This is a full-stack web app that uses MapBox GL to visualize and search redlining maps produced by the Home Owner's Loan Corporation (HOLC). In the early 20th century, HOLC scored America's urban neighborhoods and systematically denied lending to Black, Jewish, and immigrant Americans. Redlining reinforced the degree and physical scale of racial segregation and discouraged investment in non-white neighborhoods, which caused decades of compounding, racialized inequalities in wealth and access to food, healthcare, education, employment, transportation, and housing that persist today. In the map of Providence below, notice how I-95, I-195, and RI-146 were built through and demolished three out of four redlined neighborhoods including Cape Verdean Fox Point, historically Black Hardscrabble, and Pawtucket's School Street.
This project was developed by Michael Kearney and Lizzy Zhang for a software development class taught by Tim Nelson at Brown University in Spring 2023.
View digitized redlining maps and grades assigned by HOLC to neighborhoods. Green neighborhoods received an "A", blue ones a "B", yellow ones a "C", and red ones a "D". Search neighborhoods and click on neighborhoods to read HOLC's description.
- Create a MapBox Access Token.
- Store your token by running
echo 'export const ACCESS_TOKEN: string = "[YOUR TOKEN]"' > frontend/src/private/keys.ts
- Run Server.java in 'backend'.
- Run
npm run dev
to launch the frontend. - In your local browser, navigate to the localhost URL provided by Vite.
This project consists of a React and Typescript frontend wrapping MapBox GL served by a Java Spark backend. We modeled the GeoJSON spec in Java and used Moshi's polymorphic factories to serialize and parse the spatial data. A searcher handles requests from the frontend and caches text and bounding-box queries.