Click here for our open-access peer-reviewed paper in the journal Cities and the Environment, the first of several leveraging the typology, and here for the technical report detailing the methods used to produce this classification of neighborhoods in the Greater Salt Lake City metropolitan area.

As part of a multi-year large-team research project named iUTAH, I and collaborators developed a typology or classification of neighborhoods in the ten-county region centered on the Salt Lake City metro region. This region houses more than 80% of Utah’s population. Within this region we limited the study footprint to the 1350 census block groups (CBGs) in the greater Wasatch Front and Back that could be considered urban or urbanizing, which we defined for this study as all CBGs with a population density of 100 persons or more in the 2010 decennial census, after netting out areas of water and Federally-owned land where urban development is impossible or unlikely.

Working from data sources including the US Census Bureau, State agencies, Landsat imagery, and municipal water providers, we collected data describing our study area from the perspective of eight major dimensions:

• Land cover
• Land use
• Biophysical context/microclimate
• Built environment
• Housing stock
• Households
• Individuals
• Public water systems

We then ordinated this high-dimensional (n=47 variables) dataset via factor analysis to derive eight uncorrelated latent dimensions that explained more than three quarters of the variation in the original data. We interpreted the factors via analysis of the factor loadings and geographic distribution of factor scores, and describe the factors in descending order of explanatory power:

We took the results of the factor analysis and applied them as inputs to a hierarchical cluster analysis to define groups or types of neighborhoods.

Along with collaborators Doug Jackson-Smith and Philip Stoker, I contributed to the research design and interpretation of factor analysis and cluster analysis results, and co-wrote manuscripts resulting from our study. I processed satellite imagery and vector data inputs, and designed and produced all cartographic design outputs associated with the project. This project involved a significant amount of cartographic design, standardization, and associated documentation, as the research product was used as a foundational data infrastructure element for social science research in the broader iUTAH project. (For example, we used this neighborhood typology in sampling design for a large household survey of attitudes, values, and beliefs about water issues.) I also managed student research assistants doing geospatial data collection and tabulation to CBG units.