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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 211-241 |
| Number of pages | 31 |
| Journal | Environment and Behavior |
| Volume | 54 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2022 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© The Author(s) 2021.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- computer vision
- street view images
- streetscapes
- the scale of measurements
- walkability
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