to self-reporting but by staying consistent in these metrics we offer a pipeline from the racially-charged redlining maps to current events that are trackable across our three case studies by using the same data. In addition, the inclusion of roads, although not directly studied in Detroit, is for comparison with Oakland and New Orleans in case future researchers want to focus on how redlining impacted transportation. 

Source Code: https://github.com/josephpark2five/DIGHUM100/tree/main

The base map depicts the city of New Orleans. The original areas outlined in the HOLC redlining maps are outlined in their respective colors on the “HOLC 1939” layer. There are several other toggleable layers as well, such as density of white, Black, and Hispanic residents, the incarceration rate, the proportions of residents who stayed in the same area as their parents, and each tract’s household income. These layers are colored using a gradient corresponding to a colorbar in the corner of the map — darker colors correspond to higher values.

We chose to layer this demographic data derived from the Opportunity Atlas census data over the original HOLC redlining data because we wanted to emphasize how these redlining decisions made a century ago have hampered the upwards mobility of communities of color in New Orleans. Particularly, we needed to understand historical displacement and societal instability within the city. We kept the original colors from the HOLC redlining maps to maintain consistency, but we want to emphasize that the original HOLC criteria for dividing up neighborhoods was based on racist assumptions and a biased point of view. Nevertheless, as demonstrated by the demographic data from Opportunity Atlas, these divisions have persisted in these communities.  

Source Code: https://github.com/amithvasantha-cal/DIGHUM100