Quantifying Transit’s Impact on GHG Emissions and Energy Use—The Land Use Component (2015)

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11 S E C T I O N 3 Statistical modeling was used in this research to quantify the land use effect of transit. Using statistical models allowed the research team to isolate particular transit variables that determine the land use effect (such as transit supply and frequency), while controlling for other factors that are correlated with urban land use patterns (such as urban area popula- tion size and road supply). Two different datasets were used to conduct statistical analyses at different scales: • The urbanized area dataset, which contains data at a macro scale on more than 300 federal-aid urbanized areas, with boundaries defined by the FHWA. Data incorporated include urbanized area size in square miles, demographic characteristics such as population size and average income, transit variables such as route miles by mode and transit revenue miles, and control variables such as local fuel prices. Each variable in this dataset is a single aggregate value for the urbanized area. Data are from the year 2010. • The neighborhood dataset, which contains data at a micro scale for nine diverse regions in the United States (using Metropolitan Planning Organization–defined boundaries): Austin, Texas; Boston, Massachusetts; Eugene, Oregon; Houston, Texas; Kansas City (Missouri and Kansas); Portland, Oregon; Sacramento, California; Salt Lake City, Utah; and Seattle, Wash- ington. Data incorporated include land use variables such as urban density and level of land use mixing, demographic variables such as household size, transit variables such as availability of a rail station, and data on household travel behavior including driving (VMT) and transit use (passenger miles traveled). Most variables in the dataset are calculated as averages within a small area: approximately 1⁄4 mile squared. Data are from different years, ranging from 1991 to 2011, depending on the region. The urbanized area dataset was used to conduct a cross-sectional analysis to examine differ- ences in travel behavior between urbanized regions that have experienced different levels and types of transit investment. The urbanized area models enable the research team to answer the following research questions: • What is the total land use effect of an urban area’s existing transit system? • What is the likely additional land use effect within the urban area of incremental improve- ments in the transit system? The neighborhood dataset was used to model the land use effect of transit at a finer scale. Whereas the urban area model was constructed by comparing whole regions to one another, the neighborhood model incorporates small scale variations in land use patterns and travel pat- terns and includes both population and employment densities. It also explicitly considers more land use characteristics: land use mixing, pedestrian environment, and job accessibility. The Research Methodology

12 Quantifying Transit’s Impact on GHG Emissions and Energy Use—The Land Use Component neighborhood dataset allows the research team to compare the characteristics of transit-rich neighborhoods to those of transit-poor neighborhoods within regions in order to study the land use effect. The neighborhood dataset was also used to conduct a longitudinal analysis of observed land use changes in Portland, Oregon, between 1994 and 2011, in order to compare results with the cross-sectional analyses. Additional details on the statistical models are provided in Appendices A and B.