Access to Destinations: Parcel Level Land Use Data Acquisition and Analysis for Measuring Non-Auto Accessibility

This research aids in tackling one important part of accessibility metrics—measuring land use. It introduces complementary strategies to effectively measure a variety of different destination types at a highly detailed scale of resolution using secondary data. The research describes ways to overcome common data hurdles and demonstrates how existing data in one metropolitan area in the U.S. – the Twin Cities of Minneapolis and St. Paul – can be exploited to aid in measuring accessibility at an extremely fine unit of analysis (i.e., the parcel). Establishment-level data containing attribute information on location, sales, employees, and industry classification was purchased from Dun & Bradstreet, Inc. The research process involved cleaning and tailoring the parcel dataset for the 7-county metro area and integrating various GIS datasets with other secondary data sources. These data were merged with parcel-level land use data from the Metropolitan Council. The establishment-level data were then recoded into destination categories using the 2 to 6-digit classifications of the North American Industry Classification System (NAICS). The development of important components of this research is illustrated with a sample application. The report concludes by describing how such data could be used in calculating more robust measures of accessibility. This was done for capturing accessibility metrics for non-auto modes such as walking and cycling.