Defining the six neighborhood concepts with the use of a direct measure method and three common built environment measures was an objective exercise to define an abstract concept; however, the next phase proved to be more subjective in nature. The visual representation of six neighborhood types in image sets undoubtedly captures an infinite number of physical elements extending beyond the three measures of activity density, employment entropy, and intersection density utilized to spatially define them. Yet, instead of being regarded solely as a limitation in
efforts to accurately portray a household’s residential environment, the ability to reflect additional attributes in a visual format enables researchers to also account for a multitude of more nuanced features such as housing type, accessibility, etc. that were not originally used to define the concepts. Moreover, a validated process to visually depict these neighborhood concepts provides researchers and decision makers with an additional strategy for expressing quantifiable measures of varying built environments, which are not articulated in technical jargon like density and entropy. The following subsection outlines the set of principles used to guide the image selection process, the collection process, and the results of an internal trial that informed the final neighborhood concept image sets.
3.1.2.1 Image Selection Process
Each of the six neighborhoods was spatially defined by census block group boundaries that were initially defined in a Geographic Information Systems (GIS) environment. To ease the ability of capturing existing physical environments, the information in these spatially defined geographies was converted from a GIS file structure (e.g., shapefile) to a structure adoptable to Google Earth (e.g., KMZ file). This conversion process produced six individual neighborhood concept layers that were then imported into Google Earth and used to identify what block groups in the 25 most populous metropolitan regions belonged to a specific neighborhood concept. In this platform, the research team was able to zoom into a specific block group and capture a screen shot using the Google Street View technology featured within Google Earth. Thus, a street-level image may be selected to visually represent the six objectively defined neighborhood concepts. Using this platform to capture photos to best reflect a particular neighborhood concept offered a number of stylistic decisions to be made by the individual analyst, which involved the decision to screen capture one image rather than another, the camera angle to capture that image, and all of the other seemingly infinite judgments related to these and other aspects of the process. As such, the research team identified a handful of principles to guide the image selection process, while understanding that it was
impossible to standardize this admittedly idiosyncratic process. These guiding principles for the image selection process included:
Portray the neighborhood in the best possible light (i.e., avoid capturing images of general blight or structural decay, which may introduce negative bias in the preference survey).
Avoid the use of images that have specific cultural significance, uniquely identify a particular region, explicitly describe a place, or potentially elicit individual biases (i.e., avoid capturing images of churches, schools, landmarks, geographic names, etc.).
When compiling a set of images for any given neighborhood concept, order the images in a consistent manner that transitions from residential to commercial land uses, while integrating images of the transportation and recreation options
Display each image in the image set for a fixed amount of time in order to control the amount of time an image may be viewed. At the recommendation of Jansen et al (Jansen et al. 2009), such dynamic transitions between images allow
researchers to prevent observers from focusing on any potentially disturbing or distracting details that may be seen as unfavorable.
This process resulted in a set of 15 Google Street View images for each neighborhood concept that were then edited in Adobe Premiere Pro video editing software. The chosen images were next compiled into a set of PowerPoint slide presentations, where each image was displayed for two seconds before automatically transitioning to the next image. The end product was a set of 30-second visual image sets intended to represent the built environment for each neighborhood concept.
3.1.2.2 Internal Trial and Image Set Completion
The completion of the image sets was an iterative process. An internal trial was initially conducted to test the image progression within our visual display technique, eliminate distracting content, minimize respondent biases and burden, and produce an overall favorable reflection for each neighborhood concept in its image set. Respondents to this internal trial were chosen at convenience and represented a non-random sample of individuals including members of the technical advisory committee, graduate students, fellow transportation faculty, and various other professions. Trial respondents were solicited to provide qualitative feedback on the selection of imagery and the
understandability of select questions in the validation pilot survey (Section 3.1.3). Feedback from this trial exercise helped us better understand the number of images needed to visually convey a neighborhood concept without producing respondent burden. Additionally, open-ended responses provided during the internal trial indicated the image sets for neighborhood concepts A and B were too similar, which added difficulty to comparisons of their image sets. This informative finding resulted in the aggregation of the A and B neighborhood concepts into a single concept (AB), reducing the overall number of concepts to five. Section 6.1 provides the final selection of images used to visualize the five objectively-defined neighborhood concepts.