Interim Report to the U.S. Congress on
the Nonmotorized Transportation Pilot Program
SAFETEA-LU Section 1807

Chapter 1: Pilot Community Characteristics

The four communities selected for participation in this pilot program exhibit a variety of demographic, economic, and transportation related characteristics. The communities differ in population and land area, but also in their existing bicycle and pedestrian networks and their organizational capacity to implement nonmotorized projects.

This chapter provides a comparative discussion of the four pilot communities, while Chapter 2 provides snapshots of each community's plans for implementation. Information for the control community -- Spokane, Washington -- provides context for comparing program impacts in 2010. The figures that appear in this chapter were created using data extracted from tables in the 2000 U.S. Decennial Census.

Table 1.1 provides an overview of the four pilot communities' characteristics, including data from the U.S. Census on existing travel behavior. Note that in some cases, a special geographic area was defined before data were extracted. Please see Table 1.1 footnotes for more information.

Documenting the communities' differences provides an excellent opportunity to better understand factors that may influence changes in travel behavior between 2006 and 2010. Nonmotorized facilities can be developed as components of an integrated multi-modal transportation system serving communities with very different demographic and physical characteristics. By documenting these characteristics in the early stages of the program, it becomes possible to discern patterns and trends in behavior change.

Source for all demographic data: 2000 U.S. Decennial Census; Source for meteorological data: University of Minnesota research team.

¹ The land area represents Marin's City-Centered Corridor, the eastern urbanized portion of the County.
² Refers only to the population density in the City-Centered Corridor.
³ Population in all Census tracts lying wholly or partially in the City-Centered Corridor
⁴ U.S. Census 1999 dollars have been converted to 2006 dollars using the U.S. Bureau of Labor Statistics Inflation Calculator (http://www.bls.gov)

The following key community characteristics provide information that may help explain the amounts of nonmotorized travel in each community:

• Population Density
• Level of Education
• Household Income
• Time Spent Commuting to Work
• Travel Mode for Commute Trip

Population Demographics and Economic Characteristics

Population density is a critical factor affecting transportation planning decisions. Dense urban areas may be well suited for a transportation system designed to provide a broad range of transportation choices. Less dense regions may develop transportation networks that rely on high-volume roadways designed for maximum speed, efficiency, or access to specific nodes (like employment centers).

Of the four NTPP communities, Minneapolis, the eastern urbanized portion of Marin, and Columbia are densely populated (Figure 1.1); Minneapolis and Columbia include major universities. Sheboygan is sparsely populated. The control community (Spokane) has about half as many persons per square mile as Minneapolis, and about 50 percent more persons per square mile as the average among pilot communities. It should be noted that both Marin and Sheboygan have varied development patterns, with some undeveloped protected areas, dispersed corridor development, and densely built-out communities. Expectations for mode shift will differ across these varied geographies, and nonmotorized investments in each of these two pilots will center on the more developed (or densely populated) regions of their communities.

Figure 1.1: Population Density (Persons per Square Mile)

Level of education influences individuals' lifestyle choices, including their transportation choices. Data on the level of educational attainment among the population age 25 and over has been gathered for each NTPP community, and might later be correlated to mode shift and changes in transportation patterns (Figure 1.2).

Figure 1.2: Educational Attainment for Population Age 25+

It should be noted that these data do not include the share of each community's population currently enrolled in college or graduate school. One-quarter of Columbia's population (26.2 percent) and more than one-tenth of Minneapolis' population (11.3 percent) are currently enrolled in higher education. On average, almost half of the population across all four pilot communities (45.1 percent) has obtained a higher degree. Marin and Sheboygan stand in contrast to one another: more than half of Marin residents (57.5 percent) have a college degree, while an almost identical share of Sheboygan residents (55.5 percent) attained a high school diploma (or equivalent), or less.

As with educational attainment, household income influences individual lifestyle choices, including transportation and mobility decisions (Figure 1.3). Households with incomes above the national median may be able to spend more on transportation costs. Households with lower median incomes may be more limited in their transportation options. In some cases, travelers may choose automobiles or transit; in other cases they may choose nonmotorized options. In all four pilot communities and in the control community, median household income (in 2006 dollars) is well above the current U.S. poverty level of $20,000. Note, however, that the range among communities is large - more than $40,000 separates median incomes in Marin and Minneapolis.

Figure 1.3: Median Household Income (in 2006 dollars)

TRAVEL BEHAVIOR

The average number of minutes an individual spends commuting to work can influence mobility decisions and commuting patterns. Issues such as traffic congestion, rising gasoline prices, and growing distances between work and home could prompt individuals to expand their chosen modes of transportation to include transit or nonmotorized options, perhaps in combination. Among the four pilot communities, Marin residents experience the longest work commutes at more than half an hour (Figure 1.4). Columbia residents experience the shortest commute, at approximately one-quarter hour. The data displayed in this figure are obtained from the 2000 decennial U.S. Census; directly comparable data will need to be gathered through other sources at the closing stages of the pilot program, as new Census data will not be readily available in 2010.

Figure 1.4: Average Commute Time (in Minutes)

How long it takes an individual to get to work depends on the worker's means of commute. In all four pilot communities (Figure 1.5), an overwhelming share of workers age 16 and over commutes by vehicle (including carpooling and driving alone). Note, however, that Minneapolis has a relatively high share of workers commuting by walking, public transit and other means. It is also interesting to note that Marin displays more than double the number of "work-at-home" workers than the other communities.

Figure 1.5: Means of Commute (for Workers Age 16+)

This summary begins to paint a picture of each community using selected demographic characteristics, and will help us understand the kinds of transportation choices residents make. This information helps define the community context for the four pilot programs, and can be valuable when juxtaposed against each pilot's use of program funds to generate positive impacts in their communities.

Finally, please see Tables 1.2 and 1.3, and their related notes. The tables include data provided by various sources, including the pilot communities, State Departments of Transportation (SDOTs), the Federal Transit Administration (FTA), and the University of Minnesota (through its Phase I research).

Table 1.2 presents information about each community's existing transportation network, while Table 1.3 presents information about transportation usage, and travel behavior. Both tables provide additional context for the individual descriptions of NTPP activities in the four pilot communities that appear in Chapter 2.

¹ "Vehicles Available for Maximum Service" from Federal Transit Administration's National Transit Database 2005 Transit Agency Profiles.

² From Federal Transit Administration's National Transit Database 2005 Data Tables (Table 23).

³ Number of ferryboat vehicles operated in maximum service by Golden Gate Bridge, Highway and Transportation District from Federal Transit Administration's National Transit Database 2005 Data Tables (Table 24)

⁴ "Annual Vehicle Revenue Miles" from Federal Transit Administration's National Transit Database 2005 Transit Agency Profiles. This figure represents the number of miles that vehicles travel while in revenue service. Vehicle revenue miles (VRM) include layover/recovery time, but exclude deadhead, operator training and maintenance testing, as well as school bus and charter services.

⁵ "Total Fare Revenues Earned" from Federal Transit Administration's National Transit Database 2005 Transit Agency Profiles.