How are Neighborhood and Street-Level Walkability Factors Associated with Walking Behaviors? A Big Data Approach Using Street View Images. Issue 1 (January 2022)

• Record Type: Journal Article
• Authors: Koo, Bon Woo; Guhathakurta, Subhrajit; Botchwey, Nisha
• Is Part Of: Environment and behavior. Volume 54:Issue 1(2022)
• Page Start: 211
• Page End: 241
• Publication Date: 2022-01
• Subjects: the scale of measurements -- walkability -- streetscapes -- street view images -- computer vision; Human ecology -- Periodicals; 304.2
• DOI: 10.1177/00139165211014609
• Languages: English
• ISSNs: 0013-9165

Abstract

The built environment characteristics associated with walkability range from neighborhood-level urban form factors to street-level urban design factors. However, many existing walkability indices are based on neighborhood-level factors and lack consideration for street-level factors. Arguably, this omission is due to the lack of a scalable way to measure them. This paper uses computer vision to quantify street-level factors from street view images in Atlanta, Georgia, USA. Correlation analysis shows that some streetscape factors are highly correlated with neighborhood-level factors. Binary logistic regressions indicate that the streetscape factors can significantly contribute to explaining walking mode choice and that streetscape factors can have a greater association with walking mode choice than neighborhood-level factors. A potential explanation for the result is that the image-based streetscape factors may perform as proxies for some macroscale factors while representing the pedestrian experience as seen from eye-level.