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Exploring the coherence and divergence between the objective and subjective measurement of streetscape perceptions at the neighborhood level: A case study in Shanghai

Author

Listed:
  • Qiwei Song
  • Yuxian Fang
  • Meikang Li
  • Jeroen van Ameijde
  • Waishan Qiu

Abstract

Understanding micro-level perceptions of street scenes is highly concerned with residents’ behaviors and socioeconomic outcomes. While many studies rely on objective measures, such as physical features extracted from Street View Imagery (SVI) to proxy perceptions using derived formulas, others employ subjective measures from visual surveys to capture more subtle human perceptions. We argue that the two measurements can diverge significantly over the same perception concept, which might lead to opposite spatial implications in policy if not properly understood. Moreover, as perceptions are often examined individually, few studies have investigated their joint distribution patterns to reflect perceptions’ multi-dimensional nature. To fill the gaps, we collected five pairwise perceptions from SVIs (i.e., complexity, enclosure, greenness, imageability, and walkability) at the neighborhood level in Shanghai. Each perception consists of pairwise values subjectively measured using a GeoAI-based approach and objectively quantified using formulas. We statistically and spatially compared the coherence and divergence of the two measures, further examining the perceptual differences. Advanced techniques including cluster analysis and factor analysis were employed to jointly evaluate their spatial distribution discrepancy. Our results revealed more differences than similarities between the two measures statistically and spatially, confirming any spatial implications concluded from one approach can vary significantly from the other. The joint spatial pattern further corroborated our conclusions. Our study enriches the literature on micro-level street perception measures, uncovers their critical differences to guide future comparative studies, and offers new approaches for urban perception mapping.

Suggested Citation

  • Qiwei Song & Yuxian Fang & Meikang Li & Jeroen van Ameijde & Waishan Qiu, 2025. "Exploring the coherence and divergence between the objective and subjective measurement of streetscape perceptions at the neighborhood level: A case study in Shanghai," Environment and Planning B, , vol. 52(5), pages 1231-1251, June.
  • Handle: RePEc:sae:envirb:v:52:y:2025:i:5:p:1231-1251
    DOI: 10.1177/23998083241292680
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    References listed on IDEAS

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    1. Su, Shiliang & Zhou, Hao & Xu, Mengya & Ru, Hu & Wang, Wen & Weng, Min, 2019. "Auditing street walkability and associated social inequalities for planning implications," Journal of Transport Geography, Elsevier, vol. 74(C), pages 62-76.
    2. Wang, Xiaoge & Liu, Ye & Zhu, Chunwu & Yao, Yao & Helbich, Marco, 2022. "Associations between the streetscape built environment and walking to school among primary schoolchildren in Beijing, China," Journal of Transport Geography, Elsevier, vol. 99(C).
    3. Philip Salesses & Katja Schechtner & César A Hidalgo, 2013. "The Collaborative Image of The City: Mapping the Inequality of Urban Perception," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-12, July.
    4. Liang Ma & Jason Cao, 2019. "How perceptions mediate the effects of the built environment on travel behavior?," Transportation, Springer, vol. 46(1), pages 175-197, February.
    5. Hanlin Zhou & Lin Liu & Jue Wang & Kathi Wilson & Minxuan Lan & Xin Gu, 2024. "A Multiscale Assessment of the Impact of Perceived Safety from Street View Imagery on Street Crime," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 114(1), pages 69-90, January.
    6. Wu, Fangning & Li, Wenjing & Qiu, Waishan, 2023. "Examining non-linear relationship between streetscape features and propensity of walking to school in Hong Kong using machine learning techniques," Journal of Transport Geography, Elsevier, vol. 113(C).
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