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.
Horning, Jessica; El-Geneidy, Ahmed M.; Krizek, Kevin.
Access to Destinations: Parcel Level Land Use Data Acquisition and Analysis for Measuring Non-Auto Accessibility.
Minnesota Department of Transportation.
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