How can we quantify the quality and authenticity of our urban spaces?

We developed a framework for evaluating the myriad factors that contribute to successful urban environments. It combines quantitative data—walking distance to open space, access to transit, for example—with qualitative input, such as comfort, culture, or design quality. Quantitative data is sourced from existing websites, apps, ranking indexes, and third-party research projects focused on evaluation of vibrant, successful urban environments. Qualitative data is gathered via a proprietary site survey designed by our team to capture the experiential aspects of the environment via community group, user, and designer input.

As publicly accessible data is becoming more widely available, there has been an increase in attempts to measure and compare the success of cities, neighborhoods, and other subsets of urban space. Many of these initiatives are limited, however, by focusing on one aspect of the urban experience, such as pedestrian safety at intersections or traffic congestion. Only a handful attempt to identify the overall quality of place, at the neighborhood and site scale. This proves particularly challenging as both quantitative data and qualitative input are needed to truly measure urban experience.

We propose a framework that measures the success of urban areas across five different categories identified through our review of existing ratings and measurement systems: ambient comfort, amenities, built form, mobility, and safety. Quantitative data is pulled in a systematic manner via a set of vetted sources to ensure consistency across projects, paired with general demographic information for each site to give a larger context to the data. Qualitative data is then gathered in the same five categories via our team’s survey and observational work, the combination of which allows for more direct conclusions to be made in each of these areas.

Our framework is designed to work in three different capacities: first as a tool to assist Gensler’s clients and developers during their site selection process; second, as a way to organize the site analysis process, typically during the early stages of planning; and third, as a tool for performing post-occupancy analyses for clients seeking to understand the impact of urban interventions or considering the repositioning of existing assets. We also developed an instructional guide to support the adoption of this framework in the planning and design of buildings and public spaces.

Big data is an important tool, but so is individual perspective. Early in our process, we explored the potential of collecting qualitative data from publicly available databases such as Yelp! or Trip Advisor. However, without a full understanding of what was influencing the data, such as the time of day the entry was made or the users’ familiarity with the location, this data proved to be more anecdotal than demonstrable. The survey we developed to capture experiential aspects of place seeks to capture this data instead.

Scoring systems are not finite. Uniform ranking systems could not adequately consider the unique characteristics of the environments being scored. To capture these subjective considerations, we instead document each category of quantitative data against the qualitative feedback for each site. For post-occupancy projects, this allows property owners or developers to identify specific areas of improvement and establish design goals relative to each.

One public space does not fit all. There is no universal ideal when it comes to creating public space. For instance, maximizing access to sunlight is desirable with the cool temperatures and tall buildings in Chicago’s Loop area, while shade is at a premium during hot days in Los Angeles’ Pershing Square. Our framework layers the diverse cultural and social uses of public spaces across the world into its considerations.

After initial testing, we now seek to deploy our system more widely and gather aggregate information for deeper analysis. This would allow us to identify correlations between specific physical aspects of space and user perceptions of these places, and test our assumptions or existing tenets of design against real-world data. For instance, our inclination as designers may tell us that 15-foot-wide sidewalks are appropriate for a business district, but feedback from the experiential survey may tell us this would not accommodate actual foot traffic at a particular site.