Streetscapes and Walkability
October 28th, 2010, by Jeremy Krygsman
3.0 Research Methods
The purpose of this project is to understand whether green spaces can act as a tool to promote walkability. The report aims to answer several research questions by drawing conclusions from the collected quantitative and qualitative data. Listed below are the primary and subsequent research questions.
Primary Research Question:
- How do we implement green spaces in urban environments, and what implications or benefits do they pose on pedestrian reform and livability?
- What factors contribute to the creation of green spaces, and what economic tradeoffs are present in the creation of these spaces in urban environments?
Secondary Research Question:
- How will the inclusion of green spaces impact the liveability and health of the community?
- What elements at both large and small scales can be implemented to achieve a greener community?
- How will green environments improve walkability, and reduce the dependency of the automobile?
In addition to using published secondary sources as a basis for our report, primary research was conducted in the form of a survey. In order to actively engage the participants, a series of computer landscape visualizations (videos) were used as the basis for the survey questions. The following section discusses: (1) study site, (2) procedures used to collect data, and (3) procedures used to analyze data.
1. Study Site:
For this research the visualizations were not based on an actual site, however, computer visualizations were created in order to ensure a controlled environment. By using a virtual environment, variables that could potentially affect the outcome of the data are exempted throughout all visualizations as they remain consistent across varied levels of greenery. Pedestrians were not included in any of the visualizations in order to mitigate a bias that the landscape promoted a false perception of walkability and sociability. Instead, the main goal was that participants would focus on differing levels of greenery, rather than the inclusion of secondary elements, such as pedestrians. In this manner, the independent variable was the changing levels of vegetation. The only moving object within all visualizations is the traffic. It is important to note that the amount and type of vehicles remained constant throughout all the visualizations, once again to avoid bias. Furthermore the speed of traffic remained the same within all visualizations. To further decrease the bias of participants, street lighting in each environment remained the same. Thus, the only changing variable of the streetscape is the level of vegetation which changes for each video.
The environment was constructed with the idea of a typical urban main street in mind, with two to three storey buildings fronting onto the street, with 5m wide sidewalks and a four lane road in the centre. This sort of streetscape is analogous to main streets in many cities in Ontario. In the default environment, used in the first level of greenery, the sidewalk is entirely concrete, and combined with the roadway and buildings, the streetscape is very much a hard landscape. From there, amount of greenery increases in levels listed in the section below, until the environment is filled with flowers and large, leafy trees.
The computed videos were constructed in order to recreate a typical urban street that is analogous within many Ontarian cities. Two to three storey buildings were included as well as a 5 meter wide sidewalks and a four lane road. The first video (level 1), also known hereafter as the “control,” depicts a sidewalk made entirely of concrete. A total of 4 varying levels of greenery were created, each displayed during the day and at night (providing a total of 8 videos). Thus level 4 has the greatest inclusion of vegetation. The specific vegetation for each level is outlined below.
2. Procedures used to collect data:
a. To interpret the importance of green environments and the impact at varied levels, computer visualizations (videos) were used as a conceptual tool for the study of users‟ perception of walkability with varied green environments. The surveyed participants consisted mainly of students from the University of Waterloo, however a limited number from an older demographic (50 years and above).
b. Four levels of greening were used to gauge walkability and safety, both during the day and at night. The levels of greening are depicted to the left.
c. The survey consisted of the Likert scale and open-ended questions. The following questions were asked after viewing a set of videos representing a level of greening both during the day and at night:
- Please rate your experience walking through this area (Scale of 1-5).
- Please rate how safe you feel walking through this environment during the day (Scale of 1-5).
- Please rate how safe you feel walking through this environment during the night (Scale of 1-5).
- Which option did you prefer to walk in and why?
- What elements of your preferred space add to your In your opinion did you feel safer walking in the environment during the day rather than at night?
d. The sequence of videos viewed by the participants was organized in a specific order with the purpose of eliminating bias. The videos were presented in the following order: level 3, level 1, level 4, and level 2 (contents of greenery as noted above). This order was chosen to set an appropriate scale for the viewer by allowing them to view a „mid-range‟ view first, followed by alternating levels of greenery.
3. Procedures used to analyze data:
a. The collected data was analyzed through statistical analysis using Statistical Package for the Social Sciences (SPSS). SPSS is an invaluable tool and one of the most common programs using for statistical procedures (SPSS, 2010). SPSS aided in defining which features hold the greatest value in promoting walkability.
b. Green spaces were treated as the independent variable, with the lowest quality video as the basis for comparison. Thus this level was treated as the control in relation to all other visualizations.
c. Statistical analysis methods included the simple mean, median and mode measurements, frequency of rankings, normality tests (Shapiro-Wilk), Friedman‟s Anova, Wilcoxon‟s Non-parametric test, and effect sizes (Cohens D).