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November 13, 2025LandOpen Access

How Do Street Landscapes Influence Cycling Preferences? Revealing Nonlinear and Interaction Effects Using Interpretable Machine Learning: A Case Study of Xiamen Island

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Authors

PHPengliang HuJHJingnan HuangLFLibo Fang

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Overview

Analysis reveals nonlinear effects of urban mobility factors on cycling preferences in Xiamen, suggesting design improvements for sustainable travel.

Key Points

  • Cycling preferences are influenced by multiple visual indices, significantly shaping urban mobility.
  • Vegetation positively impacts cycling preferences only at higher index levels, indicating design considerations.
  • Exploratory analysis used interpretable machine learning on street view imagery from Xiamen Island.
  • Findings emphasize the importance of built environment features in promoting sustainable travel solutions.

Cite This Study

Hu et al. (2025) studied this question.

synapsesocial.com/papers/692523c6c0ce034ddc354f57https://doi.org/10.3390/land14112253
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Cycling-friendly cities require favorable perceptions of streetscapes in China: the evidence in magnifying the benefits of accessibility and land use mix (Preprint)2024
  2. 2Investigating the Impact of Streetscape and Land Surface Temperature on Cycling Behavior2024 · 5 citations
  3. 3Modeling the impact of street-level built environment on cyclists’ route choice using street view images and GPS data2025
  4. 4Pedaling through preferences: unraveling environmental drivers in cyclists’ route decisions for urban sustainability: a case study of Xiamen, China2026
  5. 5Desirable bikeshare routes: Nonlinear impacts of micro-level street environments2026