The Smart Location Database: A Nationwide Data Resource Characterizing the Built Environment and Destination Accessibility at the Neighborhood Scale

AbstractA large body of research has demonstrated that land use and urban form can have a measurable effect on the daily transportation habits of urban and suburban residents. These findings can help to inform travel demand studies and evaluations of the likely effects of land use decisions on residents' transportation choices and costs. Developing reliable data can be expensive and time consuming, however. The goal of the U.S. Environmental Protection Agency's Smart Location Database (SLD) is to summarize relevant built environment and destination accessibility variables for every census block group in the nation and to share them publicly in support of planning and research studies nationwide. This article describes the variables available in the SLD and the novel approaches we developed to calculate these variables using available private and public data sources. Of particular note are several measures of accessibility to destinations via transit developed through an analysis of more than 220 public transit data feeds available from agencies across the United States. The article concludes with a case study describing one current use of the SLD: evaluating potential employment facility locations.IntroductionDuring the past two decades, the planning profession has seen an explosion of interest in the roles that land use and urban design play in shaping the transportation habits, health, and livelihood of urban and suburban residents. Researchers in the fields of transportation planning and public health have begun to isolate and measure the relationships between the built environment in which we live and work and our propensity to choose walking, transit, or driving to meet our everyday transportation needs. These studies tend to focus on neighborhood characteristics such as the density of development, mixing of land uses, connectivity of street networks, availability of transit, and accessibility to destinations via car, transit, or foot. A 2010 meta-analysis of this literature reviewed more than 200 different studies (Ewing and Cervero, 2010). Findings from this body of research are being used to inform traffic impact analyses (Ewing et al., 2011; Gulden, Goates, and Ewing, 2013), land use scenario-planning studies (Bartholomew and Ewing, 2008), environmental impact analyses (Ramsey and Poresky, 2013), health impact assessments (de Nazelle et al., 2011), and estimates of transportation cost burdens associated with living in a particular place (Haas et al., 2008). These kinds of studies enable planners and community advocates to quantify the potential benefits of local land use decisions such as encouraging compact and mixed-use development, allowing for more jobs and housing to be in walkable and transit-rich neighborhoods, and reducing the amount of new low-density development occurring at the outer suburban fringe.Developing data that summarize built environment characteristics unfortunately can be expensive and time consuming. Moreover, each time a new community wants to conduct a planning study, the same general kinds of data must be identified, gathered, and processed. We wondered, therefore, if an economy of scale could be achieved by developing data about the built environment at the block group scale for the entire United States. These data would necessarily rely on national sources or widely used data standards. Therefore, the results could be inferior to locally derived metrics that rely on detailed land use data available only at the local scale. We hypothesized, however, that a nationwide study could produce data that are sufficient for many local and regional studies that would not otherwise move forward because they lack resources. We also hypothesized that making nationally consistent data freely available could spur the development of third party planning analysis tools that significantly reduce barriers to entry for communities seeking to analyze the potential effects of land use decisions. …