Comparing spatial metrics that quantify urban form

• Compares eighteen urban form metrics for 542 neighborhoods in Salt Lake County, Utah.
• Linear regression and correlation analysis across time periods to assess each metric’s ability to characterize urban form.
• We make recommendations about thirteen spatial metrics for planners and policy analysts.
• This case study shows despite policy efforts to encourage smart growth, urban sprawl occurred.

Measuring and characterizing urban form is an important task for planners and policy analysts. This paper compares eighteen metrics of urban form for 542 neighborhoods in Salt Lake County, Utah. The comparison was made in the context of characterizing three neighborhood types from different time periods: pre-suburban (1891–1944), suburban (1945–1990), and late-suburban (1990–2007). We used correlation analysis, within and across time periods, to assess each metric’s ability to uniquely characterize urban form; and we used linear regression to assess the ability to distinguish neighborhood type. Three of the metrics show redundancy and two did not capture differences in urban form for the case study. Based on our findings, we recommend thirteen of the eighteen metrics for planners and policy analysts who want to quantify urban form using spatial data that are commonly available. Furthermore, our case study shows that despite policy efforts to encourage “smart growth,” urban neighborhoods in Salt Lake County continue to exhibit characteristics of “sprawl.” These findings suggest the effectiveness of smart growth policies in Salt Lake County have had limited effect.

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