ArcGIS Online, Redlining and Population Density

 




I would like to sincerely apologize for my image quality, my laptop is not happy with me after this long day of classes and mapping. I decided to look into the redlining zones of Columbia as compared to the population density (on the Block level) from the 2010 census. In this map, each dot represents about 2 individuals in the area. Looking at this map, a pattern becomes clear, in the red and yellow areas of the redlining map, the highest population densities from 2010 can be found. Notice these are also close to the city center.

This can possibly investigate a few questions. For instance, why/how did it progress that the lowest quality/most hazardous places to live have become the densest over time? Is the reason these places are hazardous because of the high density of residents? What impact does the University of South Carolina play in changing the values of the redlining areas since there are not any residents to count towards population density on the grounds of campus?

I like this map for its simplicity, but I do think that it is a little hard to read. I played with the colors for about a half hour, but I couldn't find what worked the best for readability. This map also doesn't show the differences in household densities/numbers, or how many households are in each area, just the number of people. Since it is such a simple map, though interpretation is easy and straightforward, a lot of information if left to be assumed.

This evidence could help support a historical argument on population density in cities and its impact on quality of life and conditions of housing. Since these occur over time, the densities could suggest a continuation of trends from when the original redlining data was collected. Knowing the change over time is important to understanding cause and effect (or correlation) between the two data sets.

I think that other census years and their population densities could add to the map, changing from layer to layer between census years might show a continuation or a change in distribution. Along with this, if a population density is available from before the redlining map, that could be really helpful as well. I also would like to show on the map the difference in race distribution over the years, this may help to add to the picture of who makes up the population of each tract.

Since the two data sets match up well and a higher population density is set in the city center where the New Deal redlining shows the most hazardous conditions, a possible connection can be found between number of people in the area and the quality of living there.

Comments

  1. Jake FloydAugust 30, 2024 at 1:26 PM

    Hi Rachel! This is really interesting, I like the overlaying of the two different data types. I will agree, it isn't the easiest thing to read, but the message is certainly there, and it's fascinating. Particularly, your question about the causation intrigued me. Doing research into if the population density caused the hazard, or vice versa, or potentially both were caused by something else would be a great direction to go with this map. Great job!

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  2. O'Malley JenkinsSeptember 1, 2024 at 1:07 PM

    I really like the choice to analyze population density as compared to the redlining data. In regards to this, I think you also did a great job of explaining the difficulty in determining whether higher population density causes decreased living conditions or vice versa. Nice work!

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