The Influence of Built Environment onWalking Behavior: Measurement Issues, Theoretical Considerations, Modeling Methodologies and Chinese Empirical Studies - Space-Time Integration in Geography and GIScience - page 53

5.2.1 Measuring the Built Environment: Objectively

or Subjectively?

In general, objective measures come from data collected in the field (Hoehner
et al. 2005 ) or from existing land use databases available in geographic information
systems (GISs) (Lin and Moudon 2010 ). The majority of studies show that both
objective and subjective attributes are related to walking behavior (Handy et al.
2002 ; Lee and Moudon 2004 ). Subjective measures are self-reported perceptions of
the environment obtained from survey questionnaires (Humpel et al. 2004 ). In urban
planning and transportation, most empirical studies do not incorporate subjective
factors. Some researchers argue that perceptions, attitudes and preferences are diffi-
cult to measure and thus cannot be taken into account (Golledge and Stimson 1997 ;
Gärling et al. 1998 ). Most physical activity studies use subjective environmental
measures, ostensibly because the data are obtained more economically than those of
field-collected objective measures, or because detailed objective GIS land use data
are not yet commonly accessible.

5.2.1.1 Objective Measures

Distance and aesthetics have the most direct influence on walking choice. In higher-
density neighborhoods, land use is compact and destinations are closer, making
walking more advantageous. Diversity indicates a mix of land use (Cervero and
Kockelman 1997 ). Being equipped with more land use types that are within walking
distance is favorable to increase walking rates (Handy and Clifton 2001 ). Density
and diversity are land use indicators in conjunction with transport systems. Design
refers to the aesthetic or quality of the land use and the streetscape, including the
presence and attractiveness of natural sights (e.g. trees, hills), recreational facilities
(e.g. public open spaces, private gardens), architectural design and pollution levels.
Transit use is classified as active travel because it almost always requires walking
at one or both ends of the trip (Besser and Dannenberg 2005 ); hence, distance to
transit is an indicator. Areas well served by public transit have bus or rail stops
within convenient walking distance, which could decrease automobile dependence.
Though their division is ambiguous and unsettled, these D variables are useful
in organizing the empirical literature. However, the effects of distance and aesthetic
factors may vary depending on the behavior types being studied, the competitiveness
of other modal choices, the destination to be accessed and the quality of the desti-
nation to the user (Giles-Corti et al. 2005 ). One variable may have both positive and
negative effects. For example, density can increase the capability of direct access,
but lower travel speeds. Land use mixing reduces trip costs by placing destinations
closer to origins. This could induce more trips and people probably travel further at
the same cost, but to get more opportunities and benefits (Boarnet and Crane 2001 ;