Homelessness is a chronic problem in San Francisco, one of the richest cities in the world. The SF OpenData portal offers data on San Francisco’s homeless population, counted by supervisorial district. Using CartoDB, I mapped this data and the accompanying shapefile as a choropleth map, and then overlaid a S.F. neighborhood shapefile. We can see, for example, that areas close to Downtown S.F. have a higher concentration of homeless people than do other areas of the city.
The first installment of the multi-part 2014 Chronicle feature linked above concludes with the city’s current strategies for alleviating homelessness, including Mayor Ed Lee’s push for a “housing ladder” to help move people off the streets and into a stable housing situation. In this model, according to the article, “Homeless people need to move into supportive housing, many of those residents need to move on to public housing, and many of those residents need to move on to affordable and market-rate housing.” The idea is to help individuals move up the ladder, or at least stay on the same rung.
We can map some of these housing options, along with the count of the homeless population, and get a clearer picture of the economic character of S.F. neighborhoods. We can also see how far the homeless population in certain neighborhoods would potentially have to move if they were to succeed in climbing Mayor Lee’s housing ladder.
Here we have a choropleth map of the percentage of the housing stock that is affordable or rent stabilized, by district, with a bubble map of the homeless population, and points showing the locations of public housing properties (which I downloaded from Google Maps as a KML file and uploaded to CartoDB). While there is a large homeless population near the Downtown and South of Market neighborhoods, there are just a few public housing buildings scattered in the area, whereas in Chinatown, there are several public housing locations clustered together. In Bayview, we see a large homeless population, several public housing buildings, and a high percentage of affordable housing units in the housing stock of that area. From this information, we can infer a lower average household income as compared to other neighborhoods in the city. We also might guess that some portion of the homeless population of Bayview is made up of former residents of the neighborhood’s public and affordable housing units.