The federal government is a rich source of data for GIS projects and spatial analysis, with websites and portals such as The National Map, the USDA’s Geospatial Data Gateway, and geospatial data within Data.gov and the GeoPlatform. In this occasional series, we will explore online sources whose data sets are lesser-known. We begin with the U.S. Department of Housing and Urban Development.
Before we begin, however, let me make an observation or two about the (bloated) world of data today. Being a skilled and savvy data connoisseur is more important now than ever. The exponential growth of the quantity and diversity of variables means that subtle differences in data set versions can be wholly different products. This makes it super challenging to be a casual accessor or user of data. In reality, knowing that what you choose is the best fit — that the data are what you think they are, that it’s possible to understand what was really measured, and that they are current and complete — involves trust and careful scrutiny.
Now, back to HUD. Primary audiences for HUD data include planners, community organizations, developers, local and municipal governments, and social service agencies. The primary source of geospatial data sets is their HUD-eGIS Open Data Storefront whose collections can be explored through categories. This is where the majority of indices can be accessed as well. An index — a blend of several variables whose combination has been designed to reflect some synergistic information-of-interest from its individual input variables AND allows for comparisons because it’s been standardized — has the potential to be meaningless or super helpful and everywhere in between, but it can’t be improved upon until it’s used and better understood.
HUD’s Jobs Proximity Index builds from the census’s Longitudinal Employer-Household Dynamics data. Knowing the distances that people commute from their neighborhoods to their job sites helps to explain numerous factors about workers’ attendance, job satisfaction, and quality of life. Standardizing this into an index aides in analyzing trends and opportunities and necessarily involves making some data generalizations. Neighborhoods are designated by centroids of census block groups, and the statistic is derived from a gravity model that assumes straight-line distances to places where employers are based, with weighting on areas with more employers. The index values range from 0 to 100 with higher values meaning greater access to employment opportunities for those neighborhoods’ residents.
The Environmental Health Hazard Index also uses block group neighborhoods to provide a sense of local residential exposure to environmental toxins. The EPA’s 2014 National Air Toxics Assessment data is the current source for air pollutants, and these are provided at the census tract level (even though the NATA advises against the values at areas smaller than counties or states without additional data or studies).
The Location Affordability Index v 2.0 is designed to provide a sense of general affordability for neighborhoods based on standardized household housing and transportation cost estimates. As HUD says in its overview, “What is affordable is different for everyone; users can choose among eight household profiles — which vary by household income, size, and number of commuters — and see the impact of the built environment on affordability in a given neighborhood location while holding household demographics constant.” An updated version of the LAI data, (version 3.0), was produced in spring 2019 but its display version is currently working only sporadically.
All three of these indices and many other data sets use an Esri ArcGIS Online map to allow users to visualize the patterns at their scale of choice, and zooming serves to filter the downloadable raw data to the current display. Full and filtered datasets can be downloaded in multiple formats, including spreadsheets, KML and shapefiles, and file geodatabases for the full versions.
These and many other HUD datasets are intended to help support the anti-discriminatory provisions of the 1968 Fair Housing Act. HUD’s Affirmatively Furthering Fair Housing program has data and a mapping application designed to help local governments, public housing agencies, and jurisdictions within states assess their conditions.
If you’re someone who wants or needs to work with HUD data in its tabular form to enable more effective machine reading, a laundry list of collections is available on one of its main data pages. Other places where value-added data sets are available include their Housing program, where Multifamily data is available, for example. Some but not all of these are also available in their open data storefront. Even there, data comes with the warning that, “While not all records are able to be geocoded and mapped, we are continuously working to improve the address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD.”
This is sound advice, regardless of the source of the data!