The DSL recently released its first atlas map since the launch of American Panorama in December 2015. Mapping Inequality: Redlining in the New Deal America brings to life the study of New Deal America, the federal government, housing issues, and inequality by offering complete online access to the national collection of “security maps” and area descriptions produced between 1935 and 1940 by the Home Owners’ Loan Corporation (HOLC). To read more about HOLC and the New Deal visit the Introduction.
Since this blog focuses on “all things spatial”, I wanted to touch on the massive amount of GIS work that went into creating this project. First, I would like to acknowledge all of our student interns at UofR, who spent countless hours (don’t worry we paid them) making this possible. I would also like to thank our collaborators at Virginia Tech and the University of Maryland for their contribution to the GIS efforts to make this project possible. The students learned a great deal about the process of georeferencing, digitizing, database management, and topology rules. Most of the students, prior to working at the DSL, have never worked with GIS or spatial data. Here are some stats and figures that show just how much work went into creating Mapping Inequality that a majority of people don’t know.
-Georeferencing was by far the largest task of the project. Georeferencing the cities varied significantly in time depending on the size and layout of the city. One reason we added the large number of control points, was to insure that roads lined up correctly when compared to the modern day basemap. Once rectified, they were tiled and served out to the application. Note: all of these maps are downloadable via the site.
- 166 maps
- As many as 2,147 control points in a map
- The average is 734 (per map)
- 72,024 control points (144k+ clicks)
-Vectorization of the neighborhoods– via the rectified maps– required a lot of hands on digitization work. Topology rules played a large role in insuring the quality and accuracy of the
- 7,513 polygons
- As many as 498 vertices in a polygon
- Average of 31 vertices
- 229,829 vertices (clicks)
-Data Entry (polygons) Each polygon had up to seven fields that needed to be manually entered. These fields included key attributes for the project such as HOLC grade, polygon_id, and name of the neighborhood.
- Up to seven fields for each polygon (id, grade, name, etc.)
- About 45,000 data points
-Data Entry (Area Descriptions) Entering data for the area descriptions was very slow, hence the reason we have completed only 17 cities thus far. Some cities included up to 94 fields for each neighborhood. Some fields included whole paragraphs (like the one seen below).
- Up to 94 fields per neighborhood
- So far 94,719 individual fields completed for 17 cities
- Estimated about 900,000 when completed
Overall, completing all of the GIS work stated above, took 4+ years to complete. Managing this ongoing collaborative project had its hurdles, but overall, went smoothly. Allowing students to work simultaneously and quickly resulted in 45GB+ of data in the end. We hope to work with the University of Maryland on their crowd sourcing platform to complete the remaining 150 or so area descriptions. Enjoy the project and hope you can use the data to uncover new stories and questions.
*If you are interested in learning more about the methods we used to complete this project, click on the link below and download the training manual.
Thanks to all of our great students!
Credit: Rob Nelson calculated the statistics and Nathaniel Ayers created the header photo.